CDH5, a Possible New Candidate Gene for Genetic Testing of Lymphedema

TIE1 as a Candidate Gene for Lymphatic Malformations with or without Lymphedema

International Journal of Molecular Sciences ◽

10.3390/ijms21186780 ◽

2020 ◽

Vol 21 (18) ◽

pp. 6780 ◽

Cited By ~ 1

Author(s):

Sandro Michelini ◽

Maurizio Ricci ◽

Dominika Veselenyiova ◽

Sercan Kenanoglu ◽

Danjela Kurti ◽

...

Keyword(s):

Endothelial Cells ◽

Genetic Testing ◽

Cell Surface ◽

Candidate Gene ◽

Lymphatic System ◽

Surface Protein ◽

Cell Surface Protein ◽

Lymphatic Malformations ◽

Familial Cases ◽

A Cell

TIE1 is a cell surface protein expressed in endothelial cells. Involved in angiogenesis and lymphangiogenesis, including morphogenesis of lymphatic valves, TIE1 is important for lymphatic system functional integrity. The main purpose of this study was to identify different variants in the TIE1 gene that could be associated with lymphatic malformations or dysfunction and predisposition for lymphedema. In a cohort of 235 Italian lymphedema patients, who tested negative for variants in known lymphedema genes, we performed a further test for new candidate genes, including TIE1. Three probands carried different variants in TIE1. Two of these segregated with lymphedema or lymphatic dysfunction in familial cases. Variants in TIE1 could contribute to the onset of lymphedema. On the basis of our findings, we propose TIE1 as a candidate gene for comprehensive genetic testing of lymphedema.

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PALB2 as Another Candidate Gene for Genetic Testing in Patients with Hereditary Breast Cancer in Czech Republic

Klinicka onkologie ◽

10.14735/amko2016s31 ◽

2016 ◽

Vol 29 (Suppl 1) ◽

pp. S31-S34 ◽

Cited By ~ 3

Author(s):

Markéta Janatová ◽

Marianna Borecká ◽

Jana Soukupová ◽

Petra Kleiblová ◽

Jana Stříbrná ◽

...

Keyword(s):

Breast Cancer ◽

Czech Republic ◽

Genetic Testing ◽

Candidate Gene ◽

Hereditary Breast Cancer

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Whole-exome sequencing gives additional benefits compared to candidate gene sequencing in the molecular diagnosis of children with growth hormone or IGF-1 insensitivity

Acta Endocrinologica ◽

10.1530/eje-17-0453 ◽

2017 ◽

Vol 177 (6) ◽

pp. 485-501 ◽

Cited By ~ 12

Author(s):

Lucy Shapiro ◽

Sumana Chatterjee ◽

Dina G Ramadan ◽

Kate M Davies ◽

Martin O Savage ◽

...

Keyword(s):

Genetic Testing ◽

Candidate Gene ◽

Short Stature ◽

Exome Sequencing ◽

Whole Exome Sequencing ◽

Genetic Variants ◽

Genetic Defect ◽

Significant Proportion ◽

Genetic Diagnosis ◽

Whole Exome

Background GH insensitivity (GHI) is characterised by short stature, IGF-1 deficiency and normal/elevated serum GH. IGF-1 insensitivity results in pre- and post-natal growth failure with normal/high IGF-1 levels. The prevalence of genetic defects is unknown. Objective To identify the underlying genetic diagnoses in a paediatric cohort with GH or IGF-1 insensitivity using candidate gene (CGS) and whole-exome sequencing (WES) and assess factors associated with the discovery of a genetic defect. Methods We undertook a prospective study of 132 patients with short stature and suspected GH or IGF-1 insensitivity referred to our centre for genetic analysis. 107 (96 GHI, 88 probands; 11 IGF-1 insensitivity, 9 probands) underwent CGS. WES was performed in those with no defined genetic aetiology following CGS. Results A genetic diagnosis was discovered 38/107 (36%) patients (32% probands) by CGS. WES revealed 11 patients with genetic variants in genes known to cause short stature. A further 2 patients had hypomethylation in the H19/IGF2 region or mUPD7 consistent with Silver–Russell Syndrome (total with genetic diagnosis 51/107, 48% or 41/97, 42% probands). WES also identified homozygous putative variants in FANCA and PHKB in 2 patients. Low height SDS and consanguinity were highly predictive for identifying a genetic defect. Conclusions Comprehensive genetic testing confirms the genetic heterogeneity of GH/IGF-1 insensitivity and successfully identified the genetic aetiology in a significant proportion of cases. WES is rapid and may isolate genetic variants that have been missed by traditional clinically driven genetic testing. This emphasises the benefits of specialist diagnostic centres.

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KidneyNetwork: Using kidney-derived gene expression data to predict and prioritize novel genes involved in kidney disease

10.1101/2021.03.10.21253054 ◽

2021 ◽

Author(s):

Floranne Boulogne ◽

Laura R. Claus ◽

Henry Wiersma ◽

Roy Oelen ◽

Floor Schukking ◽

...

Keyword(s):

Genetic Testing ◽

Kidney Disease ◽

Candidate Gene ◽

Specific Gene ◽

Sequencing Data ◽

Specific Expression ◽

Disease Phenotypes ◽

Exome Sequencing Data ◽

Pathogenic Variants ◽

Gene Functions

AbstractBackgroundGenetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the disorder as potentially pathogenic variants can reside in genes that are not yet known to be involved in kidney disease. To help identify these genes, we have developed KidneyNetwork, that utilizes tissue-specific expression to predict kidney-specific gene functions.MethodsKidneyNetwork is a co-expression network built upon a combination of 878 kidney RNA-sequencing samples and a multi-tissue dataset of 31,499 samples. It uses expression patterns to predict which genes have a kidney-related function and which (disease) phenotypes might result from variants in these genes. We applied KidneyNetwork to prioritize rare variants in exome sequencing data from 13 kidney disease patients without a genetic diagnosis.ResultsKidneyNetwork can accurately predict kidney-specific gene functions and (kidney disease) phenotypes for disease-associated genes. Applying it to exome sequencing data of kidney disease patients allowed us to identify a promising candidate gene for kidney and liver cysts: ALG6.ConclusionWe present KidneyNetwork, a kidney-specific co-expression network that accurately predicts which genes have kidney-specific functions and can result in kidney disease. We show the added value of KidneyNetwork by applying it to kidney disease patients without a molecular diagnosis and consequently, we propose ALG6 as candidate gene in one of these patients. KidneyNetwork can be applied to clinically unsolved kidney disease cases, but it can also be used by researchers to gain insight into individual genes in order to better understand kidney physiology and pathophysiology.Significance statementGenetic testing in patients with suspected hereditary kidney disease may not reveal the genetic cause for the patient’s disorder. Potentially pathogenic variants can reside in genes not yet known to be involved in kidney disease, making it difficult to interpret the relevance of these variants. This reveals a clear need for methods to predict the phenotypic consequences of genetic variation in an unbiased manner. Here we describe KidneyNetwork, a tool that utilizes tissue-specific expression to predict kidney-specific gene functions. Applying KidneyNetwork to a group of undiagnosed cases identified ALG6 as a candidate gene in cystic kidney and liver disease. In summary, KidneyNetwork can aid the interpretation of genetic variants and can therefore be of value in translational nephrogenetics and help improve the diagnostic yield in kidney disease patients.

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