P666: Classification of nontruncating variants in the PKD1 gene based on the large internal database

Introduction: Autosomal dominant polycystic kidney disease (ADPKD) is generally a late-onset multisystem disorder characterized by bilateral kidney cysts, liver cysts, and an increased risk of intracranial aneurysms.The diagnosis of ADPKD is established through clinical manifestations and genetic testing.Studies indicate that around 78% of ADPKD resulted from (likely) pathogenic variants in the PKD1 gene.However, compared to the truncating variants, evaluating the nontruncating PKD1 variants is still challenging, due to the shortage of consensus criteria and published case reports.Here we demonstrate the combination of internal databases and literature to evaluate the classification of the nontruncating variants in the PKD1 gene.Methods: Patient samples were tested in our laboratory using Next-generation sequencing (NGS) panels, including 385 gene Renasight test, 727 gene Renomatome panel, 78 gene Expanded Polycystic Kidney Disease (with Nephronophthisis) panel, 6 gene Polycystic Kidney Disease panel, and PKD1 single gene panel.We propose the following criteria: for any nontruncating PKD1 variants with an allele frequency less than 8 in gnomADv4.1,a deep literature search will be performed.If the variants are present in our database more than 3 times, clinical information on all the cases will be requested.PS4_supporting is applied for one individual with PKD1 related condition; PS4_moderate is applied for two unrelated individuals with PKD1 related condition; PS4_strong is applied for more than three unrelated individuals with PKD1 related condition.The nontruncating variants will be classified as (likely) pathogenic if multiple individuals with the clinical features match the PKD1 related conditions.If the variants were classified as VUS due to insufficient evidence previously, an updated report will be sent to the ordering physician with the new classification.Results: All the NGS panels are processed according to lab procedures.Up to now, over 122,000 cases of renal diseases are reported in our laboratory.The diagnostic rate is around 27%. Currently, around 2107 out of 8423 PKD1 variants in our database are classified (likely) pathogenic.15% (321 variants) of the (likely) pathogenic variants are nontruncating variants (missense and small INDEL), which is twice the (likely) pathogenic nontruncating variants in Clinvar database.The total variants, (likely) pathogenic variants, and non-truncating (likely) pathogenic variants in our internal database are much more than the public Clinvar database, which has 3902 in total, 1312 (likely) pathogenic, and 163 nontruncating variants.Among the 321 nontruncating (likely) pathogenic variants, 33% of them are classified based on the combined information of the internal database and literature and 8% of them are novel, which are classified only based on our internal database.Our criteria are consistent with clinical diagnosis.Conclusion: With the help of increasing data in our internal database due to high sample volume, more nontruncating pathogenic/likely pathogenic variants in the PKD1 gene have been identified, which significantly increases the diagnostic rate.The diagnosis of ADPKD is very important for patients who can benefit from the corresponding treatment.Genetic information is also important for the patients' families, who can benefit from prognostic information, and require closer clinical monitoring and management.

Authors

Institutions

Publication Details

Journal
Genetics in Medicine Open
Published
2025-01-01
DOI
https://doi.org/10.1016/j.gimo.2025.103035
Primary Topic
Genomics and Rare Diseases
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

P666: Classification of nontruncating variants in the PKD1 gene based on the large internal database

Sumit Punj, Zhenbin Chen, Harry Gao, Huijie Liu et al.
Genetics in Medicine Open
Genomics and Rare Diseases
article

P666: Classification of nontruncating variants in the PKD1 gene based on the large internal database

Sumit Punj, Zhenbin Chen, Harry Gao, Huijie Liu, Emily Sippola
article en

Abstract

Introduction: Autosomal dominant polycystic kidney disease (ADPKD) is generally a late-onset multisystem disorder characterized by bilateral kidney cysts, liver cysts, and an increased risk of intracranial aneurysms.The diagnosis of ADPKD is established through clinical manifestations and genetic testing.Studies indicate that around 78% of ADPKD resulted from (likely) pathogenic variants in the PKD1 gene.However, compared to the truncating variants, evaluating the nontruncating PKD1 variants is still challenging, due to the shortage of consensus criteria and published case reports.Here we demonstrate the combination of internal databases and literature to evaluate the classification of the nontruncating variants in the PKD1 gene.Methods: Patient samples were tested in our laboratory using Next-generation sequencing (NGS) panels, including 385 gene Renasight test, 727 gene Renomatome panel, 78 gene Expanded Polycystic Kidney Disease (with Nephronophthisis) panel, 6 gene Polycystic Kidney Disease panel, and PKD1 single gene panel.We propose the following criteria: for any nontruncating PKD1 variants with an allele frequency less than 8 in gnomADv4.1,a deep literature search will be performed.If the variants are present in our database more than 3 times, clinical information on all the cases will be requested.PS4_supporting is applied for one individual with PKD1 related condition; PS4_moderate is applied for two unrelated individuals with PKD1 related condition; PS4_strong is applied for more than three unrelated individuals with PKD1 related condition.The nontruncating variants will be classified as (likely) pathogenic if multiple individuals with the clinical features match the PKD1 related conditions.If the variants were classified as VUS due to insufficient evidence previously, an updated report will be sent to the ordering physician with the new classification.Results: All the NGS panels are processed according to lab procedures.Up to now, over 122,000 cases of renal diseases are reported in our laboratory.The diagnostic rate is around 27%. Currently, around 2107 out of 8423 PKD1 variants in our database are classified (likely) pathogenic.15% (321 variants) of the (likely) pathogenic variants are nontruncating variants (missense and small INDEL), which is twice the (likely) pathogenic nontruncating variants in Clinvar database.The total variants, (likely) pathogenic variants, and non-truncating (likely) pathogenic variants in our internal database are much more than the public Clinvar database, which has 3902 in total, 1312 (likely) pathogenic, and 163 nontruncating variants.Among the 321 nontruncating (likely) pathogenic variants, 33% of them are classified based on the combined information of the internal database and literature and 8% of them are novel, which are classified only based on our internal database.Our criteria are consistent with clinical diagnosis.Conclusion: With the help of increasing data in our internal database due to high sample volume, more nontruncating pathogenic/likely pathogenic variants in the PKD1 gene have been identified, which significantly increases the diagnostic rate.The diagnosis of ADPKD is very important for patients who can benefit from the corresponding treatment.Genetic information is also important for the patients' families, who can benefit from prognostic information, and require closer clinical monitoring and management.

Genetics in Medicine OpenVol. 3
Natera (United States) (US)
Zero hunger
Openalex Percentile: Top 94%
Genomics and Rare Diseases
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.