Comparison of methods for donor-derived cell-free DNA quantification in plasma and urine from solid organ transplant recipients
In allograft monitoring of solid organ transplant recipients, liquid biopsy has emerged as a novel approach using quantification of donor-derived cell-free DNA (dd-cfDNA) in plasma. Despite early clinical implementation and analytical validation of techniques, direct comparisons of dd-cfDNA quantifi...
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Published in | Frontiers in genetics Vol. 14; p. 1089830 |
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Main Authors | , , , , , , , |
Format | Journal Article |
Language | English |
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Switzerland
Frontiers Media S.A
27.01.2023
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ISSN | 1664-8021 1664-8021 |
DOI | 10.3389/fgene.2023.1089830 |
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Abstract | In allograft monitoring of solid organ transplant recipients, liquid biopsy has emerged as a novel approach using quantification of donor-derived cell-free DNA (dd-cfDNA) in plasma. Despite early clinical implementation and analytical validation of techniques, direct comparisons of dd-cfDNA quantification methods are lacking. Furthermore, data on dd-cfDNA in urine is scarce and high-throughput sequencing-based methods so far have not leveraged unique molecular identifiers (UMIs) for absolute dd-cfDNA quantification. Different dd-cfDNA quantification approaches were compared in urine and plasma of kidney and liver recipients: A) Droplet digital PCR (ddPCR) using allele-specific detection of seven common
HLA-DRB1
alleles and the Y chromosome; B) high-throughput sequencing (HTS) using a custom QIAseq DNA panel targeting 121 common polymorphisms; and C) a commercial dd-cfDNA quantification method (AlloSeq
®
cfDNA, CareDx). Dd-cfDNA was quantified as %dd-cfDNA, and for ddPCR and HTS using UMIs additionally as donor copies. In addition, relative and absolute dd-cfDNA levels in urine and plasma were compared in clinically stable recipients. The HTS method presented here showed a strong correlation of the %dd-cfDNA with ddPCR (
R
2
= 0.98) and AlloSeq
®
cfDNA (
R
2
= 0.99) displaying only minimal to no proportional bias. Absolute dd-cfDNA copies also correlated strongly (
τ
= 0.78) between HTS with UMI and ddPCR albeit with substantial proportional bias (slope: 0.25; 95%-CI: 0.19–0.26). Among 30 stable kidney transplant recipients, the median %dd-cfDNA in urine was 39.5% (interquartile range, IQR: 21.8–58.5%) with 36.6 copies/μmol urinary creatinine (IQR: 18.4–109) and 0.19% (IQR: 0.01–0.43%) with 5.0 copies/ml (IQR: 1.8–12.9) in plasma without any correlation between body fluids. The median %dd-cfDNA in plasma from eight stable liver recipients was 2.2% (IQR: 0.72–4.1%) with 120 copies/ml (IQR: 85.0–138) while the median dd-cfDNA copies/ml was below 0.1 in urine. This first head-to-head comparison of methods for absolute and relative quantification of dd-cfDNA in urine and plasma supports a method-independent %dd-cfDNA cutoff and indicates the suitability of the presented HTS method for absolute dd-cfDNA quantification using UMIs. To evaluate the utility of dd-cfDNA in urine for allograft surveillance, absolute levels instead of relative amounts will most likely be required given the extensive variability of %dd-cfDNA in stable kidney recipients. |
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AbstractList | In allograft monitoring of solid organ transplant recipients, liquid biopsy has emerged as a novel approach using quantification of donor-derived cell-free DNA (dd-cfDNA) in plasma. Despite early clinical implementation and analytical validation of techniques, direct comparisons of dd-cfDNA quantification methods are lacking. Furthermore, data on dd-cfDNA in urine is scarce and high-throughput sequencing-based methods so far have not leveraged unique molecular identifiers (UMIs) for absolute dd-cfDNA quantification. Different dd-cfDNA quantification approaches were compared in urine and plasma of kidney and liver recipients: A) Droplet digital PCR (ddPCR) using allele-specific detection of seven common
HLA-DRB1
alleles and the Y chromosome; B) high-throughput sequencing (HTS) using a custom QIAseq DNA panel targeting 121 common polymorphisms; and C) a commercial dd-cfDNA quantification method (AlloSeq
®
cfDNA, CareDx). Dd-cfDNA was quantified as %dd-cfDNA, and for ddPCR and HTS using UMIs additionally as donor copies. In addition, relative and absolute dd-cfDNA levels in urine and plasma were compared in clinically stable recipients. The HTS method presented here showed a strong correlation of the %dd-cfDNA with ddPCR (
R
2
= 0.98) and AlloSeq
®
cfDNA (
R
2
= 0.99) displaying only minimal to no proportional bias. Absolute dd-cfDNA copies also correlated strongly (
τ
= 0.78) between HTS with UMI and ddPCR albeit with substantial proportional bias (slope: 0.25; 95%-CI: 0.19–0.26). Among 30 stable kidney transplant recipients, the median %dd-cfDNA in urine was 39.5% (interquartile range, IQR: 21.8–58.5%) with 36.6 copies/μmol urinary creatinine (IQR: 18.4–109) and 0.19% (IQR: 0.01–0.43%) with 5.0 copies/ml (IQR: 1.8–12.9) in plasma without any correlation between body fluids. The median %dd-cfDNA in plasma from eight stable liver recipients was 2.2% (IQR: 0.72–4.1%) with 120 copies/ml (IQR: 85.0–138) while the median dd-cfDNA copies/ml was below 0.1 in urine. This first head-to-head comparison of methods for absolute and relative quantification of dd-cfDNA in urine and plasma supports a method-independent %dd-cfDNA cutoff and indicates the suitability of the presented HTS method for absolute dd-cfDNA quantification using UMIs. To evaluate the utility of dd-cfDNA in urine for allograft surveillance, absolute levels instead of relative amounts will most likely be required given the extensive variability of %dd-cfDNA in stable kidney recipients. In allograft monitoring of solid organ transplant recipients, liquid biopsy has emerged as a novel approach using quantification of donor-derived cell-free DNA (dd-cfDNA) in plasma. Despite early clinical implementation and analytical validation of techniques, direct comparisons of dd-cfDNA quantification methods are lacking. Furthermore, data on dd-cfDNA in urine is scarce and high-throughput sequencing-based methods so far have not leveraged unique molecular identifiers (UMIs) for absolute dd-cfDNA quantification. Different dd-cfDNA quantification approaches were compared in urine and plasma of kidney and liver recipients: A) Droplet digital PCR (ddPCR) using allele-specific detection of seven common alleles and the Y chromosome; B) high-throughput sequencing (HTS) using a custom QIAseq DNA panel targeting 121 common polymorphisms; and C) a commercial dd-cfDNA quantification method (AlloSeq cfDNA, CareDx). Dd-cfDNA was quantified as %dd-cfDNA, and for ddPCR and HTS using UMIs additionally as donor copies. In addition, relative and absolute dd-cfDNA levels in urine and plasma were compared in clinically stable recipients. The HTS method presented here showed a strong correlation of the %dd-cfDNA with ddPCR ( = 0.98) and AlloSeq cfDNA ( = 0.99) displaying only minimal to no proportional bias. Absolute dd-cfDNA copies also correlated strongly ( = 0.78) between HTS with UMI and ddPCR albeit with substantial proportional bias (slope: 0.25; 95%-CI: 0.19-0.26). Among 30 stable kidney transplant recipients, the median %dd-cfDNA in urine was 39.5% (interquartile range, IQR: 21.8-58.5%) with 36.6 copies/μmol urinary creatinine (IQR: 18.4-109) and 0.19% (IQR: 0.01-0.43%) with 5.0 copies/ml (IQR: 1.8-12.9) in plasma without any correlation between body fluids. The median %dd-cfDNA in plasma from eight stable liver recipients was 2.2% (IQR: 0.72-4.1%) with 120 copies/ml (IQR: 85.0-138) while the median dd-cfDNA copies/ml was below 0.1 in urine. This first head-to-head comparison of methods for absolute and relative quantification of dd-cfDNA in urine and plasma supports a method-independent %dd-cfDNA cutoff and indicates the suitability of the presented HTS method for absolute dd-cfDNA quantification using UMIs. To evaluate the utility of dd-cfDNA in urine for allograft surveillance, absolute levels instead of relative amounts will most likely be required given the extensive variability of %dd-cfDNA in stable kidney recipients. In allograft monitoring of solid organ transplant recipients, liquid biopsy has emerged as a novel approach using quantification of donor-derived cell-free DNA (dd-cfDNA) in plasma. Despite early clinical implementation and analytical validation of techniques, direct comparisons of dd-cfDNA quantification methods are lacking. Furthermore, data on dd-cfDNA in urine is scarce and high-throughput sequencing-based methods so far have not leveraged unique molecular identifiers (UMIs) for absolute dd-cfDNA quantification. Different dd-cfDNA quantification approaches were compared in urine and plasma of kidney and liver recipients: A) Droplet digital PCR (ddPCR) using allele-specific detection of seven common HLA-DRB1 alleles and the Y chromosome; B) high-throughput sequencing (HTS) using a custom QIAseq DNA panel targeting 121 common polymorphisms; and C) a commercial dd-cfDNA quantification method (AlloSeq® cfDNA, CareDx). Dd-cfDNA was quantified as %dd-cfDNA, and for ddPCR and HTS using UMIs additionally as donor copies. In addition, relative and absolute dd-cfDNA levels in urine and plasma were compared in clinically stable recipients. The HTS method presented here showed a strong correlation of the %dd-cfDNA with ddPCR (R2 = 0.98) and AlloSeq® cfDNA (R2 = 0.99) displaying only minimal to no proportional bias. Absolute dd-cfDNA copies also correlated strongly (τ = 0.78) between HTS with UMI and ddPCR albeit with substantial proportional bias (slope: 0.25; 95%-CI: 0.19–0.26). Among 30 stable kidney transplant recipients, the median %dd-cfDNA in urine was 39.5% (interquartile range, IQR: 21.8–58.5%) with 36.6 copies/μmol urinary creatinine (IQR: 18.4–109) and 0.19% (IQR: 0.01–0.43%) with 5.0 copies/ml (IQR: 1.8–12.9) in plasma without any correlation between body fluids. The median %dd-cfDNA in plasma from eight stable liver recipients was 2.2% (IQR: 0.72–4.1%) with 120 copies/ml (IQR: 85.0–138) while the median dd-cfDNA copies/ml was below 0.1 in urine. This first head-to-head comparison of methods for absolute and relative quantification of dd-cfDNA in urine and plasma supports a method-independent %dd-cfDNA cutoff and indicates the suitability of the presented HTS method for absolute dd-cfDNA quantification using UMIs. To evaluate the utility of dd-cfDNA in urine for allograft surveillance, absolute levels instead of relative amounts will most likely be required given the extensive variability of %dd-cfDNA in stable kidney recipients. In allograft monitoring of solid organ transplant recipients, liquid biopsy has emerged as a novel approach using quantification of donor-derived cell-free DNA (dd-cfDNA) in plasma. Despite early clinical implementation and analytical validation of techniques, direct comparisons of dd-cfDNA quantification methods are lacking. Furthermore, data on dd-cfDNA in urine is scarce and high-throughput sequencing-based methods so far have not leveraged unique molecular identifiers (UMIs) for absolute dd-cfDNA quantification. Different dd-cfDNA quantification approaches were compared in urine and plasma of kidney and liver recipients: A) Droplet digital PCR (ddPCR) using allele-specific detection of seven common HLA-DRB1 alleles and the Y chromosome; B) high-throughput sequencing (HTS) using a custom QIAseq DNA panel targeting 121 common polymorphisms; and C) a commercial dd-cfDNA quantification method (AlloSeq® cfDNA, CareDx). Dd-cfDNA was quantified as %dd-cfDNA, and for ddPCR and HTS using UMIs additionally as donor copies. In addition, relative and absolute dd-cfDNA levels in urine and plasma were compared in clinically stable recipients. The HTS method presented here showed a strong correlation of the %dd-cfDNA with ddPCR (R 2 = 0.98) and AlloSeq® cfDNA (R 2 = 0.99) displaying only minimal to no proportional bias. Absolute dd-cfDNA copies also correlated strongly (τ = 0.78) between HTS with UMI and ddPCR albeit with substantial proportional bias (slope: 0.25; 95%-CI: 0.19-0.26). Among 30 stable kidney transplant recipients, the median %dd-cfDNA in urine was 39.5% (interquartile range, IQR: 21.8-58.5%) with 36.6 copies/μmol urinary creatinine (IQR: 18.4-109) and 0.19% (IQR: 0.01-0.43%) with 5.0 copies/ml (IQR: 1.8-12.9) in plasma without any correlation between body fluids. The median %dd-cfDNA in plasma from eight stable liver recipients was 2.2% (IQR: 0.72-4.1%) with 120 copies/ml (IQR: 85.0-138) while the median dd-cfDNA copies/ml was below 0.1 in urine. This first head-to-head comparison of methods for absolute and relative quantification of dd-cfDNA in urine and plasma supports a method-independent %dd-cfDNA cutoff and indicates the suitability of the presented HTS method for absolute dd-cfDNA quantification using UMIs. To evaluate the utility of dd-cfDNA in urine for allograft surveillance, absolute levels instead of relative amounts will most likely be required given the extensive variability of %dd-cfDNA in stable kidney recipients.In allograft monitoring of solid organ transplant recipients, liquid biopsy has emerged as a novel approach using quantification of donor-derived cell-free DNA (dd-cfDNA) in plasma. Despite early clinical implementation and analytical validation of techniques, direct comparisons of dd-cfDNA quantification methods are lacking. Furthermore, data on dd-cfDNA in urine is scarce and high-throughput sequencing-based methods so far have not leveraged unique molecular identifiers (UMIs) for absolute dd-cfDNA quantification. Different dd-cfDNA quantification approaches were compared in urine and plasma of kidney and liver recipients: A) Droplet digital PCR (ddPCR) using allele-specific detection of seven common HLA-DRB1 alleles and the Y chromosome; B) high-throughput sequencing (HTS) using a custom QIAseq DNA panel targeting 121 common polymorphisms; and C) a commercial dd-cfDNA quantification method (AlloSeq® cfDNA, CareDx). Dd-cfDNA was quantified as %dd-cfDNA, and for ddPCR and HTS using UMIs additionally as donor copies. In addition, relative and absolute dd-cfDNA levels in urine and plasma were compared in clinically stable recipients. The HTS method presented here showed a strong correlation of the %dd-cfDNA with ddPCR (R 2 = 0.98) and AlloSeq® cfDNA (R 2 = 0.99) displaying only minimal to no proportional bias. Absolute dd-cfDNA copies also correlated strongly (τ = 0.78) between HTS with UMI and ddPCR albeit with substantial proportional bias (slope: 0.25; 95%-CI: 0.19-0.26). Among 30 stable kidney transplant recipients, the median %dd-cfDNA in urine was 39.5% (interquartile range, IQR: 21.8-58.5%) with 36.6 copies/μmol urinary creatinine (IQR: 18.4-109) and 0.19% (IQR: 0.01-0.43%) with 5.0 copies/ml (IQR: 1.8-12.9) in plasma without any correlation between body fluids. The median %dd-cfDNA in plasma from eight stable liver recipients was 2.2% (IQR: 0.72-4.1%) with 120 copies/ml (IQR: 85.0-138) while the median dd-cfDNA copies/ml was below 0.1 in urine. This first head-to-head comparison of methods for absolute and relative quantification of dd-cfDNA in urine and plasma supports a method-independent %dd-cfDNA cutoff and indicates the suitability of the presented HTS method for absolute dd-cfDNA quantification using UMIs. To evaluate the utility of dd-cfDNA in urine for allograft surveillance, absolute levels instead of relative amounts will most likely be required given the extensive variability of %dd-cfDNA in stable kidney recipients. |
Author | Banz, Vanessa Sandberg, Fanny Kueng, Nicholas Kuhn, Christian Sidler, Daniel Largiadèr, Carlo R. Amstutz, Ursula Arcioni, Séverine |
AuthorAffiliation | 5 Department of Visceral Surgery and Medicine , Inselspital , Bern University Hospital and University of Bern , Bern , Switzerland 1 Department of Clinical Chemistry , Inselspital , Bern University Hospital and University of Bern , Bern , Switzerland 4 Department of Nephrology and Hypertension , Inselspital , Bern University Hospital and University of Bern , Bern , Switzerland 2 Graduate School for Cellular and Biomedical Sciences , University of Bern , Bern , Switzerland 3 Division of Medical Genetics , Central Institute of Hospitals , Valais Hospital , Sion , Switzerland |
AuthorAffiliation_xml | – name: 4 Department of Nephrology and Hypertension , Inselspital , Bern University Hospital and University of Bern , Bern , Switzerland – name: 2 Graduate School for Cellular and Biomedical Sciences , University of Bern , Bern , Switzerland – name: 1 Department of Clinical Chemistry , Inselspital , Bern University Hospital and University of Bern , Bern , Switzerland – name: 5 Department of Visceral Surgery and Medicine , Inselspital , Bern University Hospital and University of Bern , Bern , Switzerland – name: 3 Division of Medical Genetics , Central Institute of Hospitals , Valais Hospital , Sion , Switzerland |
Author_xml | – sequence: 1 givenname: Nicholas surname: Kueng fullname: Kueng, Nicholas – sequence: 2 givenname: Séverine surname: Arcioni fullname: Arcioni, Séverine – sequence: 3 givenname: Fanny surname: Sandberg fullname: Sandberg, Fanny – sequence: 4 givenname: Christian surname: Kuhn fullname: Kuhn, Christian – sequence: 5 givenname: Vanessa surname: Banz fullname: Banz, Vanessa – sequence: 6 givenname: Carlo R. surname: Largiadèr fullname: Largiadèr, Carlo R. – sequence: 7 givenname: Daniel surname: Sidler fullname: Sidler, Daniel – sequence: 8 givenname: Ursula surname: Amstutz fullname: Amstutz, Ursula |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/36777723$$D View this record in MEDLINE/PubMed |
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ContentType | Journal Article |
Copyright | Copyright © 2023 Kueng, Arcioni, Sandberg, Kuhn, Banz, Largiadèr, Sidler and Amstutz. Copyright © 2023 Kueng, Arcioni, Sandberg, Kuhn, Banz, Largiadèr, Sidler and Amstutz. 2023 Kueng, Arcioni, Sandberg, Kuhn, Banz, Largiadèr, Sidler and Amstutz |
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Keywords | ddPCR urine dd-cfDNA cell-free DNA kidney transplant biomarker liver transplant high-throughput sequencing |
Language | English |
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Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Edited by: Vanessa Meyer, University of the Witwatersrand, South Africa Reviewed by: Jeff Reeve, University of Alberta, Canada This article was submitted to Human and Medical Genomics, a section of the journal Frontiers in Genetics Justin Rosenheck, Ohio State University Hospital, United States |
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Title | Comparison of methods for donor-derived cell-free DNA quantification in plasma and urine from solid organ transplant recipients |
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