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Pathogenic / Likely pathogenic variants in connective tissue and related disorders gene panel and anamnesis of patients with cervical insufficiency.

Journal: PLOS ONE

Article Title: Unravelling the genetic landscape of cervical insufficiency: Insights into connective tissue dysfunction and hormonal pathways

doi: 10.1371/journal.pone.0310718

Figure Lengend Snippet: Pathogenic / Likely pathogenic variants in connective tissue and related disorders gene panel and anamnesis of patients with cervical insufficiency.

Article Snippet: We compiled a connective disorder gene panel by accessing data from the PanelApp database’s homepage ( https://panelapp.genomicsengland.co.uk/ ), encompassing genes from EDS, OI, and Stickler syndrome panels (n = 102, ).

Techniques: Sequencing, RNA Expression

A) Expression (Y axis) of connective tissue disorder genes (blue) in relation to all genes showing at least some expression within cervix (TPM>0) (light blue) (X axis). B) Beighton (pink) / Brighton (blue) / Total score (green) (Y axis) obtained by each study patient (X axis) in the connective tissue disfunction assessment questionnaire. C) Patients age (X-axis) correlation with Beighton hypermobility score (Y-axis). A larger circle size indicates a greater number of patients with the same age and Beighton score. D) Total score obtained in connective tissue dysfunction assessment questionnaire (X-axis) correlation with number of rare damaging gene variants in connective tissue gene panel (Y-axis). A larger circle size indicates a greater number of patients with the same score and number of rare variants.

Journal: PLOS ONE

Article Title: Unravelling the genetic landscape of cervical insufficiency: Insights into connective tissue dysfunction and hormonal pathways

doi: 10.1371/journal.pone.0310718

Figure Lengend Snippet: A) Expression (Y axis) of connective tissue disorder genes (blue) in relation to all genes showing at least some expression within cervix (TPM>0) (light blue) (X axis). B) Beighton (pink) / Brighton (blue) / Total score (green) (Y axis) obtained by each study patient (X axis) in the connective tissue disfunction assessment questionnaire. C) Patients age (X-axis) correlation with Beighton hypermobility score (Y-axis). A larger circle size indicates a greater number of patients with the same age and Beighton score. D) Total score obtained in connective tissue dysfunction assessment questionnaire (X-axis) correlation with number of rare damaging gene variants in connective tissue gene panel (Y-axis). A larger circle size indicates a greater number of patients with the same score and number of rare variants.

Article Snippet: We compiled a connective disorder gene panel by accessing data from the PanelApp database’s homepage ( https://panelapp.genomicsengland.co.uk/ ), encompassing genes from EDS, OI, and Stickler syndrome panels (n = 102, ).

Techniques: Expressing

We were the first to apply the Beighton/Brighton criteria to test the hypothesis linking the connective tissue dysfunction-driven nature of CI to genetics. While our analysis strengthened the association of CI with connective tissue pathways, further research is needed to explore the relationships between subclinical phenotypic expressions of connective tissue disorders and CI. Our next hypothesis is that the use of Beighton/Brighton criteria, along with the connective tissue dysfunction assessment questionnaire developed by our group, can serve as a predictive tool for CI/PTB, at least for a subset of patients. This investigation is currently underway in our group.

Journal: PLOS ONE

Article Title: Unravelling the genetic landscape of cervical insufficiency: Insights into connective tissue dysfunction and hormonal pathways

doi: 10.1371/journal.pone.0310718

Figure Lengend Snippet: We were the first to apply the Beighton/Brighton criteria to test the hypothesis linking the connective tissue dysfunction-driven nature of CI to genetics. While our analysis strengthened the association of CI with connective tissue pathways, further research is needed to explore the relationships between subclinical phenotypic expressions of connective tissue disorders and CI. Our next hypothesis is that the use of Beighton/Brighton criteria, along with the connective tissue dysfunction assessment questionnaire developed by our group, can serve as a predictive tool for CI/PTB, at least for a subset of patients. This investigation is currently underway in our group.

Article Snippet: We compiled a connective disorder gene panel by accessing data from the PanelApp database’s homepage ( https://panelapp.genomicsengland.co.uk/ ), encompassing genes from EDS, OI, and Stickler syndrome panels (n = 102, ).

Techniques: