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Genetic and Phenotypic Correlation: Gene–Disease Validation Series II
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Genetic and Phenotypic Correlation: Gene–Disease Validation Series II

A special issue of Genes (ISSN 2073-4425). This special issue belongs to the section "Human Genomics and Genetic Diseases".

Deadline for manuscript submissions: closed (20 July 2024) | Viewed by 4539

Special Issue Editors

Dr. Yu An

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Guest Editor
Human Phenome Institute, Fudan University, Shanghai, China
Interests: genetics and genomics; developmental disorder; neurodevelopmental disorder; genetic counseling; translational medicine
Special Issues, Collections and Topics in MDPI journals
Dr. Hong Guo

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Guest Editor
Department of Medical Genetics, College of Basic Medical Sciences, Army Medical University, Chongqing, China
Interests: genetic
Dr. Yiran Guo

E-Mail Website
Guest Editor
Center for Data Driven Discovery in Biomedicine, Children’s Hospital of Philadelphia, Philadelphia, PA, USA
Interests: bioinformatics; rare/common diseases; human genomics/genetics; medical genomics/genetics; clinical genomics/genetics; cancer genomics/genetics
Dr. Junyu Zhang

E-Mail Website
Guest Editor
Department of Reproductive Genetics, Obstetrics and Gynecology Hospital of Tongji University, 2699 West Gaoke Road, Shanghai 201204, China
Interests: reproductive genetics; gene disease validity; variant interpretation
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

With the increasing use of genomic sequencing technology, a significant number of genes contributing to Mendelian disorders can be rapidly identified. However, the clinical utility of this technology bottlenecks at variant interpretation. Substantial gaps in the knowledge base necessitate more information on gene disease validation, especially genetic or experimental evidence on variants of known genes, which can clarify the correlation between genotype and phenotype.

The “one-gene-one-disease” paradigm has been challenged by multiple disease traits caused by one gene or one locus in one gene. At times, face lumping and the splitting conundrum are necessary to evaluate the validity of a gene–disease relationship. However, variable expressivity and the incomplete penetrance of recurrent variants make genetic diagnosis challenging. More genetic and experimental evidence could enhance our understanding of the role of genetic etiology in diseases; filling this research gap constitutes the genetic basis for improving precision medicine.

This Special Issue welcomes a variety of research papers, including systematic reviews of the genotype–phenotype correlation, detailed studies on genetic and experimental evidence of gene alteration, and novel insights into the genetic mechanism of rare genetic diseases, involving both the modifier factor discovery and expanded clinical phenotype of genetic variants.

Dr. Yu An
Dr. Hong Guo
Dr. Yiran Guo
Dr. Junyu Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Genes is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • developmental disorder
  • neurodevelopment
  • birth defect
  • genetic disorder
  • gene discovery
  • next-generation sequencing (NGS)
  • whole-exome/genome sequencing
  • molecular biology
  • animal modeling
  • genotype
  • phenotype
  • gene curation
  • pathogenesis
  • modifier
  • variant interpretation

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Published Papers (4 papers)

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Research

17 pages, 600 KiB  
Article
Mortality in Patients with 22q11.2 Rearrangements
by Melisa Cilio Arroyuelo, Jair Tenorio-Castano, Luis Fernández García-Moya, Alejandro Parra, Mario Cazalla, Natalia Gallego, Lucía Miranda, María Ángeles Mori, Luis García-Gueretta, Carlos Labrandero, Elena Mansilla, Emi Rikeros, Fe García-Santiago, Isabel Vallcorba, Pedro Arias, Cristina Silván, Lucia Deiros Bronte, Julián Nevado and Pablo Lapunzina
Genes 2024, 15(9), 1146; https://doi.org/10.3390/genes15091146 - 30 Aug 2024
Viewed by 827
Abstract
The 22q11.2 region is highly susceptible to genomic rearrangements leading to multiple genomic disorders, including 22q11.2 microdeletion syndrome (22q11.2 DS) (MIM# 188400), 22q11.2 microduplication syndrome (MIM# 608363), supernumerary der(22)t(11;22) syndrome (also known as Emanuel Syndrome; MIM# 609029), and Cat Eye Syndrome (MIM# 115470). [...] Read more.
The 22q11.2 region is highly susceptible to genomic rearrangements leading to multiple genomic disorders, including 22q11.2 microdeletion syndrome (22q11.2 DS) (MIM# 188400), 22q11.2 microduplication syndrome (MIM# 608363), supernumerary der(22)t(11;22) syndrome (also known as Emanuel Syndrome; MIM# 609029), and Cat Eye Syndrome (MIM# 115470). In this study, we present data on causes of mortality, average age of death, and the existing associated risk factors in patients with 22q11.2 rearrangements. Our cohort included 223 patients (120 males and 103 females) with confirmed diagnoses of 22q11.2 rearrangements diagnosed through molecular techniques (FISH, MLPA, and CMA). Relatives from patients who have been molecularly confirmed with 22q11.2 rearrangements have also been added to the study, regardless of the presence or absence of symptoms. Of these 223 individuals, 21 (9.4%) died. Deceased patients’ rearrangements include 19 microdeletions, 1 microduplication, and 1 patient with a marker chromosome. The median age of death was 3 months and 18 days (ranging from 3 days to 34 years). There were 17 patients who died at pediatric age (80.95%), 3 died at adult age (14.28%), and for 1 of whom, the age of death is unknown (4.76%). Eighteen patients were White Mediterranean (European non-Finnish) (85.71%) whereas three were Amerindian (South American) (14.28%). Mortality from cardiac causes accounted for 71.42%. The second most frequent cause of death was sepsis in two patients (9.52%). One patient died from respiratory failure (4.76%) and one from renal failure (4.76%). Information regarding the cause of death was not available in two patients (9.52%). Most patients who died were diagnosed within the first week of life, the majority on the first day. This study adds additional information on mortality in one of the largest cohorts of patients with 22q11.2 rearrangements in more than 30 years of follow-up. Full article
(This article belongs to the Special Issue Genetic and Phenotypic Correlation: Gene–Disease Validation Series II)
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10 pages, 592 KiB  
Article
Novel Loss-of-Function SYCP2 Variants in Infertile Males Upgrade the Gene–Disease Clinical Validity Classification for SYCP2 and Male Infertility to Strong
by Jinli Li, Samantha L.P. Schilit, Shanshan Liang, Ningxin Qin, Xiaoming Teng and Junyu Zhang
Genes 2024, 15(8), 1092; https://doi.org/10.3390/genes15081092 - 19 Aug 2024
Viewed by 1189
Abstract
Male infertility affects approximately 7% of the male population, and about 15% of these cases are predicted to have a genetic etiology. One gene implicated in autosomal dominant male infertility, SYCP2, encodes a protein critical for the synapsis of homologous chromosomes during [...] Read more.
Male infertility affects approximately 7% of the male population, and about 15% of these cases are predicted to have a genetic etiology. One gene implicated in autosomal dominant male infertility, SYCP2, encodes a protein critical for the synapsis of homologous chromosomes during meiosis I, resulting in impaired spermatogenesis. However, the clinical validity of the gene–disease pair was previously categorized as on the border of limited and moderate due to few reported cases. This study investigates the genetic cause of infertility for three unrelated Chinese patients with oligoasthenozoospermia. Whole exome sequencing (WES) and subsequent Sanger sequencing revealed novel heterozygous loss-of-function (LOF) variants in SYCP2 (c.89dup, c.946_947del, and c.4378_4379del). These cases, combined with the previously reported cases, provide strong genetic evidence supporting an autosomal dominant inheritance pattern. The experimental evidence also demonstrates a critical role for SYCP2 in spermatogenesis. Collectively, this updated assessment of the genetic and experimental evidence upgrades the gene–disease association strength of SYCP2 and autosomal dominant male infertility from on the border of limited and moderate to strong. The reclassification improves SYCP2 variant interpretation and qualifies it for the inclusion on diagnostic male infertility gene panels and prioritization in whole exome or genome studies for related phenotypes. These findings therefore improve the clinical interpretation of SYCP2 LOF variants. Full article
(This article belongs to the Special Issue Genetic and Phenotypic Correlation: Gene–Disease Validation Series II)
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12 pages, 3239 KiB  
Article
Exploring the Genotype–Phenotype Correlations in a Child with Inherited Seizure and Thrombocytopenia by Digenic Network Analysis
by Shuanglong Lu, Zhixiao Niu and Xiaohong Qiao
Genes 2024, 15(8), 1004; https://doi.org/10.3390/genes15081004 - 31 Jul 2024
Viewed by 871
Abstract
Understanding the correlation between genotype and phenotype remains challenging for modern genetics. Digenic network analysis may provide useful models for understanding complex phenotypes that traditional Mendelian monogenic models cannot explain. Clinical data, whole exome sequencing data, in silico, and machine learning analysis were [...] Read more.
Understanding the correlation between genotype and phenotype remains challenging for modern genetics. Digenic network analysis may provide useful models for understanding complex phenotypes that traditional Mendelian monogenic models cannot explain. Clinical data, whole exome sequencing data, in silico, and machine learning analysis were combined to construct a digenic network that may help unveil the complex genotype–phenotype correlations in a child presenting with inherited seizures and thrombocytopenia. The proband inherited a maternal heterozygous missense variant in SCN1A (NM_001165963.4:c.2722G>A) and a paternal heterozygous missense variant in MYH9 (NM_002473.6:c.3323A>C). In silico analysis showed that these two variants may be pathogenic for inherited seizures and thrombocytopenia in the proband. Moreover, focusing on 230 epilepsy-associated genes and 35 thrombopoiesis genes, variant call format data of the proband were analyzed using machine learning tools (VarCoPP 2.0) and Digenic Effect predictor. A digenic network was constructed, and SCN1A and MYH9 were found to be core genes in the network. Further analysis showed that MYH9 might be a modifier of SCN1A, and the variant in MYH9 might not only influence the severity of SCN1A-related seizure but also lead to thrombocytopenia in the bone marrow. In addition, another eight variants might also be co-factors that account for the proband’s complex phenotypes. Our data show that as a supplement to the traditional Mendelian monogenic model, digenic network analysis may provide reasonable models for the explanation of complex genotype–phenotype correlations. Full article
(This article belongs to the Special Issue Genetic and Phenotypic Correlation: Gene–Disease Validation Series II)
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16 pages, 1858 KiB  
Article
Genotype–Phenotype Correlations in Alport Syndrome—A Single-Center Experience
by Ștefan Nicolaie Lujinschi, Bogdan Marian Sorohan, Bogdan Obrișcă, Alexandra Vrabie, Gabriela Lupușoru, Camelia Achim, Andreea Gabriella Andronesi, Andreea Covic and Gener Ismail
Genes 2024, 15(5), 593; https://doi.org/10.3390/genes15050593 - 7 May 2024
Cited by 1 | Viewed by 1172
Abstract
Background: Alport syndrome (AS) is a common and heterogeneous genetic kidney disease, that often leads to end-stage kidney disease (ESKD). Methods: This is a single-center, retrospective study that included 36 adults with type IV collagen (COL4) mutations. Our main scope was to describe [...] Read more.
Background: Alport syndrome (AS) is a common and heterogeneous genetic kidney disease, that often leads to end-stage kidney disease (ESKD). Methods: This is a single-center, retrospective study that included 36 adults with type IV collagen (COL4) mutations. Our main scope was to describe how genetic features influence renal survival. Results: A total of 24 different mutations were identified, of which eight had not been previously described. Mutations affecting each of the type IV collagen α chains were equally prevalent (33.3%). Most of the patients had pathogenic variants (61.1%). Most patients had a family history of kidney disease (71%). The most prevalent clinical picture was nephritic syndrome (64%). One-third of the subjects had extrarenal manifestations, 41.6% of patients had ESKD at referral, and another 8.3% developed ESKD during follow-up. The median renal survival was 42 years (95% CI, 29.98–54.01). The COL4A4 group displayed better renal survival than the COL4A3 group (p = 0.027). Patients with missense variants had higher renal survival (p = 0.023). Hearing loss was associated with lower renal survival (p < 0.001). Conclusions: Patients with COL4A4 variants and those with missense mutations had significantly better renal survival, whereas those with COL4A3 variants and those with hearing loss had worse prognoses. Full article
(This article belongs to the Special Issue Genetic and Phenotypic Correlation: Gene–Disease Validation Series II)
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