Adapting Clinical Chemistry Plasma as a Source for Liquid Biopsies
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eLife Assessment
This important work provides a new method to extract cfDNA from residual plasma from heparin separators for molecular testing. The evidence supporting the authors' claims is convincing, although some further metrics should also be evaluated. This finding will be interesting to people working in epigenomics and infectious disease diagnostics.
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Abstract
Background
Circulating cell-free DNA (cfDNA) has become a valuable analyte for molecular testing but requires specialized collection tubes or immediate processing. We investigated the feasibility of using residual plasma from heparin separators, which are routinely used in clinical chemistry, as an accessible and underutilized source for cfDNA testing.
Methods
We analyzed matched plasma samples collected in EDTA, Streck, and heparin separators in a Healthy Cohort (n = 5) and matched samples collected in EDTA and heparin separators from a Hospital Cohort derived from viral PCR-positive patients (n = 34). Whole-genome sequencing and genome-wide enriched methylation sequencing were performed to evaluate concordance across multiple benchmarks, including metagenomics, chromosomal copy number, methylome, and fragmentomics.
Results
In the Healthy Cohort, methylation patterns were correlated (Pearson’s r = 0.92–0.93) between tube types, and fragmentation features were preserved with a modal size peak at 166 bp and a consistent top 10 end motif ranking across tube types (n = 5). In the Hospital Cohort, heparin separators showed a strong concordance with matched EDTA tubes for viral detection (n = 34, Pearson’s r = 0.99), copy number alteration profiling (n = 6, Pearson’s r = 0.86-0.98), and methylation patterns (n = 12, r = 0.83-0.93).
Conclusions
Residual plasma from routine clinical chemistry tests can provide a vast, untapped resource for cfDNA analysis.
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eLife Assessment
This important work provides a new method to extract cfDNA from residual plasma from heparin separators for molecular testing. The evidence supporting the authors' claims is convincing, although some further metrics should also be evaluated. This finding will be interesting to people working in epigenomics and infectious disease diagnostics.
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Reviewer #1 (Public review):
Summary:
The manuscript "Adapting Clinical Chemistry Plasma as a Source for Liquid Biopsies" addresses a timely and practical question: whether residual plasma from heparin separator tubes can serve as a source of cfDNA for molecular profiling. This idea is attractive, since such samples are routinely generated in clinical chemistry labs and would represent a vast and accessible resource for liquid biopsy applications. The preliminary results are encouraging, but in its current form, the study feels incomplete and requires additional work.
My major concerns/suggestions are as follows:
(1) Context and literature
The introduction provides only limited background on prior attempts to use heparinized plasma for cfDNA work. It is well known that heparin can inhibit PCR and sequencing library preparation, which …
Reviewer #1 (Public review):
Summary:
The manuscript "Adapting Clinical Chemistry Plasma as a Source for Liquid Biopsies" addresses a timely and practical question: whether residual plasma from heparin separator tubes can serve as a source of cfDNA for molecular profiling. This idea is attractive, since such samples are routinely generated in clinical chemistry labs and would represent a vast and accessible resource for liquid biopsy applications. The preliminary results are encouraging, but in its current form, the study feels incomplete and requires additional work.
My major concerns/suggestions are as follows:
(1) Context and literature
The introduction provides only limited background on prior attempts to use heparinized plasma for cfDNA work. It is well known that heparin can inhibit PCR and sequencing library preparation, which has historically discouraged its use. The authors should summarize the relevant literature more comprehensively and explain clearly why this approach has not been widely adopted until now, and how their work differs from or overcomes these earlier challenges.
(2) Genome-wide coverage
The analyses focus on correlations in methylation patterns and fragmentation metrics, but there is no evaluation of sequencing coverage across the genome. For both WGS and WMS, it would be important to demonstrate whether cfDNA from heparin plasma provides unbiased coverage, or whether certain genomic regions are systematically under-represented. A comparison against coverage profiles from cell-derived DNA (e.g., PBMC genomic DNA) would help to put the results in context and assess whether the material is suitable for whole-genome applications.
(3) Viral detection sensitivity
The study shows strong concordance in viral detection between EDTA and heparin samples, but the sensitivity analysis is lacking. For clinical relevance, it is critical to demonstrate how well heparin-derived plasma performs in low viral load cases. A quantitative comparison of viral read counts and genome coverage across tube types would strengthen the conclusions.
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Reviewer #2 (Public review):
Summary:
The authors propose that leftover heparin plasma can serve as a source for cfDNA extraction, which could then be used for downstream genomic analyses such as methylation profiling, CNV detection, metagenomics, and fragmentomics. While the study is potentially of interest, several major limitations reduce its impact; for example, the study does not adequately address key methodological concerns, particularly cfDNA degradation, sequencing depth limitations, statistical rigor, and the breadth of relevant applications.
Strengths:
The paper provides a cheap method to extract cfDNA, which has broad application if the method is solid.
Weaknesses:
(1) The introduction lacks a sufficient review of prior work. The authors do not adequately summarize existing studies on cfDNA extraction, particularly those …
Reviewer #2 (Public review):
Summary:
The authors propose that leftover heparin plasma can serve as a source for cfDNA extraction, which could then be used for downstream genomic analyses such as methylation profiling, CNV detection, metagenomics, and fragmentomics. While the study is potentially of interest, several major limitations reduce its impact; for example, the study does not adequately address key methodological concerns, particularly cfDNA degradation, sequencing depth limitations, statistical rigor, and the breadth of relevant applications.
Strengths:
The paper provides a cheap method to extract cfDNA, which has broad application if the method is solid.
Weaknesses:
(1) The introduction lacks a sufficient review of prior work. The authors do not adequately summarize existing studies on cfDNA extraction, particularly those comparing heparin plasma and EDTA plasma. This omission weakens the rationale for their study and overlooks important context.
(2) The evaluation of cfDNA degradation from heparin plasma is incomplete. The authors did not compare cfDNA integrity with that extracted from EDTA plasma under realistic sample handling conditions. Their analysis (lines 90-93) focuses only on immediate extraction, which is not representative of clinical workflows where delays are common. This is in direct conflict with findings from Barra et al. (2025, LabMed), who showed that cfDNA from heparin plasma is substantially more degraded than that from EDTA plasma. A systematic comparison of cfDNA yields and fragment sizes under delayed extraction conditions would be necessary to validate the feasibility of their proposed approach.
(3) The comparison of methylation profiles suffers from the same limitation. The authors do not account for cfDNA degradation and the resulting reduced input material, which in turn affects sequencing depth and data quality. As shown by Barra et al., quantifying cfDNA yield and displaying these data in a figure would strengthen the analysis. Moreover, the statistical method applied is inappropriate: the authors use Pearson correlation when Spearman correlation would be more robust to outliers and thus more suitable for methylation and other genomic comparisons.
(4) The CNV analysis also raises concerns. With low-coverage WGS (~5X) from heparin-derived cfDNA, only large CNVs (>100 kb) are reliably detectable. The authors used a 500 kb bin size for CNV calling, but they did not acknowledge this as a limitation. Evaluating CNV detection at multiple bin sizes (e.g., 1 kb, 10 kb, 50 kb, 100 kb, 250 kb) would provide a more complete picture. In addition, Figure 3 presents CNV results from only one sample, which risks bias. Similar bias would exist for illustrations of CNVs from other samples in the supplementary figures provided by the authors. Again, Spearman correlation should be applied in Figure 3c, where clear outliers are visible.
(5) It is important to point out that depth-based CNV calling is just one of the CNV calling methods. Other CNV calling software using SNVs, pair-reads, split-reads, and coverage depth for calling CNV, such as the software Conserting, would be severely affected by the low-quality WGS data. The authors need to evaluate at least two different software with specific algorithms for CNV calling based on current WGS data.
(6) The authors omit an important application of cfDNA: somatic mutation detection. Degraded cfDNA and reduced sequencing depth could substantially impact SNV calling accuracy in terms of both recall and precision. Assessing this aspect with their current dataset would provide a more comprehensive evaluation of heparin plasma-derived cfDNA for genomic analyses.
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Author response:
Reviewer #1 (Public review):
Summary:
The manuscript "Adapting Clinical Chemistry Plasma as a Source for Liquid Biopsies" addresses a timely and practical question: whether residual plasma from heparin separator tubes can serve as a source of cfDNA for molecular profiling. This idea is attractive, since such samples are routinely generated in clinical chemistry labs and would represent a vast and accessible resource for liquid biopsy applications. The preliminary results are encouraging, but in its current form, the study feels incomplete and requires additional work.
We thank the reviewer for the encouragement and for recognizing the potential of clinical chemistry plasma as an accessible source for cfDNA-based analyses. We look forward to addressing the gaps described below.
My major concerns/suggestions are as …
Author response:
Reviewer #1 (Public review):
Summary:
The manuscript "Adapting Clinical Chemistry Plasma as a Source for Liquid Biopsies" addresses a timely and practical question: whether residual plasma from heparin separator tubes can serve as a source of cfDNA for molecular profiling. This idea is attractive, since such samples are routinely generated in clinical chemistry labs and would represent a vast and accessible resource for liquid biopsy applications. The preliminary results are encouraging, but in its current form, the study feels incomplete and requires additional work.
We thank the reviewer for the encouragement and for recognizing the potential of clinical chemistry plasma as an accessible source for cfDNA-based analyses. We look forward to addressing the gaps described below.
My major concerns/suggestions are as follows:
(1) Context and literature
The introduction provides only limited background on prior attempts to use heparinized plasma for cfDNA work. It is well known that heparin can inhibit PCR and sequencing library preparation, which has historically discouraged its use. The authors should summarize the relevant literature more comprehensively and explain clearly why this approach has not been widely adopted until now, and how their work differs from or overcomes these earlier challenges.
We thank the reviewer for their valuable comments and agree that the review of prior work needs to be more thorough, with the gaps clearly identified. In the revised manuscript, we will expand the introduction to include a more comprehensive summary of prior studies. Some of the material was in the Discussion, but we will move it to the introduction in the revision. In general, we will comment briefly here about the novelty of this work and the previous gap in the literature:
(1) Previous pre-analytical studies use DNA fluorometry and qPCR, which cannot distinguish between genomic DNA contamination (from cells) and cfDNA. In contrast, our study uses adapter-based NGS with DNA spike-ins, which can exclude genomic DNA contamination and enable precise quantification of cfDNA input and measurement of their lengths. In Figure 5b-c, we demonstrate that we were able to match our paired sample results only under the measurements of our NGS study, not in previous attempts. Note the current Fig. 5 captions b&c should be swapped and will be corrected in the revision.
(2) As the reviewer has astutely mentioned, heparin is a well-recognized inhibitor of PCR, and heparinized specimens are historically contraindicated for molecular testing. However, most modern cfDNA assays now use NGS, which includes multiple purification steps before PCR amplification, minimizing the impact of heparin interference.
(3) Previous clinical chemistry tests used serum tubes, which are known to generate background gDNA during clotting and are therefore unsuitable for cfDNA-based analyses. In recent years, modern hospital chemistry laboratories, especially those supporting emergency departments, have gradually transitioned to heparin separator tubes for faster turnaround. Hence, residual plasma from heparin separator tubes is a more recent option, one that was not widely available when key pre-analytical studies on cfDNA were performed.
(2) Genome-wide coverage
The analyses focus on correlations in methylation patterns and fragmentation metrics, but there is no evaluation of sequencing coverage across the genome. For both WGS and WMS, it would be important to demonstrate whether cfDNA from heparin plasma provides unbiased coverage, or whether certain genomic regions are systematically under-represented. A comparison against coverage profiles from cell-derived DNA (e.g., PBMC genomic DNA) would help to put the results in context and assess whether the material is suitable for whole-genome applications.
Thank you for the insightful comment. We agree that evaluating sequencing coverage across the genome is important for assessing the suitability of cfDNA from heparin separators. In response, we are performing additional, in-depth runs to compare genome-wide coverage profiles in the Hospital Cohort. The results of these analyses will be included in the revised version of the manuscript.
(3) Viral detection sensitivity
The study shows strong concordance in viral detection between EDTA and heparin samples, but the sensitivity analysis is lacking. For clinical relevance, it is critical to demonstrate how well heparin-derived plasma performs in low viral load cases. A quantitative comparison of viral read counts and genome coverage across tube types would strengthen the conclusions.
We agree that evaluating analytical sensitivity in cases with low viral loads is important for understanding clinical performance. To address this point, we plan to include additional paired cases with viral loads below 1,000 IU/mL and examine the correlation of viral read counts between EDTA and heparin separators in this subset.
Reviewer #2 (Public review):
Summary:
The authors propose that leftover heparin plasma can serve as a source for cfDNA extraction, which could then be used for downstream genomic analyses such as methylation profiling, CNV detection, metagenomics, and fragmentomics. While the study is potentially of interest, several major limitations reduce its impact; for example, the study does not adequately address key methodological concerns, particularly cfDNA degradation, sequencing depth limitations, statistical rigor, and the breadth of relevant applications.
We thank the reviewer for the insightful comments and will work to clarify and address the mentioned issues. We do not find the residual plasma from the heparin separator to be a replacement for gold standard methods. Instead, we take it as a practical and complementary resource that may help broaden the accessibility of samples. Comparable cfDNA metrics highlight its potential to serve as an additional source for biobanking and research applications.
Strengths:
The paper provides a cheap method to extract cfDNA, which has broad application if the method is solid.
We thank the reviewer for the encouraging comment. While cost-effectiveness is a practical advantage, we believe the greater strength of this approach lies in the accessibility of sampling. Residual plasma from routine clinical tests offers an opportunity to include patients or time points that would otherwise be difficult to capture, such as those with severe illness or those sampled before treatment.
Weaknesses:
(1) The introduction lacks a sufficient review of prior work. The authors do not adequately summarize existing studies on cfDNA extraction, particularly those comparing heparin plasma and EDTA plasma. This omission weakens the rationale for their study and overlooks important context.
We thank both reviewers for this comment. See above under Reviewer 1’s responses for our provisional perspective on the background literature and gap. We will expand the Introduction to provide a more comprehensive summary of prior studies.
(2) The evaluation of cfDNA degradation from heparin plasma is incomplete. The authors did not compare cfDNA integrity with that extracted from EDTA plasma under realistic sample handling conditions. Their analysis (lines 90-93) focuses only on immediate extraction, which is not representative of clinical workflows where delays are common. This is in direct conflict with findings from Barra et al. (2025, LabMed), who showed that cfDNA from heparin plasma is substantially more degraded than that from EDTA plasma. A systematic comparison of cfDNA yields and fragment sizes under delayed extraction conditions would be necessary to validate the feasibility of their proposed approach.
We appreciate this thoughtful comment, which highlights reasonable concerns about cfDNA degradation in heparin. We would like to clarify that the Hospital Cohort, which only used leftover plasma in the clinical lab, was designed to reflect real-world clinical workflows, where unavoidable delays before plasma processing are already incorporated. In the Healthy Cohort, a subset of samples is also processed after controlled delays, as shown in Supplementary Figure 2.
Regarding the differing results in Barra et al. (2025, LabMed), where heparin tubes showed 85% cfDNA degradation, it is important to note that samples were incubated at 37 °C for 24 hours. We anticipate that endogenous nuclease would be active under 37 °C and would cause cfDNA degradation. However, this condition differs markedly from the relevant clinical workflows we describe here. In the routine hospital settings, blood samples are typically kept at room temperature for up to 60 minutes during transport and waiting. The outpatient setting can be more variable, but samples here are supposed to be refrigerated during transportation. They are then processed in high-throughput, fully automated systems that comply with nationally standardized quality regulations in the United States (CLIA). The resultant plasma will be physically separated from cellular components because of the gel in the heparin separators. The processed tubes are subsequently transferred to refrigerated storage at 4 °C. Under these conditions, samples do not experience prolonged exposure to elevated temperatures such as 37 °C, and refrigeration usually occurs within two hours of collection. We will incorporate these details in the revised manuscript.
Also, as we mentioned in our reply to Reviewer 1, Barra et al. used qPCR like most cfDNA pre-analytical studies, but qPCR is not a perfect DNA quantification method for NGS-based downstream analyses because it measures both cfDNA and contaminating genomic DNA. The latter can be excluded by most NGS assays. By using constant spike-in internal controls, our approach directly quantifies the amount of sequenceable cfDNA, providing a more accurate estimate of input DNA (Figure 5c). In one possible future experiment, the same sample in the Healthy Cohort can be delayed by 1-2 hours prior to processing (centrifugation and refrigeration) and kept at room temperature rather than 4 °C to mimic real-world delays. Outputs would be cfDNA yields and fragment sizes, and we would use constant spike-ins to quantify the amount of sequenceable DNA.
(3) The comparison of methylation profiles suffers from the same limitation. The authors do not account for cfDNA degradation and the resulting reduced input material, which in turn affects sequencing depth and data quality. As shown by Barra et al., quantifying cfDNA yield and displaying these data in a figure would strengthen the analysis. Moreover, the statistical method applied is inappropriate: the authors use Pearson correlation when Spearman correlation would be more robust to outliers and thus more suitable for methylation and other genomic comparisons.
We appreciate the reasonable concerns regarding cfDNA degradation and agree that the methylation profile is not an adequate metric for degradation. To evaluate for degradation, we will focus on NGS-derived length profiles (WGS data) and constant spike-in DNA. We appreciate the reviewer’s suggestion to use the Spearman correlation, and this will be incorporated.
(4) The CNV analysis also raises concerns. With low-coverage WGS (~5X) from heparin-derived cfDNA, only large CNVs (>100 kb) are reliably detectable. The authors used a 500 kb bin size for CNV calling, but they did not acknowledge this as a limitation. Evaluating CNV detection at multiple bin sizes (e.g., 1 kb, 10 kb, 50 kb, 100 kb, 250 kb) would provide a more complete picture. In addition, Figure 3 presents CNV results from only one sample, which risks bias. Similar bias would exist for illustrations of CNVs from other samples in the supplementary figures provided by the authors. Again, Spearman correlation should be applied in Figure 3c, where clear outliers are visible.
We appreciate the reviewer’s constructive comments regarding the CNV analysis. We agree that the use of low-coverage WGS (~5×) limits the reliable detection of small CNVs, and we will acknowledge this as a limitation in the revised manuscript. To address this point, we will perform additional analyses using 50kb as bin sizes. To reduce potential bias from single-sample representation, we will show the aggregated CNV plots for all CNA-positive cases along with their log₂ copy ratio correlations, and Spearman’s correlation will be applied as suggested.
(5) It is important to point out that depth-based CNV calling is just one of the CNV calling methods. Other CNV calling software using SNVs, pair-reads, split-reads, and coverage depth for calling CNV, such as the software Conserting, would be severely affected by the low-quality WGS data. The authors need to evaluate at least two different software with specific algorithms for CNV calling based on current WGS data.
Thank you for this suggestion. We will evaluate CNV profiles using alternative informatics methods.
(6) The authors omit an important application of cfDNA: somatic mutation detection. Degraded cfDNA and reduced sequencing depth could substantially impact SNV calling accuracy in terms of both recall and precision. Assessing this aspect with their current dataset would provide a more comprehensive evaluation of heparin plasma-derived cfDNA for genomic analyses.
We thank the reviewer for emphasizing SNVs as an important application of cfDNA. We agree that the limited volume of residual plasma is a constraint. Routine chemistry tests leave ~1–2 mL of plasma, and this limited volume places an upper limit on performing SNV analysis. We will expand the discussion of this limitation in the paper. Our approach is not intended to replace specialized tubes for large-volume cfDNA collection but rather to complement them by enabling the use of residual material.
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