Bi-allelic truncating variants in CFAP206 cause male infertility in human and mouse

Shen, Qunshan; Martinez, Guillaume; Liu, Hongbin; Beurois, Julie; Wu, Huan; Amiri-Yekta, Amir; Liang, Dan; Bidart, Marie; Cazin, Caroline; Celse, Tristan; Satre, Véronique; Thierry‐Mieg, Nicolas; Whitfield, Marjorie; Touré, Aminata; Song, Bing; Lv, Mingrong; Li, Kuokuo; Liu, Chunyu; Tao, Fangbiao; He, Xiaojin; Zhang, Feng; Arnoult, Christophe; Ray, Pierre F.; Cao, Yunxia; Coutton, Charles

doi:10.1007/s00439-021-02313-z

Cited by 35 publications

(27 citation statements)

References 29 publications

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“…Second, the sample size of the training cohort was relatively limited, and the external validation was not performed due to the difficulty to collect additional samples. Further studies are needed to accomplish the validation of the predictive model under a systems-level through integrating genomic and clinical information 45 – 48 , and explore the potential causal effects of these risk factors associated with postoperative hemorrhage under a Mendelian randomization framework 49 – 51 . As the LPD procedures were recommended by the Study Group of Pancreatic Surgery in the Chinese Society of Surgery of Chinese Medical Association 52 , our predictive model can be used only in patients who underwent LPD in the same surgical manner.…”

Section: Discussionmentioning

confidence: 99%

Nomogram and a predictive model for postoperative hemorrhage in preoperative patients of laparoscopic pancreaticoduodectomy

Zhang

et al. 2021

Sci Rep

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To develop a predictive model and a nomogram for predicting postoperative hemorrhage in preoperative patients undergoing laparoscopic pancreaticoduodenectomy (LPD). A total of 409 LPD patients that underwent LPD by the same surgical team between January 2014 and December 2020 were included as the training cohort. The preoperative data of patients were statistically compared and analyzed for exploring factors correlated with postoperative hemorrhage. The predictive model was developed by multivariate logistic regression and stepwise (stepAIC) selection. A nomogram based on the predictive model was developed. The discriminatory ability of the predictive model was validated using the receiver operating characteristic (ROC) curve and leave-one-out method. The statistical analysis was performed using R 3.5.1 (www.r-project.org). The predictive model including the risk-associated factors of postoperative hemorrhage was as follows: 2.695843 − 0.63056 × (Jaundice = 1) − 1.08368 × (DM = 1) − 2.10445 × (Hepatitis = 1) + 1.152354 × (Pancreatic tumor = 1) + 1.071354 × (Bile duct tumor = 1) − 0.01185 × CA125 − 0.04929 × TT − 0.08826 × APTT + 26.03383 × INR − 1.9442 × PT + 1.979563 × WBC − 2.26868 × NEU − 2.0789 × LYM − 0.02038 × CREA + 0.00459 × AST. A practical nomogram based on the model was obtained. The internal validation of ROC curve was statistically significant (AUC = 0.7758). The validation by leave-one-out method showed that the accuracy of the model and the F measure was 0.887 and 0.939, respectively. The predictive model and nomogram based on the preoperative data of patients undergoing LPD can be useful for predicting the risk degree of postoperative hemorrhage.

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Section: Discussionmentioning

confidence: 99%

Nomogram and a predictive model for postoperative hemorrhage in preoperative patients of laparoscopic pancreaticoduodectomy

Zhang

et al. 2021

Sci Rep

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“…RS1 is adjacent to the base of the inner dynein arm, while RS2 and RS3are respectively attached to the front and back of the nexin–dynein regulatory complex (N-DRC) and the calmodulin- and spoke-associated complex (CSC) ( Zhu et al, 2017 ). Defects of several genes that encode CSC components have been reported to be related to MMAF, including CFAP61 ( Ma A. et al, 2021 ; Liu M. et al, 2021 ; Hu et al, 2022 ), CFAP91 ( Martinez et al, 2020 ), CFAP206 ( Shen et al, 2021 ) and CFAP251 ( Auguste et al, 2018 ; Kherraf et al, 2018 ; Li W. et al, 2019 ; Wang J. et al, 2021 ). Early in 2007, Dymek and Smith conducted immunoprecipitation experiments using anti-CaM antibodies and found that the CSC is comprised of three polypeptides, namely, CaM-IP2, CaM-IP3 and CaM-IP4, which are also termed as CFAP61, CFAP91 and CFAP251, respectively ( Dymek and Smith, 2007 ).…”

Section: Pathogenic Genes and Their Function Inspermatogenesismentioning

confidence: 99%

Clinical detection, diagnosis and treatment of morphological abnormalities of sperm flagella: A review of literature

Wang

Zheng

et al. 2022

Front. Genet.

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Sperm carries male genetic information, and flagella help move the sperm to reach oocytes. When the ultrastructure of the flagella is abnormal, the sperm is unable to reach the oocyte and achieve insemination. Multiple morphological abnormalities of sperm flagella (MMAF) is a relatively rare idiopathic condition that is mainly characterized by multiple defects in sperm flagella. In the last decade, with the development of high-throughput DNA sequencing approaches, many genes have been revealed to be related to MMAF. However, the differences in sperm phenotypes and reproductive outcomes in many cases are attributed to different pathogenic genes or different pathogenic mutations in the same gene. Here, we will review information about the various phenotypes resulting from different pathogenic genes, including sperm ultrastructure and encoding proteins with their location and functions as well as assisted reproductive technology (ART) outcomes. We will share our clinical detection and diagnosis experience to provide additional clinical views and broaden the understanding of this disease.

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“…Interestingly, in humans, mutations in genes orthologous to SPEF2A (SPEF2) and CFAP69 turned out to cause MMAF and very rarely PCD (until now, only mutations in SPEF2 were connected to PCD) [190][191][192][193][194][195]. Among other MMAF-causative genes [196,197] studied in Tetrahymena are, as mentioned before, CFAP43 and CFAP44 [127,[198][199][200][201][202], the CSC subunits CFAP61 [203,204] and CFAP251 [204,205], and CFAP206, which forms a part of the RS2 base [126,196].…”

Section: Ciliate: Tetrahymena and Parameciummentioning

confidence: 99%

PCD Genes—From Patients to Model Organisms and Back to Humans

Niziolek

Osinka

Samsel

et al. 2022

IJMS

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Primary ciliary dyskinesia (PCD) is a hereditary genetic disorder caused by the lack of motile cilia or the assembxly of dysfunctional ones. This rare human disease affects 1 out of 10,000–20,000 individuals and is caused by mutations in at least 50 genes. The past twenty years brought significant progress in the identification of PCD-causative genes and in our understanding of the connections between causative mutations and ciliary defects observed in affected individuals. These scientific advances have been achieved, among others, due to the extensive motile cilia-related research conducted using several model organisms, ranging from protists to mammals. These are unicellular organisms such as the green alga Chlamydomonas, the parasitic protist Trypanosoma, and free-living ciliates, Tetrahymena and Paramecium, the invertebrate Schmidtea, and vertebrates such as zebrafish, Xenopus, and mouse. Establishing such evolutionarily distant experimental models with different levels of cell or body complexity was possible because both basic motile cilia ultrastructure and protein composition are highly conserved throughout evolution. Here, we characterize model organisms commonly used to study PCD-related genes, highlight their pros and cons, and summarize experimental data collected using these models.

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Bi-allelic truncating variants in CFAP206 cause male infertility in human and mouse

Cited by 35 publications

References 29 publications

Nomogram and a predictive model for postoperative hemorrhage in preoperative patients of laparoscopic pancreaticoduodectomy

Nomogram and a predictive model for postoperative hemorrhage in preoperative patients of laparoscopic pancreaticoduodectomy

Clinical detection, diagnosis and treatment of morphological abnormalities of sperm flagella: A review of literature

PCD Genes—From Patients to Model Organisms and Back to Humans

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