METHOD FOR PREDICTING THE RISK OF INCIDENCE OF CHRONIC KIDNEY DISEASE
20230127440 · 2023-04-27
Assignee
Inventors
Cpc classification
G01N33/74
PHYSICS
G01N2800/347
PHYSICS
International classification
Abstract
The present invention relates to means and methods suitable for risk prediction of chronic kidney disease (CKD) using Pro-Enkephalin or fragments thereof as biomarker. The risk prediction methods of the invention are intended for healthy subjects and for subjects suffering from diseases such as hypertension, cardiovascular diseases and events, diabetes, metabolic syndrome, obesity, or autoimmune diseases. Subject matter of the invention is also a method of predicting the worsening or improvement of kidney function or dysfunction in healthy and diseased individuals.
Claims
1. A method for predicting the risk of incidence of chronic kidney disease (CKD) in a subject comprising: a) determining the level of Pro-Enkephalin or fragments thereof in a bodily fluid obtained from said subject; and b) correlating said level of Pro-Enkephalin or fragments thereof with a risk of incidence of chronic kidney disease, wherein a level above a threshold is predictive for an enhanced risk of incidence of chronic kidney disease, wherein the subject is selected from the group comprising (i) healthy subjects, (ii) diseased subjects not having CKD.
2. A method according to claim 1, wherein diseased subjects not having CKD comprises the group of subjects with metabolic syndrome, diabetes, obesity, cardiovascular disease, cardiovascular events, hypertension, and/or autoimmune disease, at the time the sample of bodily fluid is obtained.
3. A method according to claim 1 or claim 2, wherein the subject had a history of a cardiovascular event or cardiovascular disease at the time the sample of bodily fluid is taken, wherein said cardiovascular event or cardiovascular disease is selected from the group comprising myocardial infarction, stroke, acute heart failure, coronary artery disease, cardiac insufficiency, chronic heart failure, and cardiac disease associated with chronic or acute cerebrovascular disease.
4. A method according to claim 1 or claim 2, wherein the subject is diagnosed as suffering from an autoimmune disease at the time the sample of bodily fluid is taken from said subject, wherein the autoimmune disease is selected from the group comprising Sjögren's disease, systemic lupus erythematodes (SLE), psoriasis, polymyositis, dermatomyositis, inclusion body myositis, Myasthenia gravis, autoimmune degenerative diseases of joints, particularly rheumatoid arthritis, or autoimmune diseases of the central nervous system, wherein said subject does not suffer from kidney disease.
5. A method according to any one of claims 1 to 4, wherein said subject has as an estimated glomerular filtration rate (eGFR) of greater than 60 ml/min/1.73 m.sup.2 for >3 months and kidney damage for >3 months.
6. A method according to any one of claims 1 to 5, wherein at least one additional parameter is determined, said parameter being selected from the group comprising: age, gender, systolic blood pressure and/or diastolic blood pressure (SBP and/or DBP), antihypertensive treatment (AHT), body mass index, body fat mass, body lean mass, waist circumference, waist-hip-ratio, current smoker, diabetes heredity, serum creatinine level, cystatin C level, cardiovascular disease (CVD), total cholesterol, triglyceride, low-density-lipocholesterol (LDL-C), high-density-lipocholesterol (HDL-C), whole blood or plasma glucose, plasma insulin, HOMA (Insulin (μU/ml)×glucose (mmol/l)/22.5), and/or HbA.sub.1c (%).
7. A method according to any one of claims 1 to 6, further comprising determining the status of genetic markers.
8. A method for predicting the risk of incidence of chronic kidney disease according to any one of claims 1 to 7, wherein a group of parameters is determined, said group comprising: fasting glucose, systolic blood pressure, anti-hypertensive medication and body mass index (BMI).
9. A method according to any one of the preceding claims, wherein the sample is selected from the group comprising blood sample, a serum sample, a plasma sample, a cerebrospinal fluid sample, a saliva sample and a urine sample or an extract of any of the aforementioned samples.
10. A method according to any of the preceding claims, wherein the Pro-Enkephalin concentration and/or the concentration of other substances found in the bodily fluid is measured in non-fastening or fastening subjects.
11. A method according to any of the preceding claims, wherein the level of Pro-Enkephalin or fragments thereof is determined by an immunoassay
12. A method for predicting the risk of incidence of chronic kidney disease as defined in any of the preceding claims, wherein the Pro-Enkephalin fragment comprises an amino acid sequence as defined in any of the sequences depicted in SEQ ID NOs: 1 to 14.
13. A method according to any of the preceding claims, wherein the Pro-Enkephalin fragment comprises Pro-Enkephalin A 119-159 (SEQ ID NO: 6) or a fragment thereof.
14. A method for predicting the risk of incidence of chronic kidney disease as defined in any of the preceding claims, wherein said method is performed at least once at time-point t0 and optionally at least one or more subsequent time-point(s) (t1 . . . tn) to monitor the risk development of incidence of chronic kidney disease.
15. A method for predicting the risk of incidence of chronic kidney disease as defined in any of the preceding claims, wherein a bodily fluid of a subject with a Pro-Enkephalin level above a certain threshold level, is classified as having an elevated risk for development of CKD, wherein the threshold associated with an elevated risk for development of CKD is between 30 and 80 pmol/L, more preferably between 35 and 60 pmol/L, even more preferably between 40 and 50 pmol/L, most preferred between 41 and 49 pmol/L.
16. A method according to any of the preceding claims, wherein the level of Pro-Enkephalin or fragments thereof of at least 5 amino acids, or at least of 6 amino acids, or at least of 7 amino acids, or at least of 8 amino acids, or at least of 9 amino acids, or at least of 10 amino acids, or at least of 12 amino acids is determined by using a binder to Pro-Enkephalin or fragments thereof of at least 5 amino acids, or of at least 6 amino acids, or of at least 7 amino acids, or of at least 8 amino acids, or of at least 9 amino acids, or of at least 10 amino acids, or of at least 12 amino acids.
17. A method according to claims 1-10 and 12-16, wherein the level of Pro-Enkephalin is determined with an immunoassay or with a mass spectrometric assay.
18. A method according to any of the preceding claims, wherein a binder is used that specifically binds to Pro-Enkephalin or a fragment thereof, preferably selected from the group comprising an antibody, an antibody fragment or a non-Ig-Scaffold binding to Pro-Enkephalin or fragments thereof.
19. A method according to any of the preceding claims, wherein said threshold is <41 pmol/L and indicates a low risk of incidence of chronic kidney disease, a range of 41-49 indicates a medium risk of incidence of chronic kidney disease, and a threshold of >49 pmol/L indicates a high risk of incidence of chronic kidney disease.
20. A method according to any of the preceding claims, wherein an assay is used comprising two binders that bind to two different regions within the region of Pro-Enkephalin that is amino acid 133-140 (SEQ ID NO. 13) and amino acid 152-159 (SEQ ID No. 14) wherein each of said regions comprises at least 4 or 5 amino acids.
21. A method according to any of the preceding claims, wherein the assay sensitivity is <15 pmol/L.
22. A method according to any of the preceding claims, further comprising performing a step of selecting suitable therapeutic or preventive measures, when the level Pro-Enkephalin or fragments thereof is above a threshold, preferably a threshold between 30 and 80 pmol/L, more preferably between 35 and 60 pmol/L, even more preferably between 40 and 50 pmol/L, most preferred between 41 and 49 pmol/L.
23. A method according to any of the preceding claims, wherein said determination of Pro-Enkephalin or fragments thereof is performed more than once in order to monitor the risk of development of the incidence of chronic kidney disease.
24. A method according to any of the preceding claims, wherein said method is performed to stratify said subjects into risk groups.
25. A method for predicting a worsening or improvement of kidney function or dysfunction in (i) healthy subjects, or (ii) diseased subjects with or without kidney dysfunction, wherein said method comprises performing the steps (a) determining the level of Pro-Enkephalin or fragments thereof in a bodily fluid obtained from said subject; and (b) correlating said level of Pro-Enkephalin or fragments thereof with a risk of incidence of chronic kidney disease, wherein a level above a threshold as defined in the preceding claims is predictive for an enhanced risk of worsening of kidney function or dysfunction, and wherein a level below a threshold is predictive for lower risk of worsening of kidney function or dysfunction, optionally comprising steps depicted in any one of the preceding claims.
26. A point-of-care device for performing a method according to any of the preceding claims, wherein said point of care device comprises at least one antibody or antibody fragment directed to amino acid 133-140 (SEQ ID No. 13) and/or amino acid 152-159 (SEQ ID NO. 14).
27. A kit for performing a method according to any of the preceding claims, comprising a point of care device, wherein said point of care device comprises at least one antibody or antibody fragment directed to either amino acid 133-140 (SEQ ID No. 13) or amino acid 152-159 (SEQ ID NO. 14).
Description
EXAMPLES
Example 1—Development of Antibodies
[0140] Antibodies were prepared as set forth in PCT application PCT/EP2013/070470.
Example 2—PENK in Healthy Subjects
[0141] Healthy subjects (n=4211, average age 56 years) were measured using the MR-PENK assay. The mean value was 44.7 pmol MR-PENK pmol/L, the lowest value was 9 pmol/L and the 99.sup.th percentile was 80 pmol/L. Since the assay sensitivity was 5.5 pmol/L, 100% of all healthy subjects were detectable using the described MR-PENK assay.
Example 3—Clinical Study and Statistical Analysis of Obtained Results
[0142] The background population for this study is the population-based prospective study from Malmö, Sweden, (Malmö Diet and Cancer Study MDCS) of which 28,098 healthy men and women born between 1923-1945 and 1923-1950 participated in the baseline examination between 1991 and 1996. The total participation rate was approximately 40.8%. Individuals from 6,103 randomly selected participants of the MDCS who underwent additional phenotyping were included, designed to study epidemiology of carotid artery disease, in the MDC Cardiovascular Cohort (MDC-CC) between 1991 and 1994. During the follow-up re-examination this random sample was re-invited to the follow-up re-examination between 2007 and 2012. 3,734 individuals of those that were alive and had not emigrated from Sweden (N=4,924) attended the follow-up re-examination. After excluding all individuals without MR-PENK levels measured at baseline (n=1,460), the association between yearly change in eGFR, plasma creatinine and plasma Cystatin C in 2,801; 2,843 and 2,978 individuals was tested, respectively, for whom measurements where available at both examinations. The relation between MR-PENK concentration at baseline and presence of CKD at follow-up re-examination was examined in a total of 2,567 participants with an eGFR of higher than 60 ml/min/1.73 m.sup.2 at baseline.
[0143] All participants underwent a physical examination during baseline examination and the following anthropometric characteristics were assessed: height (cm), weight (kg), waist as well as hip circumference by trained nurses. Systolic and diastolic blood pressure (mmHG) were measured after 10 minutes of rest by trained personal. Lean body mass and body fat were estimated using a bioelectric impedance analysis (single-frequence analyses, BIA 103; JRL Systems, Detroit, Mich.). Questions concerning socio-economic status, lifestyle factors and medical history were answered by the participants via self-administrated questionnaire. Non-fasting-blood samples were drawn and immediately frozen to −80° C. and stored in a biological bank available for DNA extraction. Participant in the MDC-CC also provided fasting blood samples in which plasma creatinine (μmol/L) and cystatin C (mg/L) were measured. In addition total cholesterol(mmol/L), Triglyceride (TG)(mmol/L), low-density-lipo-cholesterol (LDL-C) (mmol/L), high-density-lipo-cholesterol (HDL-C) (mmol/L), whole blood glucose (mmol/L), plasma insulin (μlU/ml), HOMA (insulin*glucose/22.5), HbA1c (%) were quantified and blood pressure was measured in supine position with a mercury column sphygmomanometer after 10 min of rest.
[0144] During the follow-up re-examination (2007-2012) the following anthropometric characteristics were measured: height (m), weight (kg), waist and hip circumference (cm), systolic and diastolic blood pressure (SBP and DBP) (mmHG) following a similar protocol as in the baseline examination. Further concentrations of cholesterol (mmol/L), triglyceride (mmol/L), HDL-C (mmol/L), glucose (mmol/L), Creatinine (μmol/L), Cystatin C (mg/l) were quantified in fasting blood samples.
[0145] MR-PENK was measured in fasting plasma samples from 4,634 participants at MDC-CC baseline examination using the chemiluminometric sandwich immunoassay. For 1,460 individuals fasting plasma levels of MR-PENK were lacking. Those were slightly younger, had a marginal higher BMI and plasma creatinine as well as lower systolic blood pressure, fasting glucose and HbA1c-conctration at MDC baseline but did not differ in gender, plasma lipids, cystatin C or anti-hypertensive treatment frequency levels from the included participants (Supplement Table T1). To achieve normal distribution we transformed the positively skewed concentration of fasting plasma MR-PENK with the natural logarithm. Additionally, continuous MR-PENK concentrations were divided into tertiles, defining the first tertile (lowest MR-PENK concentration) as the reference. Due to the fact that women had a significantly higher mean MR-PENK concentration at baseline compared to men (one-way ANOVA P-value <0.000001), fasting plasma levels of MR-PENK were first grouped gender-specific and then these groups were combined. Both, at baseline and follow-up examination, concentrations of creatinine and cystain C were analyzed from plasma and are presented in μmol/L and mg/L, respectively. CKD was defined as presence of an estimated GFR (eGFR) of less than 60 ml/min/1.73 m.sup.2 calculated according to the previously reported CKD-EPI-2012 equation which considers blood concentration of creatinine as well as cystatin C.
[0146] Statistical Analyses
[0147] Association between fasting plasma MR-PENK concentration at baseline and the risk of CKD at follow-up re-examination was analyzed using logistic regression adjusting for follow-up time in years, age, sex, GFR (ml/min/1.73 m.sup.2) and for common risk factors for kidney function at baseline (systolic blood pressure, BMI (kg/m.sup.2), fasting glucose and anti-hypertensive medication).
[0148] SPSS (version 21, IBM) was used for the clinical epidemiological analyses and all analyses were adjusted for sex and age. Additional adjustments for covariates in specific models are reported in the results section. The null-hypothesis was rejected, if a 2-sided P-value of less than 0.05 was observed and the association was considered as statistical significant.
[0149] Cross-sectional analyses between MR-PENK and kidney function at MDC baseline (1991-1994)
[0150] High levels of MR-PENK were significantly associated with older age and decrease in several anthropometric characteristics in both men and women. In addition concentrations of TG, fasting plasma glucose, plasma insulin and HBbA1c decreased with increasing MR-PENK. Creatinine and cystatin C levels were significantly higher for individuals in the highest tertile (Table 1). Further adjustment of the basic model (age & sex) for BMI, body fat mass, fasting plasma glucose concentration, body lean mass, cystatin C or eGFR did not reveal that any of these covariates was driving the observed associations between MR-PENK concentration and the tested phenotypic characteristics.
TABLE-US-00003 TABLE 1 Cross-sectional relationship between tertiles of MR-PENK levels and phenotypic characteristics of Malmö Diet and Cancer Study participants baseline.sup.1 (1991-1994) Fasting plasma MR-proenkephalin concentration.sup.2 n Low Medium High P-trend.sup.3 Age (years) 4634 57.56 (0.153) 58.04 (0.153) 59.12 (0.153) <0.000001 BMI (kg/m.sup.2) 4630 26.69 (0.099) 25.80 (0.098) 24.96 (0.099) <0.000001 Waist (cm) 4629 87.65 (0.255) 84.85 (0.254) 83.00 (0.255) <0.000001 SBP (mmHG) 4634 144.42 (0.459) 141.58 (0.458) 141.334 (0.460) 0.000002 DBP (mmHG) 4634 88.36 (0.237) 87.07 (0.236) 86.78 (0.237) 0.000003 Glucose (mmol/L).sup.4 4616 6.04 (0.039) 5.71 (0.039) 5.56 (0.039) <0.000001 Creatinine (μmol/L) 4541 81.80 (0.370) 84.73 (0.368) 88.96 (0.370) <0.000001 Cystatin C (mg/L) 4310 0.75 (0.004) 0.78 (0.004) 0.83 (0.004) <0.000001 eGFR CKD-EPI 2012 4252 93.33 (0.302) 89.82 (0.302) 85.20 (0.305) <0.000001 Antihypertensive 789 17.0 16.3 17.8 /.sup.5 treatment (%) .sup.1as mean and SE; .sup.2gender-secific MR-PENK tertile cut-offs in pmol/L Males: low: mean 33.08 (18.30-38.50), medium: mean 42.45 (38.60-46.60), high: mean 55.45 (46.70-164.70 - Females: low: mean 37.06 (9.00-43.00), medium: mean 47.40 (43.10-51.70), high: mean 61.71 (51.80-518.10); .sup.3general linear model adjusted for age and sex; .sup.4fasting whole blood was converted into plasma value by multiplication with the factor 1.11; SBP = Systolic blood pressure; DBP = Diastolic blood pressure; .sup.5Chi.sup.2-test
[0151] Prospective changes in kidney function at follow-up re-examination in relation to fasting plasma MR-PENK concentration at baseline examination
[0152] Next the relation between fasting plasma MR-PENK concentration at baseline and change for phenotypic characteristics between baseline and follow-up re-examination in 2,908 participants from MDC-CC was examined. The decline in eGFR as well as the increase of cystatin C and plasma creatinine was significant in a linear model adjusted for age at follow-up, sex and corresponding baseline values. Per year of follow-up men and women classified within the highest tertile of MR-PENK concentration at baseline, eGFR declined by 1.543 ml/min/1.73 m.sup.2 (P.sub.trend<0.001), while cystatin C and plasma creatinine increased by 0.026 mg/l (P.sub.trend<0.01) and 0.222 μmol/L (P.sub.trend<0.00001), respectively. (Table 2).
TABLE-US-00004 TABLE 2 Association between tertiles of fasting plasma MR-PENK at baseline examination (1991-1996) and mean changes by year in kidney function and other clinical characteristics during the follow up re-examination (2007-2012) in Malmö Diet and Cancer Study Fasting plasma MR-proenkephalin concentration Low Medium High N (%) n 971 (33.4) 965 (33.2) 972 (33.2) P-trend.sup.1 BMI (kg/m.sup.2) 2903 0.080 (0.005) 0.080 (0.005) 0.083 (0.005) 0.710206 Waist (cm) 2905 0.602 (0.015) 0.564 (0.015) 0.557 (0.015) 0.033180 SBP (mmHG) 2903 0.270 (0.035) 0.199 (0.035) 0.248 (0.035) 0.655250 DBP (mmHG) 2902 −0.161 (0.019) −0.194 (0.019) −0.211 (0.019) 0.069642 Glucose (mmol/L).sup.2 2897 0.0045 (0.000) 0.0042 (0.000) 0.0039 (0.000) 0.002307 Creatinine (μmol/L) 2767 −0.066 (0.043) −0.034 (0.043) 0.222 (0.043) 0.000003 Cystatin C (mg/L) 2636 0.023 (0.001) 0.023 (0.001) 0.026 (0.001) 0.007428 eGFR CKD-EPI 2012 2601 −1.412 (0.026) −1.412 (0.0269) −1.543 (0.026) 0.000593 Incidence of CKD (%) 2819 233 (24.4) 298 (31.3) 422 (44.3) <0.0001 .sup.1in a general linear model adjusted for age at follow-up, sex and value at baseline; BSA = body surface area; .sup.2difference was calculated transferring the baseline fasting whole blood into plasma value (x factor 1.11); SBP = Systolic blood pressure; DBP = Diastolic blood pressure;
[0153] Prospective analysis of the association between fasting plasma MR-PENK levels at baseline and CKD at follow-up re-examination
[0154] Prevalence of CKD based on eGFR above 60 ml/min/1.73 m.sup.2 was 32.3% in 2,567 participants during a median follow-up time of 16.6 years (range 13.42-20.35 years). The event rate during the follow-up time was 19.46 per 1.000 person-years and the occurrence of CKD was significantly more common in women than in men (20.93 vs. 17.31 per 1,000 person-years; X2 P-value<0.001). We observed a significant risk increase for incidence of CKD at follow-up re-examination with increasing MR-PENK levels in a basic adjusted logistic regression model (OR: 1.165 per increase in 1 SD; P.sub.trend=0.012). Men and women having high baseline concentration of MR-PENK had a ⅓ higher risk for incident CKD compared to individuals having low levels at baseline (OR: 1.34; 95% CI: 1.061-1.701). The association was stronger when we added further risk factor for kidney function, such as fasting plasma glucose, systolic blood pressure, anti-hypertensive medication and BMI at baseline, into the model leading to an OR of 1.236 per increase of 1 SD p-ENK concentration (P.sub.trend<0.01). Participants with highest compared to the lowest MR-PENK levels at baseline had a 51.4% increased risk for incident CKD (95% CI 1.184-1.936). When gender-specific multivariate adjusted analysis was performed, the risk increase for high MR-PENK concentration at baseline was comparable in women (P.sub.trend=0.005), although in men the trend was similar but no longer significant (P.sub.trend=0.08). However, introducing a cross product of gender and tertiles of MR-PENK concentration in the multivariate adjusted model, did not show an interaction for MR-PENK and sex (P.sub.trend=0.99). For sensitivity analyses, prevalent patients with diabetes and CV diseases at MDC-baseline as potential risk-factors for CKD were excluded, which did not change the results in the remaining 2,452 individuals (OR=1.528 for highest MR-PENK concentration at baseline; 95% CI 1.188-1.965).