Abstract
Background and Objectives
Chronic kidney disease (CKD) is known to be associated with increased plasma phosphorylated tau217 (p-tau217) concentrations, potentially confounding the utility of plasma p-tau217 measurements as a marker of amyloid pathology in individuals with suspected Alzheimer disease (AD). In this study, we quantitatively investigate the relationship of plasma p-tau217 concentrations vs estimated glomerular filtration rate (eGFR) in individuals with CKD with and without amyloid pathology.
Methods
This was a retrospective examination of data from 2 observational cohorts from either the Mayo Clinic Study of Aging or the Alzheimer's Disease Research Center cohorts. p-Tau217 was determined using the ALZpath Simoa p-tau217 immunoassay and an immunoprecipitation mass spectrometry assay that simultaneously measures p-tau217 and nonphosphorylated-tau217 (np-tau217) to determine %p-tau217 ([p-tau217/nonphosphorylated-tau217]) × 100%) (C2N Diagnostics). Amyloid positivity was defined by amyloid-PET and a centiloid of ≥25. Log-log linear regression fits were used to quantitatively predict increases in plasma p-tau217 associated with decreasing eGFR.
Results
Participants (n = 202, mean age of 78 years, 38% female) with diagnoses of cognitive unimpairment (n = 109), mild cognitive impairment (n = 71), and dementia (n = 22) were included. In all, 114 (56%) of all participants were amyloid-PET positive (A+). In addition, 86 (43%) of all participants were classified as having CKD (CKD stages 3–4). p-Tau217 concentrations were significantly higher in A− participants with an eGFR of <60 (mL/min/1.73 m2), as compared with those with eGFR >60 A− participants. For an eGFR of 45 vs 60 in the A− cohort, the calculated percentage changes were +31%, +55%, and +19%, for ALZpath p-tau217, C2N p-tau217, and C2N %p-tau217, respectively. For the A+ cohort, the corresponding calculated percentage changes were +17%, +15%, and −5%, respectively.
Discussion
CKD was associated with increased p-tau217 concentrations when measuring p-tau217 by ALZpath and C2N methodologies, but the effect was mitigated by the use of %p-tau217. These results indicate limitations for the utility of plasma p-tau217 measurements in individuals with significant renal impairment (eGFR <45 or CKD stage 3b or greater). Determination of eGFR should be considered to avoid inaccurate classification of the presence of AD-related pathology by plasma p-tau217 in individuals with CKD.
Classification of Evidence
This study provides Class II evidence that in individuals with CKD stage 3 (especially stage 3b) or higher, p-tau217 concentrations are increased, with a greater increase in amyloid-PET–negative individuals.
Introduction
The recent Food and Drug Administration approval of amyloid-targeting therapies has fueled the interest of introducing Alzheimer disease (AD) blood-based biomarkers into clinical practice.1-3 The circulating concentration of phosphorylated-tau plasma protein at threonine 217 (p-tau217) have been shown to increase in the presence of AD-related amyloid pathology.4-6 Although the performance of these biomarkers in selected populations has been characterized in various studies, a better understanding of how biomarkers are affected by comorbidities present in real-world practice is imperative for the successful implementation of these biomarkers in routine laboratory medicine.7-9
Comorbidities such as diabetes mellitus (DM), chronic kidney disease (CKD), increased body mass index (BMI), history of stroke, and myocardial infarction (MI) have been reported to result in alteration of circulating p-tau217 concentrations.10,11 However, when adjusted for age and sex, DM was no longer associated with increases in p-tau217 concentration, whereas in stroke, MI and CKD p-tau217 increases remained significant.10,11 Data on the effect of CKD on AD blood-based biomarker concentrations are limited. Previous work has examined plasma AD biomarkers among cognitively normal adults of the population-based Mayo Clinic Study of Aging (MCSA) and demonstrated that a clinical history of CKD was strongly associated with increased plasma p-tau217 concentrations measured by immunoassay.11 Associations of CKD with plasma p-tau217 concentrations as measured by immunoprecipitation mass spectrometry (IPMS) were also investigated.12 Reduced estimated glomerular filtration rates (eGFR) were associated with increased plasma levels of both phosphorylated and nonphosphorylated 217 peptides. However, the use of a p-tau217/np-tau217 percent ratio (or %p-tau217) attenuated the relative increase that resulted from a decreased eGFR as compared with p-tau217 alone.12 Nonphosphorylated 217 peptides, which are not increased in the context of AD pathology, serve to normalize for the total amount of tau present in the sample.13 This normalization effect is believed to result in improved clinical performance of the %p-tau217.13
These findings highlight the need to consider CKD when implementing p-tau blood-based biomarkers in clinical practice. As eGFR is reduced, the rate of renal excretion of proteins such as cystatin C and creatinine is reduced, resulting in a nonlinear increase of circulating protein concentrations vs eGFR.14 However, it is unclear at which CKD stage the increase in plasma p-tau217 in different assays renders the interpretation of these biomarkers unreliable. CKD is a relatively common comorbidity in older individuals and is defined as stages 3–5.15 Population prevalence estimates of CKD stages using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) 2021 eGFR equation in individuals age 65+ years are 15.0% for stage 3 (eGFR of <60–30 mL/min/1.73 m2) and 1.5% for stages 4 and 5 (<30 eGFR of <60–30 mL/min/1.73 m2).15 CKD stage 3 is divided into 2 subcategories: stage 3a (eGFR of 45–59 mL/min/1.73 m2) and stage 3b (eGFR of 30–44 mL/min/1.73 m2), with prevalences for age 65+ years of 10.7% (stage 3a) and 4.3% (stage 3b), respectively.15 As p-tau clinical cutoffs for detecting the presence of AD pathology are further developed in different assays, the quantitative impact of potentially confounding CKD on p-tau measurement needs to be better understood for optimal clinical use. It should be noted that a lack of association between eGFR and brain-amyloid burden has been previously reported.16
The aim of this study was to quantitatively assess the effect of CKD on plasma p-tau217 concentrations as measured by immunoassay and IP-MS in individuals with and without amyloid pathology. We examined the association between eGFR and p-tau217 concentrations in a well characterized cohort of participants and derived equations to estimate the effect of eGFR on p-tau217 concentration and %p-tau217 measurements across CKD stages of impaired renal function.
Methods
Participants
Participants were retrospectively selected from the MCSA and the Mayo Clinic Alzheimer's Disease Research Center (ADRC) in Rochester, MN. The MCSA is a population-based study in Olmsted County, Minnesota, examining long-term cognitive aging in adults to study prevalence, incidence, and risk factors of mild cognitive impairment (MCI) and dementia with a focus on biomarkers for dementia.17 The Mayo Clinic ADRC is a longitudinal study of participants referred to the Mayo Clinic behavioral neurology practice.
Study samples were selected at random to yield a range of clinical diagnoses of cognitive unimpairment (CU), MCI, or dementia, and amyloid-PET centiloid values. All participant samples that were included (n = 250) had the following parameters: (1) plasma p-tau217 and np-tau217 concentrations measured by IP-MS (C2N Diagnostics); (2) amyloid-PET data; (3) information about CKD status based on at least 2 coded indications of CKD in the medical record within the past 5 years before sample draw; and (4) available concurrent plasma and serum sample aliquots from the same visit as the sample aliquot used for p-tau217 mass spectrometry measurement. The concurrent plasma aliquot was used for p-tau217 measurement by the ALZpath assay, and the serum aliquot was used for creatinine measurement and eGFR determination. Samples where either the ALZpath p-tau217 or the creatinine measurement failed (n = 48) because of insufficient sample volume were excluded from final analysis yielding a total of 202 participants. No comorbidities or other clinical information were used as exclusion criteria.
During testing, the laboratories were blinded to the clinical diagnosis, amyloid-PET data, and any previous plasma biomarker results.
Sample Collection
Fasting blood samples were collected in EDTA tubes (plasma) or serum tubes (serum). Plasma and serum were separated within 2 hours of collection. After centrifugation, samples were aliquoted into 1.5-mL polypropylene tubes, which were stored frozen at −80°C until testing.
ALZpath p-tau217 Assay
The ALZpath p-tau217 assay is a plasma-based immunoassay performed on the Quanterix Simoa HD-X automated immunoassay analyzer.18 EDTA-plasma samples were analyzed directly from the aliquot tubes. Testing was performed per manufacturer instructions and results expressed in pg/mL.
p-Tau217 Mass Spectrometry Assay
EDTA-plasma samples were shipped frozen to C2N Diagnostics for analysis. Concentrations (pg/mL) of p-tau217 and np-tau217 concentrations were determined by IP-MS as previously described.19 The %p-tau217 measure was calculated as p-tau217 measured concentration divided by the np-tau217 measured concentration × 100%. For samples with p-tau217 concentrations below the analytical measurement range (<0.50 pg/mL), a value of 0.25 pg/mL was used to calculate the %p-tau217.
Creatinine and eGFR
Serum creatinine measurements were performed using the Roche Elecsys enzymatic method. eGFR was calculated using the 2021 CKD-EPI equations.20
11C Pittsburgh Compound B PET Imaging
Amyloid-PET imaging was performed using 11C Pittsburgh Compound B, and PET images were analyzed using an in-house automated image processing pipeline as described previously.21,22 Amyloid-PET was considered positive (A+) based on a centiloid value of ≥25.22 An amyloid-PET centiloid value of 25 was used because it has been previously reported as being optimal for identification of an intermediate-to-high degree of AD neuropathologic changes.23,24
Statistical Analysis
Differences in plasma p-tau217 assays by eGFR classification (either < or ≥60) among A− and A+ participants were evaluated with Wilcoxon rank sum tests. Normal approximated p values were calculated in the event of ties. Log-log linear regression was used to assess associations of continuous eGFR with plasma p-tau217 assays. Predicted geometric mean p-tau217 concentrations, equivalent to the estimated median of a log-normal distribution, and 95% CIs were calculated by exponentiating estimates at eGFRs of 30, 40, 45, 50, and 60 mL/min/1.73 m2. Associated percentage change relative to an eGFR of 60 mL/min/1.73 m2 was reported with 95% CIs. We used a 0.42 pg/mL cutoff for the ALZpath p-tau217 assay to evaluate the diagnostic properties of this assay in discriminating between A− and A+ in the context of CKD.
BMI was not considered to be a confounder of the associations between eGFR and plasma p-tau217 after observing a rank correlation of −0.07 between the two. In addition, insufficient evidence of association between BMI and eGFR was observed in a simple linear regression and log-log linear model estimates were changed a little when including BMI as a covariate. A result was deemed statistically significant if its p value was below the standard alpha threshold of 0.05. All analyses were performed using R version 4.2.2 (R Foundation for Statistical Computing, Vienna, Austria).
Standard Protocol Approvals, Registrations, and Patient Consents
The MCSA and Mayo Clinic ADRC informed consent protocols have been approved by the Institutional Review Board (IRB) of Mayo Clinic (IRB #14-004401 and IRB #712-98). Written informed consent was obtained for all who participated.
Data Availability
Data not provided in the article because of space limitations may be shared (anonymized) at the request of any qualified investigator for purposes of replicating procedures and results.
Results
Participants (n = 202) included individuals with diagnoses of CU (n = 109), MCI (n = 71), and dementia (n = 22). Participant demographics (age, sex, race, BMI, and eGFR) and associated CKD stages are presented in Table 1. The median age was 79 years (range, 56–95 years), 62% of the participants were male, and nearly all (99%) were White and non-Hispanic. Median eGFR (mL/min/1.73 m2) was 60, 64, and 68 in the CU, MCI, and dementia groups, respectively. Median eGFR (mL/min/1.73 m2) also did not vary significantly between the A− (median eGFR of 63) and A+ (median eGFR of 61) cohorts.
Table 1.
Study Demographics and Measured Plasma Tau217 Concentrations
| Total (n = 202) | CU (n = 109) | MCI (n = 71) | Dementia (n = 22) | p Valuea | A− (n = 88) | A+ (n = 114) | p Valueb | |
| Age, y | ||||||||
| Median (Q1, Q3) | 79 (72, 85) | 78 (73, 86) | 81 (74, 87) | 74 (65, 80) | 0.003 | 78 (71, 83) | 80 (74, 87) | 0.11 |
| Mean (SD) | 78 (9) | 78 (9) | 80 (8) | 72 (10) | 77 (8) | 79 (9) | ||
| Range | 56–95 | 60–94 | 59–95 | 56–90 | 59–94 | 56–95 | ||
| Sex, n (%) | 0.53 | 0.36 | ||||||
| Female | 76 (38) | 44 (40) | 23 (32) | 9 (41) | 30 (34) | 46 (40) | ||
| Male | 126 (62) | 65 (60) | 48 (68) | 13 (59) | 58 (66) | 68 (60) | ||
| Race/ethnicity, n (%) | 0.70 | 0.14 | ||||||
| Asian | 1 (0) | 0 (0) | 1 (1) | 0 (0) | 1 (1) | 0 (0) | ||
| Black | 2 (1) | 1 (1) | 1 (1) | 0 (0) | 2 (2) | 0 (0) | ||
| White, not Hispanic | 199 (99) | 108 (99) | 69 (97) | 22 (100) | 85 (97) | 114 (100) | ||
| APOE ε4 genotype, n (%) | <0.001 | <0.001 | ||||||
| Noncarrier | 126 (63) | 75 (69) | 43 (61) | 8 (36) | 66 (76) | 60 (53) | ||
| Homozygote | 66 (33) | 33 (31) | 25 (35) | 8 (36) | 21 (24) | 45 (39) | ||
| Heterozygote | 9 (4) | 0 (0) | 3 (4) | 6 (27) | 0 (0) | 9 (8) | ||
| BMI, kg/m2 | 0.003 | <0.001 | ||||||
| Median (Q1, Q3) | 28 (25, 31) | 29 (26, 31) | 27 (25, 30) | 25 (23, 27) | 29 (26, 32) | 27 (24, 30) | ||
| Range | 18–45 | 18–44 | 20–45 | 19–32 | 20–45 | 18–44 | ||
| Amyloid-PET, Centiloid ≥25 (PiB SUVR ≥1.52), n (%) | 0.001 | — | ||||||
| A− | 88 (44) | 58 (53) | 27 (38) | 3 (14) | 88 (100) | 0 (0) | ||
| A+ | 114 (56) | 51 (47) | 44 (62) | 19 (86) | 0 (0) | 114 (100) | ||
| eGFR, mL/min/1.73 m2 | 0.03 | 0.84 | ||||||
| Median (Q1, Q3) | 62 (53, 74) | 60 (47, 72) | 64 (54, 76) | 68 (61, 80) | 63 (54, 74) | 61 (50, 74) | ||
| Range | 25–98 | 25–95 | 25–98 | 45–95 | 25–98 | 25–95 | ||
| eGFR ≥60 mL/min/1.73 m2, n (%) | 0.06 | 0.32 | ||||||
| No | 86 (43) | 53 (49) | 28 (39) | 5 (23) | 34 (39) | 52 (46) | ||
| Yes | 116 (57) | 56 (51) | 43 (61) | 17 (77) | 54 (61) | 62 (54) | ||
| eGFR, mL/min/1.73 m2, n (%) | 0.09 | 0.59 | ||||||
| <45 | 29 (14) | 21 (19) | 8 (11) | 0 (0) | 12 (14) | 17 (15) | ||
| 45–59 | 57 (28) | 32 (29) | 20 (28) | 5 (23) | 22 (25) | 35 (31) | ||
| ≥60 | 116 (57) | 56 (51) | 43 (61) | 17 (77) | 54 (61) | 62 (54) | ||
| CKD stage (eGFR range), n (%)c | — | — | ||||||
| 1 (≥90) | 11 (5) | 6 (6) | 3 (4) | 2 (9) | 6 (7) | 5 (4) | ||
| 2 (60–90) | 105 (52) | 50 (46) | 40 (56) | 15 (68) | 48 (55) | 57 (50) | ||
| 3a (45–59) | 57 (28) | 32 (29) | 20 (28) | 5 (23) | 22 (25) | 35 (31) | ||
| 3b (30–44) | 23 (11) | 17 (16) | 6 (8) | 0 (0) | 10 (11) | 13 (11) | ||
| 4 (15–29) | 6 (3) | 4 (4) | 2 (3) | 0 (0) | 2 (2) | 4 (4) | ||
| ALZpath p-tau217, pg/mL | <0.001 | |||||||
| Median (Q1, Q3) | 0.40 (0.24, 0.73) | 0.33 (0.20, 0.50) | 0.48 (0.27, 0.79) | 1.09 (0.70, 1.49) | <0.001 | 0.25 (0.18, 0.38) | 0.65 (0.38, 1.04) | |
| Range | 0.06–3.50 | 0.07–2.69 | 0.06–3.50 | 0.20–3.35 | 0.07–1.22 | 0.06–3.50 | ||
| C2N p-tau217, pg/mL | <0.001 | <0.001 | ||||||
| Median (Q1, Q3) | 1.52 (0.66, 3.19) | 1.29 (0.60, 1.95) | 1.72 (0.76, 3.35) | 5.92 (2.87, 9.39) | 0.78 (0.25, 1.37) | 2.56 (1.44, 4.45) | ||
| Range | 0.25–17.07 | 0.25–9.56 | 0.25–10.84 | 0.25–17.07 | 0.25–5.35 | 0.25–17.07 | ||
| C2N np-tau217, pg/mL | 0.32 | 0.32 | ||||||
| Median (Q1, Q3) | 105 (85, 139) | 110 (91, 140) | 96 (79, 135) | 110 (91, 137) | 100 (83, 135) | 113 (90, 140) | ||
| Range | 18–367 | 18–367 | 46–292 | 76–225 | 18–367 | 46–320 | ||
| C2N %p-tau217 | <0.001 | <0.001 | ||||||
| Median (Q1, Q3) | 1.32 (0.63, 2.54) | 1.01 (0.56, 1.89) | 1.69 (0.80, 2.84) | 5.04 (2.44, 7.90) | 0.67 (0.40, 1.14) | 2.28 (1.35, 3.95) | ||
| Range | 0.14–15.37 | 0.14–6.66 | 0.16–9.32 | 0.33–15.37 | 0.14–6.66 | 0.16–15.37 |
Abbreviations: A− = amyloid-PET negative; A+ = amyloid-PET positive; BMI = body mass index; CU = cognitive unimpairment; eGFR = estimated glomerular filtration rate; MCI = mild cognitive impairment; np-tau217 = nonphosphorylated-tau217; PiB = 11C Pittsburgh compound B; p-tau217 = phosphorylated tau217; SUVR = standardized uptake value ratio.
A total of 202 participants were classified as CU, MCI, or dementia. These participants were also classified as A− or A+.
p Values based on three-group Kruskal-Wallis tests for continuous measures or three-group χ2 tests for categorical measures.
p Values based on two-group Wilcoxon rank sum tests for continuous measures or χ2 tests for categorical measures.
p Value not reported because this classification is based on eGFR for which p values are already shown.
Figure 1 shows the amyloid-PET centiloids vs the p-tau217, np-tau217, and %p-tau217 assay determinations for eGFR (mL/min/1.73 m2) patient subsets of <60 and 60+. The eGFR cut point of 60 (mL/min/1.73 m2) corresponds to the lower eGFR limit of CKD stage 2. Spearman correlation coefficient values (ρ) are given for each. For the ALZpath p-tau217, C2N p-tau217, and C2N %p-tau217 assays, the ρ values are comparatively higher for 60+ eGFR values (ρ from 0.70 to 0.75, all p < 0.001) than for the <60 eGFR cohort (ρ from 0.54 to 0.61, p < 0.001), indicating a stronger correlation with amyloid-PET centiloid values. As expected, the np-tau217 assay did not show significant correlation with amyloid-PET centiloid values as compared with the correlations observed between amyloid-PET centiloid and p-tau217 determinations.
Figure 1. p-Tau217, np-tau217, and %p-tau217 Measurements vs Amyloid-PET Centiloid Values for eGFR <60 and eGFR 60+ Cohorts.
Spearman correlation coefficient values (ρ) are given for each plot. The red dashed line denotes a centiloid value of 25. Centiloid values of ≥25 were considered amyloid positive. The significance level for each correlation (p) is also shown. eGFR = estimated glomerular filtration rate; np-tau217 = nonphosphorylated-tau217; p-tau217 = phosphorylated tau217.
Figure 2 compares the p-tau217, np-tau217, and %p-tau217 assay distributions for A+ (n = 88) and A− (n = 114) between participants by eGFR subsets of <60 (mL/min/1.73 m2) and 60+ (≥60) (mL/min/1.73 m2). The A+ cohort did not exhibit significant differences in p-tau217 measurements between the eGFR <60 and 60+ (mL/min/1.73 m2) subsets regardless of the p-tau217 assay. Within the A+ cohort, participants with an eGFR <60 (mL/min/1.73 m2) did not exhibit significantly higher p-tau217 median concentrations compared with participants with an eGFR of 60+ (mL/min/1.73 m2) in both the ALZpath (medians of 0.66 pg/mL vs 0.65 pg/mL; p = 0.26) and C2N p-tau217 (medians of 2.80 pg/mL vs 2.40 pg/mL; p = 0.43) assays. By contrast, for the A− cohort, participants with an eGFR <60 (mL/min/1.73 m2) had significantly higher median p-tau217 concentrations (p < 0.001) as compared with participants with an eGFR of 60+ (mL/min/1.73 m2) in both the ALZpath p-tau217 (medians of 0.31 pg/mL vs 0.22 pg/mL) and C2N p-tau217 (medians of 1.14 pg/mL vs 0.64 pg/mL) assays. Significant differences in medians (p < 0.001) were observed between eGFR <60 and 60+ (mL/min/1.73 m2) in both the A− (medians of 139.5 pg/mL vs 95.4 pg/mL) and A+ cohorts (medians of 134.6 pg/mL vs 95.2 pg/mL) for C2N np-tau217. Finally, for the %p-tau217 ratio, differences between eGFR <60 and 60+ (mL/min/1.73 m2) individual cohort medians were not statistically significant for both the A− (medians of 0.88 pg/mL vs 0.65 pg/mL; p = 0.06) and A+ (medians of 2.08 pg/mL vs 2.35 pg/mL; p = 0.12) cohorts.
Figure 2. p-Tau217, np-tau217, and %p-tau217 Measurements for eGFR <60 and eGFR 60+.
Box and whisker plots of p-tau217 (A, B), np-tau217 (C), and %ptau217 (D) among amyloid-PET–positive (A+) and amyloid-PET–negative (A–) participants by eGFR status of <60 mL/min/1.73 m2 (blue) and 60+ mL/min/1.73 m2 (yellow). The median value is shown as a line within the box with the limits of the box representing 25th and 75th interquartile percent values. The whiskers extend to the largest and smallest values within 1.5 times the interquartile range. Kruskal-Wallis test was used to generate the p values shown. eGFR = estimated glomerular filtration rate; np-tau217 = nonphosphorylated-tau217; p-tau217 = phosphorylated tau217.
Log-log linear regression fits of p-tau217 and np-tau217 concentrations and %p-tau217 vs eGFR are shown in Figure 3. Fits are shown among all participants, among amyloid-negative participants only (A−), and among amyloid-positive participants only (A+). The resulting best-fit equations after exponentiation for each assay are given in Table 2 with corresponding calculated geometric means (or median of the log-normal distribution) at 60, 50, 45, 40, and 30 (mL/min/1.73 m2) eGFR. Using these best-fit equations, the percentage change for the geometric mean of the ALZpath and C2N p-tau217 concentrations between an eGFR of 45 and 60 (mL/min/1.73 m2) were +23% and +32%, respectively, for all participants. The %p-tau217 percentage change between an eGFR of 45 (mL/min/1.73 m2) and 60 (mL/min/1.73 m2) showed a smaller change of +6.0%. This smaller percentage change in %p-tau217 is likely attributable to the estimated concomitant increase in np-tau217 of 24% between an eGFR of 45 and 60.
Figure 3. p-Tau217, np-tau217, and %p-tau217 Measurements vs eGFR.
Best-fit log-log equations after exponentiation are shown in red with dashed 95% CIs. “All” represents all participants (n = 202), “A−” represents amyloid-PET–negative participants (N = 88), and “A+” (N = 114) represents amyloid-PET–positive participants. eGFR = estimated glomerular filtration rate; np-tau217 = nonphosphorylated-tau217; p-tau217 = phosphorylated tau217.
Table 2.
Best-Fit Equations and Percentage Change vs Baseline Measurements at eGFR 60
| eGFR | ALZpath p-tau217 | |||||
| All p-tau217 = 8.42 × eGFR(−0.7322) |
Amyloid− p-tau217 = 11.83 × eGFR(−0.9395) |
Amyloid+ p-tau217 = 5.55 × eGFR(−0.534) |
||||
| Calculated value, pg/mL | % Change from 60 eGFR (95% CI) | Calculated value, pg/mL | % Change from 60 eGFR (95% CI) | Calculated value, pg/mL | % Change from 60 eGFR (95% CI) | |
| 60 | 0.42 | N/A | 0.25 | N/A | 0.62 | N/A |
| 50 | 0.48 | +14 (7–22) | 0.30 | +19 (12–26) | 0.69 | +10 (2–20) |
| 45 | 0.52 | +23 (11–37) | 0.33 | +31 (19–45) | 0.73 | +17 (3–33) |
| 40 | 0.57 | +35 (16–56) | 0.37 | +46 (27–68) | 0.77 | +24 (4–49) |
| 30 | 0.70 | +66 (29–113) | 0.48 | +92 (51–143) | 0.90 | +45 (6–97) |
| eGFR | C2N p-tau217 | |||||
| All p-tau217 = 70.96 × eGFR(−0.9577) |
Amyloid− p-tau217 = 350.5 × eGFR(−1.512) |
Amyloid+ p-tau217 = 17.02 × eGFR(−0.4809) |
||||
| Calculated value, pg/mL | % Change from 60 eGFR (95% CI) | Calculated value, pg/mL | % Change from 60 eGFR (95% CI) | Calculated value, pg/mL | % Change from 60 eGFR (95% CI) | |
| 60 | 1.41 | N/A | 0.72 | N/A | 2.38 | N/A |
| 50 | 1.67 | +19 (9–31) | 0.94 | +32 (19–45) | 2.59 | +9 (−2 to 22) |
| 45 | 1.85 | +32 (14–52) | 1.11 | +55 (32–80) | 2.73 | +15 (−4 to 37) |
| 40 | 2.07 | +47 (20–81) | 1.32 | +85 (49–129) | 2.89 | +22 (−5 to 56) |
| 30 | 2.73 | +94 (36–176) | 2.04 | +185 (97–314) | 3.31 | +40 (−9 to 114) |
| eGFR | C2N np-tau217 | |||||
| All np-tau217 = 2,423 × eGFR(−0.7588) |
Amyloid− np-tau217 = 4,194 × eGFR(−0.9044) |
Amyloid+ np-tau217 = 1,570 × eGFR(−0.6437) |
||||
| Calculated value, pg/mL | % Change from 60 eGFR (95% CI) | Calculated value, pg/mL | % Change from 60 eGFR (95% CI) | Calculated value, pg/mL | % Change from 60 eGFR (95% CI) | |
| 60 | 108 | N/A | 103 | N/A | 113 | N/A |
| 50 | 124 | +15 (12–18) | 122 | +18 (12–24) | 127 | +12 (9–17) |
| 45 | 135 | +24 (19–30) | 134 | +30 (20–40) | 135 | +20 (14–27) |
| 40 | 147 | +36 (28–45) | 149 | +44 (30–60) | 146 | +30 (20–41) |
| 30 | 183 | +69 (52–89) | 194 | +87 (56–124) | 176 | +56 (36–79) |
| eGFR | C2N %p-tau217 | |||||
| All %p-tau217 = 2.929 × eGFR(−0.1989) |
Amyloid− %p-tau217 = 8.357 × eGFR(−0.6081) |
Amyloid+ %p-tau217 = 1.084 × eGFR(0.1628) |
||||
| Calculated value | % Change from 60 eGFR (95% CI) | Calculated value | % Change from 60 eGFR (95% CI) | Calculated value | % Change from 60 eGFR (95% CI) | |
| 60 | 1.30 | N/A | 0.69 | N/A | 2.11 | N/A |
| 50 | 1.35 | +4 (−5 to 13) | 0.77 | +12 (2–22) | 2.05 | −3 (−13 to 8) |
| 45 | 1.37 | +6 (−8 to 21) | 0.83 | +19 (3–38) | 2.01 | −5 (−19 to 13) |
| 40 | 1.41 | +8 (−11 to 31) | 0.89 | +28 (4–57) | 1.98 | −6 (−26 to 18) |
| 30 | 1.49 | +15 (−17 to 59) | 1.06 | +52 (8–116) | 1.89 | −11 (−40 to 33) |
Abbreviations: eGFR = estimated glomerular filtration rate; N/A = not available; np-tau217 = nonphosphorylated-tau217; p-tau217 = phosphorylated tau217.
Best log-log fit equations from Figure 3 are shown. These equations were used to calculate (calculated value) geometric mean (median) p-tau217, np-tau217, or %p-tau217 values at different eGFRs (mL/min/1.73 m2). These were calculated for each assay for all samples, amyloid-PET–negative samples, and amyloid-PET–positive, samples. The percentage change at eGFR X (where X = eGFR of 50, 45, 40, or 30) from eGFR 60 was calculated using (p-tau217 at eGFR X − p-tau217 at eGFR 60)/(p-tau217 at eGFR 60). 95% CIs are given for percentage change calculations.
Overall, the A− cohort was more affected by reductions in eGFR from 60 to 45 (mL/min/1.73 m2) than the A+ cohort in all assays (Table 2). For the ALZpath p-tau217 measurement, the percentage change for 45 vs 60 (mL/min/1.73 m2) eGFR was +31% among A− participants vs +17% among A+ participants. For C2N p-tau217, the change was +55% for A− vs +15% for A+ participants for 45 vs 60 (mL/min/1.73 m2) eGFR. Smaller changes were observed in the C2N %p-tau217 assays between an eGFR of 60 and 45 (mL/min/1.73 m2), with the percentage changes of +19% for A− participants vs −5.0% for A+ participants. In all cases for p-tau217 and np-tau217, the calculated increases between 60 and 30 (mL/min/1.73 m2) eGFR were more than double than the increases observed between 60 and 45 (mL/min/1.73 m2) eGFR for the A− cohorts.
Using the ALZpath p-tau217 assay cutoff (0.42 pg/mL) available at the time of this publication,18 the number of samples classified as positive or negative at different CKD stages for the A− and A+ samples were calculated (Table 3). ALZpath p-tau217 results >0.42 pg/mL were classified as positive. Table 3 presents concordance between p-tau217 and amyloid-PET for all participants and at different CKD stages, whereas Table 4 presents the difference in concordance for eGFR <45 vs 45+ and eGFR <60 vs 60+(mL/min/1.73 m2). At more severe CKD stages, the proportion of amyloid-PET–negative samples that were classified as positive for p-tau217 increased. For example, in the A− group with eGFR <45 (mL/min/1.73 m2) (CKD stage 3b and greater), 50% (6/12) had ALZpath p-tau217 concentrations of >0.42 pg/mL. By contrast, in A− participants with eGFR values of 45+ (mL/min/1.73 m2), only 11% (8/76) had p-tau217 concentrations >0.42 pg/mL. This effect was less pronounced when comparing an eGFR of <60 vs 60+(mL/min/1.73 m2) for the A− cohort, where 29% (10/34) vs 7% (4/54) of A− samples were classified as positive by the ALZpath p-tau217 assay, respectively. Among the A+ participants, the number of samples who exhibited p-tau217 concentrations >0.42 pg/mL was highest in participants with lower eGFR. Among participants with eGFR <45 (mL/min/1.73 m2), 100% (17/17) of participants had p-tau217 concentrations >0.42 pg/mL, whereas 68% (42/62) of the A+ participants had p-tau217 concentrations >0.42 pg/mL in the eGFR 60+ cohort.
Table 3.
Concordance of Amyloid-PET Positivity and ALZpath p-tau217 for Different CKD Stages
| ALZpath p-tau217 | All participants CKD stage 1–4 |
eGFR <45 CKD stage 3b–4 |
eGFR 45–59 CKD stage 3a |
eGFR 60+ CKD stage 1–2 |
||||
| Amyloid-PET | Amyloid-PET | Amyloid-PET | Amyloid-PET | |||||
| Negative N (%) |
Positive N (%) |
Negative N (%) |
Positive N (%) |
Negative N (%) |
Positive N (%) |
Negative N (%) |
Positive N (%) |
|
| Negative (≤0.42 pg/mL) | 74 (84%) | 33 (29%) | 6 (50%) | 0 | 18 (82%) | 13 (37%) | 50 (93%) | 20 (32%) |
| Positive (>0.42 pg/mL) | 14 (16%) | 81 (71%) | 6 (50%) | 17 (100%) | 4 (18%) | 22 (63%) | 4 (7%) | 42 (68%) |
| Total | 202 | 29 | 57 | 116 | ||||
Abbreviations: CKD = chronic kidney disease; eGFR = estimated glomerular filtration rate; p-tau217 = phosphorylated tau217.
Concordance of amyloid-PET classification and the ALZpath p-tau217 classification for different CKD stages using a cutoff of >0.42 pg/mL as described by Ashton et al.18 eGFR ranges are given in mL/min/1.73 m2.
Table 4.
Concordance of Amyloid-PET Positivity and ALZpath p-tau217 for eGFR Ranges of <45 vs 45+ and for eGFR <60 vs 60+
| ALZpath p-tau217 | eGFR <45 CKD stage 3b–4 |
eGFR 45+ CKD stage 1–3a |
eGFR <60 CKD stage 3a–4 |
eGFR 60+ CKD stage 1–2 |
||||
| Amyloid-PET | Amyloid-PET | Amyloid-PET | Amyloid-PET | |||||
| Negative N (%) |
Positive N (%) |
Negative N (%) |
Positive N (%) |
Negative N (%) |
Positive N (%) |
Negative N (%) |
Positive N (%) |
|
| Negative (≤0.42 pg/mL) | 6 (50%) | 0 | 68 (89%) | 33 (34%) | 24 (71%) | 13 (25%) | 50 (93%) | 20 (32%) |
| Positive (>0.42 pg/mL) | 6 (50%) | 17 (100%) | 8 (11%) | 64 (66%) | 10 (29%) | 39 (75%) | 4 (7%) | 42 (68%) |
| Total | 29 | 173 | 86 | 116 | ||||
Abbreviations: CKD = chronic kidney disease; eGFR = estimated glomerular filtration rate; p-tau217 = phosphorylated tau217.
Concordance of amyloid-PET classification and the ALZpath p-tau217 classification for different eGFR ranges (mL/min/1.73 m2) using a p-tau217 cutoff of >0.42 pg/mL as described by Ashton et al.18
Classification of Evidence
This study provides Class II evidence that in patients with CKD stage 3 (especially stage 3b) or higher, p-tau217 concentrations are increased, with a greater increase in amyloid-PET–negative patients.
Discussion
This study quantitatively assessed the relationship between eGFR and p-tau217 concentrations in both immunoassay and MS-based assay determinations in a cohort of participants over a range of eGFR values and amyloid-PET classifications to evaluate how impaired kidney function affects p-tau217 concentrations. Although previous studies have indicated that CKD may affect the interpretation of some AD plasma biomarkers, such as p-tau217, these studies did not systematically evaluate a continuum of numerical eGFR or quantitatively characterize the influence of decreased kidney function on p-tau217 concentrations.12
As the glomerular filtration rate decreases, protein clearance and plasma protein concentrations increase in a nonlinear fashion.14 Both creatinine (molecular weight [M.W.] of 0.1 kilodalton [kDa]) and cystatin C (M.W. 13 kDa) are proteins that increase in a log-log linear fashion (and this can be described by log-log linear or “power function” fit equations) vs decreases in eGFR.14 Based on this, it would seem advantageous to fit p-tau (M.W. of 50–80 kDa) concentrations vs eGFR in a log-log linear manner, rather than using simple linear fit models for p-tau217 concentrations vs eGFR. Indeed, increases in p-tau concentrations because of reduced filtration were smaller between an eGFR of 60 and 45 than between an eGFR of 45 and 30, supporting the use of log-log linear fit function. We used 60 (mL/min/1.73 m2), the lower limit of eGFR stage 2, as a comparative baseline eGFR in this study, in part, because of the observations that concentrations of creatinine are relatively unchanged at eGFRs above 60 mL/min/1.73 m2.14 Owing to the expected positive association between p-tau217 concentrations and amyloid level in the A+ cohort, we feel that the analysis of A− participants is likely to provide a more accurate estimate of the true effect of eGFR on p-tau217 concentrations than the overall A+/A− population.
Our findings suggest that in A− cohort participants with significantly impaired kidney function (CKD stage 3b or higher or an eGFR <45 mL/min/1.73 m2), p-tau217 concentrations can be falsely elevated, such that participants might be misclassified as being falsely positive for the presence of amyloid pathology (Table 3). Concordantly, A+ participants also showed increased p-tau217 concentrations in the presence of reduced eGFR. This may result in a higher number of A+ participants with significantly decreased kidney function being classified as positive (increased sensitivity) when compared with participants without renal impairment (Tables 3 and 4). This effect may increase amyloid detection sensitivity estimates while simultaneously decreasing specificity estimates for p-tau217 measurements by some p-tau217 assays, depending on the relative number of participants with CKD included in the evaluation cohorts.
The effect of reduced eGFR on p-tau217 concentrations was more pronounced in the A− compared with the A+ group. The reason for the apparently larger relative increases in p-tau217 concentrations in the A− cohort is unknown; however, it does not seem to be methodology dependent because it was observed in both the immunoassay and IP-MS–based p-tau217 assay as well as in np-tau217 and %p-tau217. The apparent disparate effects of CKD on p-tau217 measurements between A+ and A− participants may be due to the additional noise from pathologic p-tau production confounding power function estimates of p-tau217 concentrations across the examined reduced eGFR range in the A+ participants. Alternatively, this may be due to differences in relative macromolecular clearances of p-tau217 in A− vs A+ participants, including perhaps saturation of clearance of elevated p-tau217 in A− participants, although there is no evidence available to substantiate this.
Although established clinical cut points are not currently available for all the assays examined here, a published ALZpath assay single-cut point model (positive >0.42 pg/mL) has been reported.18 Applying this assay-specific p-tau217 threshold to the ALZpath immunoassay in the A− cohort, the best-fit estimate reaches 0.42 pg/mL at an eGFR of 35 mL/min/1.73 m2 (stage 3b). This eGFR is an illustrative example rather than a proposed eGFR decision level. Because the geometric mean can be interpreted as the median of a log-normal distribution, our results suggest that approximately half of A− participants with an eGFR of 35 mL/min/1.73 m2 would be incorrectly classified as positive using a single threshold of 0.42 pg/mL in the ALZpath assay. Based on the findings presented here, we believe that the risk of false positives for amyloid pathology is higher for individuals with CKD stage 3b–5 using p-tau217–based methods.
In principle, best-fit equations could be used to adjust assay-specific p-tau217 concentration (or for percentage p-tau217 ratio)–based cutoffs for each eGFR value by estimating the relative percentage change in p-tau217 concentrations (or ratio) in A− individuals for a specified eGFR as compared with a relatively unaffected eGFR such as 60, as is presented in Table 2. However, this comparative approach would require that the population used to establish the original cutoff values for interpretation be CKD free and with a homogenous eGFR, which has not been established in previous studies.18 In addition, power function best-fit imprecision stemming from the CKD patient sample size in this study and added reporting/interpretation complexity disfavor this approach.
These results demonstrate limitations for the specificity for amyloid pathology of plasma p-tau217 measurements alone in the presence of significant renal impairment (eGFR <45 mL/min/1.73 m2 or CKD stage 3b or greater, Table 2), potentially resulting in the misclassification of A− participants as A+. In this study, measured p-tau217 concentrations between 60 and 45 mL/min/1.73 m2 (CKD stage 3a) in participants did not seem to be as strongly affected by reduced eGFR, although caution should be used in these patients as well, particularly those who are moderately positive by p-tau217 for amyloid pathology (Table 2). Although a relatively small percentage of individuals (depending on population) being tested will have 3b or greater CKD staging (eGFR <45 mL/min/1.73 m2), the use of an ALZpath assay 2-cut point model in individuals with impaired kidney function might be preferable to avoid misclassification because these individuals likely will be classified in the intermediate range rather than positive.18,25
In individuals with CKD stage 3b or higher (eGFR <45 mL/min/1.73 m2), the use of the %p-tau217 seems to be less affected by CKD than p-tau217 determinations alone (Table 2). This pattern was also seen in the CKD stage 3a population (eGFR 45–<60 mL/min/1.73 m2). This finding agrees with prior observations that the use of a %p-tau217 ratio at least partially mitigated the confounding effects of CKD on p-tau217 measurements.12 The concurrent similar quantitative rates of increase in p-tau217 and np-tau217 as described here likely reduce the effect of decreasing eGFR on %p-tau217. However, the resulting %p-tau217 best-fit equations indicate that in severe CKD (stages 4–5, or eGFR of <30 mL/min/1.73 m2), the %p-tau217 measurement may also be adversely affected. The degree of the impact in individuals with severe CKD cannot be precisely determined using the current data set because of the small number of individuals with CKD stage 4–5. Thus, in this study, estimates of increases in p-tau217 and %p-tau217 become less precise in individuals with more severe eGFR reduction (Figure 3 and Table 2).
This study represents a quantitative study of the effects of moderate-to-severe renal impairment on plasma markers for AD. While this study provides quantitative estimates of the effects of eGFR, larger cohorts of individuals with CKD stages 3b–5 are needed to decrease uncertainty in best-fit model estimates. However, individuals with CKD stages 3b–5 that are also characterized for amyloid status are rare and samples are challenging to obtain. Furthermore, as age and sex are incorporated into eGFR calculations, there are associated alterations in underlying creatinine concentrations at given eGFR values.20 BMI can potentially affect eGFR estimates and p-tau217 concentrations.26 Additional work needs to be conducted to elucidate how these effects on eGFR might affect models of p-tau217 concentrations in relation to eGFR. Furthermore, this data set is largely racial homogeneous, and these findings should be confirmed in other populations. Finally, reductions in eGFR can stem from a number of factors, including hypertension, nephrotoxic substances, cardiac dysfunction, and other comorbidities, which may have unexplored effects on p-tau concentrations or measurements.
The confounding effects of CKD might extend to other p-tau217 assays, as well as other blood-based phosphorylated tau variants such as p-tau231 and p-tau181, which also increase in association with AD-related amyloid pathology.27-29 However, in practice, the generalizability of these findings will need to be confirmed. While this study focused on the most clinically useful blood-based biomarker, p-tau217, others have evaluated the effect of CKD on p-tau181 and also reported a similar increase of p-tau181 in the context of CKD (stages 3–5).11,12 Therefore, the risk of false positives in individuals with CKD should be further evaluated in an assay and cutoff-specific manner when using alternate testing approaches.
Owing to reduced specificity of p-tau217 in the presence of renal impairment, determination of eGFR at the time of plasma p-tau217 testing might be required for guiding patient evaluation. This would ensure that individuals with CKD stages 3b or greater are not evaluated by assays significantly affected by reduced kidney function. In these individuals, amyloid-PET and/or CSF-based assays may be preferable to reduce the risk of potential false-positive result. Although CKD may also influence AD CSF biomarkers, the effect seems to be less pronounced.30,31 Alternatively, a p-tau217 blood-based assay using a ratio approach, such as in the case of the %p-tau217 assay, that appears less susceptible to positive interference in the presence of CKD could be used. Screening for eGFR as part of a diagnostic algorithm is not without precedent. For example, patients undergoing imaging with gadolinium contrast agents are routinely screened for CKD by creatinine-based eGFR because gadolinium can cause nephrogenic fibrosis in individuals with CKD stages 4–5.32
Because plasma p-tau217 immunoassays are convenient, noninvasive tools for the evaluation of amyloid pathology, the increases observed in p-tau217 concentrations in individuals with CKD stages 3b or higher may limit the clinical utility of these assays in this patient population. This degree of renal impairment represents a relatively small but substantial subset (5.8%) of the general 65 years and older population.15 Although this can be mitigated by use of %p-tau217 measurements in individuals in CKD stages 1–3, the use of %p-tau217 might still be problematic in patients with CKD stages 4–5 which represents 1.3% of the general 65+-year-old population.15
Although the specific false-positive rate will depend on the assay and patient population, our data suggest that false-positive rates for p-tau217 assays can be expected to increase with decreasing eGFR. As more is learned about the effects of impaired renal function on the concentration of AD blood-based biomarkers, potential alternative diagnostic pathways and clinical testing algorithms may be introduced to avoid this confounding effect. Diagnostic algorithms that incorporate eGFR measurements to identify patient CKD stage upon assessment of plasma p-tau217 concentrations could be used to avoid potential false elevated results and indicate a need for alternate methods to investigate for the presence of amyloid pathology.
Glossary
- A−
amyloid-PET negative
- A+
amyloid-PET positive
- AD
Alzheimer disease
- ADRC
Alzheimer's Disease Research Center
- BMI
body mass index
- CKD
chronic kidney disease
- CKD-EPI
Chronic Kidney Disease Epidemiology Collaboration
- CU
cognitively unimpaired
- DM
diabetes mellitus
- eGFR
estimated glomerular filtration rate
- IP-MS
immunoprecipitation mass spectrometry
- IRB
institutional review board
- kDA
kilodalton
- MCI
mild cognitive impairment
- MCSA
Mayo Clinic Study of Aging
- MI
myocardial infarction
- M.W.
molecular weight
- np-tau217
nonphosphorylated-tau217
- p-tau217
phosphorylated tau217
Author Contributions
J.A. Bornhorst: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data. C.S. Lundgreen: drafting/revision of the manuscript for content, including medical writing for content; analysis or interpretation of data. S.D. Weigand: drafting/revision of the manuscript for content, including medical writing for content; analysis or interpretation of data. D.J. Figdore: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data. H. Wiste: drafting/revision of the manuscript for content, including medical writing for content; analysis or interpretation of data. M. Griswold: drafting/revision of the manuscript for content, including medical writing for content. P. Vemuri: drafting/revision of the manuscript for content, including medical writing for content. J. Graff-Radford: drafting/revision of the manuscript for content, including medical writing for content. D.S. Knopman: drafting/revision of the manuscript for content, including medical writing for content. P. Cogswell: drafting/revision of the manuscript for content, including medical writing for content. C.R. Jack: drafting/revision of the manuscript for content, including medical writing for content. R.C. Petersen: drafting/revision of the manuscript for content, including medical writing for content. A. Algeciras-Schimnich: drafting/revision of the manuscript for content, including medical writing for content; major role in the acquisition of data; study concept or design; analysis or interpretation of data.
Study Funding
The authors acknowledge grant support from both the NIA (R37 AG011378, R01 AG041851, U01 AG006786, RF1 AG069052, R01 AG056366, RF1 AG061900), NIH (P30 AG062677), and the Carl Angus DeSantis Foundation.
Disclosure
J.A. Bornhorst has participated on an advisory board for Sunbird Bio and received an honorarium from Roche Diagnostics. C.S. Lundgreen, S.D. Weigand, D.J. Figdore, H. Wiste, and M. Griswold report no disclosures. P. Vemuri receives funding from the NIH. J. Graff-Radford receives funding from the NIH; he serves on DSMB for STROKENet, and serves as site investigator for Alzheimer's Clinical Trial Consortium studies co-sponsored by Cognition Therapeutics and Eisai. D.S. Knopman serves on a data safety monitoring board for the Dominantly Inherited Alzheimer Network Treatment Unit study; was an investigator in Alzheimer clinical trials sponsored by Biogen, Lilly Pharmaceuticals, and the University of Southern California, both of which have ended, and is currently an investigator in a trial in frontotemporal degeneration with Alector; has served as a consultant for Roche, AriBio, Linus Health, Biovie, and Alzeca Biosciences but receives no personal compensation; and receives funding from the NIH. P. Cogswell reports no disclosures. C.R. Jack receives funding from the NIH and the Alexander Family Alzheimer's Disease Research Professorship of the Mayo Clinic. R.C. Petersen has consulted for Roche Inc., Genentech Inc., Eli Lilly Inc., Nestle Inc., and Eisai Inc.; has served on a DSMB for Genentech Inc.; receives royalties from Oxford University Press for Mild Cognitive Impairment and from UpToDate; and his research funding is from NIH/NIA. A. Algeciras-Schimnich has participated in advisory boards for Roche Diagnostics and Fujirebio Diagnostics. Go to Neurology.org/N for full disclosures.
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Data Availability Statement
Data not provided in the article because of space limitations may be shared (anonymized) at the request of any qualified investigator for purposes of replicating procedures and results.