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RecruitingNCT06025240HLA-ABUpdated Aug 30, 2024

Expanding the Scope of Post-transplant HLA-specific Antibody Detection and Monitoring in Renal Transplant Recipients

An observational study in Kidney Transplant, Renal Transplant Failure and Kidney Transplant Rejection, sponsored by Liverpool University Hospitals NHS Foundation Trust. Recruiting at 1 site in United Kingdom. Open to participants aged 18 Years and older. Per ClinicalTrials.gov, last updated 2024-08-30.

Sponsored by Liverpool University Hospitals NHS Foundation Trust · Observational

From the registry’s dates

  • Primary completion was expected by Oct 2025, 11 months ago, but the record still lists the study as recruiting.
  • Started Oct 2023; still recruiting 2 years 11 months later.
Study type
Observational
Model
Cohort
Time perspective
Other
Enrollment
282
Ages
18 Years and older
Sex
All
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Study summary

The purpose of this study is to assess a new test to detect antibodies which may form following kidney transplant. These antibodies can be difficult to detect as they do not cause any symptoms but can lead to kidney damage. A new blood test will be performed alongside existing antibody tests to see how well the test functions in comparison and to see how well it is able to distinguish between inflammation caused by antibodies and other sorts of inflammation such as a urinary tract infection. The investigators also want to determine whether it is predictable whom will develop antibodies after a transplant and use these results to change the current way patients are monitored for antibodies after receiving a transplant. In addition to this, the investigators want to establish if patients over 60 years of age are relatively protected against immunological events such as rejection compared to patients who are under 60 years of age. The results could potentially lead to using a different immunosuppression regime based on which population age group patients belong to and lowering the risks associated with these drugs.

Read the detailed description

Donor-derived cell-free DNA (dd-cfDNA)

Post-transplant monitoring for acute rejection in most centres, focuses on identification of a deterioration in graft function which may be totally asymptomatic. The current best practice to investigate a suspected rejection are renal graft biopsy with appropriate staining for complement component C4d and a serum single antigen bead (SAB) testing. This reactive approach to assessing and monitoring rejection, mainly driven by serial assessments of renal function to determine response to treatment, avoids the need for multiple invasive diagnostic tests such as biopsies, but it poses the risk of missing the early detection and treatment of rejection prior to an objective decline in function. A "creeping creatinine", where there are small but sustained increases in creatinine at sequential visits is relatively common and by the time a deterioration consistent with rejection is observed there can already have been significant tissue damage.

Donor-derived cell-free DNA (dd-cfDNA) has been described as a useful biomarker for graft injury secondary to rejection which can be evident in blood weeks to months prior to histological evidence of graft injury. dd-cfDNA levels are high in the immediate post-operative phase, although there is a sharp drop off to low baseline levels after a few days to two weeks making it a useful biomarker in all but the earliest rejection episode. Levels are much higher in antibody mediated rejection (ABMR) when compared to cellular rejection offering improvements in sensitivity when considering ABMR alone (85%) versus rejection of all aetiology (59%). The investigators believe it is important to correlate the findings of the dd-cfDNA sample with the other tests described, so that observations about the percentage dd-cfDNA found in different pathologies and the overall frequency of positive results can be made.

Immunological Factors in Older Age Renal Transplant and Longitudinal Donor Specific Antibodies (DSA) study

Older patients who undergo kidney transplant (KT) have better survival than those who remain on the waiting list. Nevertheless, outcomes are inferior to younger recipients and KT is often felt to be a predominantly quality of life intervention for older patients. Frailty may have a beneficial influence on the risk of post-transplant adverse immunological events and rejection episodes. If transplanted with good quality organs (all barring elderly deceased after circulatory death - DCD grafts), older kidney transplant recipients will have fewer rejection episodes than younger counterparts. The investigators conducted a retrospective cohort study of the outcomes for older age transplant recipients (>60) locally, to compare results before and after the change in allocation system which coincides with the COVID-19 pandemic. In this study, the investigators observed less favourable HLA-mismatching, a higher rate of re-intervention (operative or interventional radiology), higher rates of tertiary centre readmissions and higher 1-year mortality rates.

The previous post-transplant HLA-specific antibody work examined only the first positive sample post-transplant independent of pre-transplant sensitisation status. The investigators, thus, propose prospectively recruiting patients, irrespective of age, undergoing transplant to determine the overall frequency of immunological events and de novo HLA specific antibody formation. Given the importance of early detection and intervention of antibody mediated processes and optimising treatment protocols for frail patients, the investigators aim to expand the research interest in post-transplant antibody monitoring. The investigators, thus, propose prospectively recruiting patients, irrespective of age, undergoing transplant to determine the overall frequency of immunological events and de novo HLA specific antibody formation. Data on clinical outcomes will be collected and the investigators would look to compare the \<60s with those 60 or older patients undergoing kidney transplant.

Determining Predictive Models for Post-transplant HLA-specific Antibody Formation

As an adjunct to the proposed study looking at the influence of age on immunological events, the investigators aim to examine the cohort as a whole to determine the differential clinical outcomes for patients with and without de novo HLA-specific antibody over time. An important part of this arm of the study will be to determine predictive models using machine learning methodology to determine those most at risk for the development of de-novo HLA specific antibody post-transplant.

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Conditions studied

  • Kidney Transplant
  • Renal Transplant Failure
  • Kidney Transplant Rejection
  • Frailty
  • Kidney Transplant; Complications
  • Transplant Dysfunction
  • Diagnosis
  • Renal Transplant

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Keywords

  • kidney transplant
  • novel biomarkers
  • post-transplant antibodies
  • HLA-specific antibodies
  • donor specific antibodies
  • transplant in older age
  • machine learning
  • predictive models
  • rejection
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In context

Frailty

1,199 studies on the registry are indexed under Frailty; 430 are open to participants now.

This study's planned enrollment of 282 is above the median of 223 across 496 observational studies indexed under Frailty.

Browse Frailty studies →

Lead sponsor

Liverpool University Hospitals NHS Foundation Trust is the lead sponsor of 60 studies on the registry; 13 are open to participants now.

Counted across the registry records on this site, refreshed daily.

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Who can participate

Ages eligible
18 Years and older
Sexes eligible
All
Accepts healthy volunteers
No
Sampling method
Non-probability sample

Study population

  1. cf-DNA arm: Patients who have undergone a "high risk" renal transplant in our unit within the last 6-12 months will be retrospectively recruited to the study.
  2. Older Age Immunological Events: Post-transplant patients prospectively recruited, irrespective of age, undergoing transplant to determine the overall frequency of immunological events and de novo HLA specific antibody formation. We will collect data on clinical outcomes and would look to compare the \<60s with those 60 or older looking for a difference in immunological events beteween the 2 groups.
  3. Predictive models: A subset of the cohort of recruits to the immunological factors in older age study will be used to determine machine learning algorithms of predictive factors for the development of de novo donor specific antibody.

Inclusion criteria

  1. cf-DNA arm:

    • Adult patients transplanted within 6-12 months (retrospective recruitment)
    • Patients admitted for renal transplant or within the first 6 months following transplant (prospective recruitment)
    • Patients must have capacity to provide informed consent
    • Patients must have received a high-risk transplant defined as level 4 mismatch, cRF >20, second or subsequent transplant, ABO or HLA incompatible
  2. Older Age Immunological Events:

    • Any adult patient with capacity undergoing, or within 72 hours of, a renal transplant
  3. Predictive models:

    • Any adult patient with capacity undergoing, or within 72 hours of, a renal transplant
    • Unsensitized pre-transplant

Exclusion criteria

Exclusion Criteria:

  1. cf-DNA arm:

    • Transplanted for longer than 12 months;
    • Low risk transplants;
    • Patients lacking capacity;
  2. Older Age Immunological Events:

    • Patients lacking capacity
    • Patients transplanted longer than 2 weeks
  3. Predictive models:

    • Sensitised patients
    • Patients lacking capacity
    • Patients transplanted longer than 2 weeks
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Study design

Observational model
Cohort
Time perspective
Other
Enrollment
282 participants (estimated)
Patient registry
No
Biospecimen retention
Samples with dna

Groups and cohorts

  • cf-DNA arm

    Participants will be recruited on the basis of having received a renal transplant within the last 6-12 months which has been deemed high risk. They will be identified from a database currently held within the renal transplant unit by members of the direct care team. They will be approached at a routine outpatient appointment for inclusion into the study and testing can be performed at their time of routine post-transplant testing where they will undergo blood (dd-cf DNA NGS assay), standard of care tests: blood count, renal profile, donor specific antibodies (DSA) sample, BK virus PCR, CMV PCR, urine testing and an ultrasound of the graft.

    Diagnostic Test: cf-DNA

  • Immunological Events following renal transplant in older age

    The renal transplant population will be divided on the basis of age into two cohort: ≥60 and \<60. All renal transplant patients are regularly followed up in the outpatient clinic where blood and urine tests are collected, and clinical evaluations are performed. It is not foreseen that this study will necessitate any additional hospital visits or testing above and beyond the usual standard of care. Serum samples are taken at the time intervals indicated for routine storage and we will simply use those samples for HLA testing (either screening alone or screening and single antigen bead testing if screening yields a positive result).

    Diagnostic Test: Immunological Events following renal transplant in older age

  • Determining Predictive Models for Post-transplant HLA-specific Antibody Formation

    A subset of the cohort of recruits to the immunological factors in older age study will be used to determine machine learning algorithms of predictive factors for the development of de novo donor specific antibody. Only patients who were unsensitised prior to the kidney transplant will be included into the study because prior sensitisation makes determining de novo specificities much harder. The follow up period will be set at 1 year to synchronise with the older age study.

    Other: Determining Predictive Models for Post-transplant HLA-specific Antibody Formation

Interventions

  • Diagnostic testcf-DNA

    In addition to the standard of care tests, participants will have an additional blood sample (dd-cf DNA). A cohort study patients who have undergone high immunological risk kidney transplant at our centre defined as a re-transplant, where the cRF is \>20% or where there is a level 4 HLA-mismatch. We will take a single plasma sample for dd-cfDNA testing at 6-12 months post-transplant and pair this with an assessment of renal function (creatinine, eGFR), MSU, BK and CMV PCR, single antigen bead (SAB) monitoring of HLA-specific antibodies and allograft USS.

    Also known as: donor derived cell-free DNA (dd-cf DNA)

  • Diagnostic testImmunological Events following renal transplant in older age

    Determine the overall frequency of immunological events and de novo HLA specific antibody formation in the \<60 and \>60 age population. Standard of care test taken at the different time intervals for routine storage. We will use those samples for HLA testing (either screening alone or screening and single antigen bead testing if screening yields a positive result).

    Also known as: Longitudinal DSA monitoring

  • OtherDetermining Predictive Models for Post-transplant HLA-specific Antibody Formation

    A machine learning model will be developed in Python using a range of pre- and post-transplant variables to determine a predictive model for de novo HLA-specific antibody following renal transplant.

    Also known as: Machine learning algorithms

06

What researchers measure

Primary outcomes

  1. dd-cf DNA

    Occurrence of a positive cell free DNA test in high-risk post-transplant patients at 6-12 months

    Time frame: 6-12 months post-transplant

  2. Immunological events in older age

    Frequency of the development of immunological events in the over 60s versus \<60 cohorts

    Time frame: through study completion, an average of 1 year

  3. Longitudinal DSA monitoring

    Frequency of development of de novo HLA specific antibody in the 1st year following transplantation in patients previously unsensitised.

    Time frame: through study completion, an average of 1 year

Secondary outcomes

  1. Occurrence of UTIs, viral reactivation and structural transplant abnormalities in high-risk post-transplant patients at 6-12 months

    as above

    Time frame: 6-12 months

  2. Association of cell free DNA result and any identified pathology (DSA, UTI, viral infection)

    as above

    Time frame: through study completion, an average of 1 year

  3. Comparison of graft and patient survival to 12 months in the over 60s and <60

    as above

    Time frame: through study completion, an average of 1 year

  4. Comparison of renal function, viral reactivation, readmission and reoperation rates between the 2 age groups (over 60s and <60)

    as above

    Time frame: through study completion, an average of 1 year

  5. Comparison of post-transplant complications (utilising the Clavien-Dindo classification of surgical complications) between patients developing de novo HLA specific antibody and those who do not, using machine learning models

    as above

    Time frame: through study completion, an average of 1 year

  6. Comparison of post-transplant graft and patient survival between patients developing de novo HLA specific antibody and those who do not, using machine learning models

    as above

    Time frame: through study completion, an average of 1 year

07

Study locations

1 of 1 sites recruiting
  • Liverpool University Hospitals NHS Foundation Trust
    Liverpool, Merseyside L7 8YE, United Kingdom
    Recruiting
08

References and documents

Individual participant data

Plan to share: Undecided

No publications or documents are linked to this record.

09

Updates

Tracking since Sep 25, 2026
No changes since tracking began. The registry record was last updated on Aug 30, 2024, before this site started recording changes on Sep 25, 2026. Its history is on ClinicalTrials.gov ↗
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Registry details

Key details

Study ID
NCT06025240
Lead sponsor
Liverpool University Hospitals NHS Foundation Trust
Collaborators
Kidney Research United Kingdom
Responsible party
Sponsor
First posted
Sep 6, 2023
Start date
Oct 13, 2023
Primary completion
Oct 13, 2025 (estimated)
Completion
Oct 13, 2026 (estimated)
Last update
Aug 30, 2024

Study contacts

George E Nita, MBChB MSc MRCSEd
Contact
george.nita@liverpoolft.nhs.uk
01517062000
Petra M Goldsmith, MBBChir PhD FRCS
Contact
petra.goldsmith@liverpoolft.nhs.uk
01517055550
Petra M Goldsmith, MBBChir PhD FRCS
study director · Liverpool University Hospitals NHS Foundation Trust
George E Nita, MBChB MSc MRCSEd
principal investigator · Liverpool University Hospitals NHS Foundation Trust

Oversight

Data monitoring committee
No
FDA-regulated drug
No
FDA-regulated device
No
View the source record on ClinicalTrials.gov ↗

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