Method for predicting the risk of incidence of chronic kidney disease

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 comprising: measuring the level of a Pro Enkephalin protein comprising the amino acid sequence of SEQ ID NO:1 or fragments thereof in a sample of bodily fluid obtained from a subject, wherein, before obtaining said sample, a prior sample of bodily fluid of said subject exhibited a level of a Pro Enkephalin protein comprising the amino acid sequence of SEQ ID NO:1 or fragments thereof above 30 pmol/L and said subject was subjected to therapeutic measures to prevent development of chronic kidney disease, wherein said fragments of Pro Enkephalin comprise the amino acid sequence of SEQ ID NO: 2, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 7, SEQ ID NO: 8, SEQ ID NO: 9, or SEQ ID NO: 10, and wherein, at the time of obtainment of said prior sample, the subject was a (i) healthy subject, or (ii) diseased subject that did not have chronic kidney disease and that had an estimated glomerular filtration rate of greater than 60 ml/min/1.73 m.sup.2 for >3 months.

2. The method according to claim 1, wherein at least one additional parameter is measured for the subject and said additional parameter is selected from: age, gender, systolic blood pressure, diastolic blood pressure, anti-hypertensive treatment, body mass index, body fat mass, body lean mass, waist circumference, waist-hip-ratio, current smoker, heredity diabetes, serum creatinine level, cystatin C level, cardiovascular disease, total cholesterol, triglyceride, low-density-lipocholesterol, high-density-lipocholesterol, whole blood or plasma glucose, plasma insulin, and/or HbA.sub.1c.

3. The method according to claim 1, wherein a group of additional parameters are measured for the subject, said group consisting of fasting glucose, systolic blood pressure, anti-hypertensive medication, and body mass index (BMI).

4. The method according to claim 1, wherein the sample of bodily fluid obtained from the subject is a blood sample, a serum sample, a plasma sample, a cerebrospinal fluid sample, a saliva sample, a urine sample or an extract of any of the aforementioned samples.

5. The method according to claim 1, wherein the bodily fluid is obtained from a non-fasting subject.

6. The method of claim 2, wherein the fragments of the Pro Enkephalin each comprise the amino acid sequence of SEQ ID NO: 2, SEQ ID NO: 5, SEQ ID NO: 6, or SEQ ID NO: 10.

7. The method according to claim 1, wherein the prior sample of bodily fluid was measured by an immunoassay with a sensitivity of <15pmol/L.

8. The method according to claim 1, wherein the bodily fluid is obtained from a fasting subject.

9. A method for preparing a sample comprising: obtaining a sample of bodily fluid from a subject; and adding to said sample, a binder that binds to a Pro Enkephalin protein comprising the amino acid sequence of SEQ ID NO:1, or one or more fragments thereof, wherein said one or more fragments comprise the amino acid sequence of SEQ ID NO: 2, SEQ ID NO: 5, SEQ ID NO: 6, SEQ ID NO: 8, SEQ ID NO: 9, SEQ ID NO: 10 or SEQ ID NO: 11, wherein, at the time of obtaining said sample, the subject is a (i) healthy subject, or (ii) diseased subject that does not have chronic kidney disease, and that has had an estimated glomerular filtration rate of greater than 60 ml/min/1.73 m.sup.2 for >3 months, and wherein in said sample, said binder is bound to the Pro Enkephalin or one or more of said fragments at a level above 30 pmol/L.

10. The method of claim 9, wherein said binder is bound to the Pro Enkephalin or one or more of said fragments at a level of between 30 to and 80 pmol/L.

11. The method according to claim 9, wherein said binder is bound to the Pro Enkephalin or one or more of said fragments at a level above 49 pmol/L.

12. The method of claim 9, wherein said binder is bound to the Pro Enkephalin or one or more of said fragments at a level of 35 pmol/L or above.

13. The method of claim 9, wherein said binder is bound to the Pro Enkephalin or one or more of said fragments at a level of 40 pmol/L or above.

14. The method of claim 9, wherein said binder is bound to the Pro Enkephalin or one or more of said fragments at a level of 41 pmol/L or above.

Description

EXAMPLES

Example 1—Development of Antibodies

(1) Antibodies were prepared as set forth in PCT application PCT/EP2013/070470.

Example 2—PENK in Healthy Subjects

(2) 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

(3) 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.

(4) 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.

(5) 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/1) were quantified in fasting blood samples.

(6) 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.

(7) Statistical Analyses

(8) 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).

(9) Equation 1: Example Mean Change in Weight (Kg) Per Year of Follow-Up

(10) $\frac{\mathrm{weight}{\left(\mathrm{kg}\right)}_{\mathrm{follow}-\mathrm{up}\mathrm{re}-\mathrm{examination}}-\mathrm{weight}{\left(\mathrm{kg}\right)}_{\mathrm{baseline}\mathrm{examination}}}{\mathrm{follow}\text{-}\mathrm{up}\mathrm{time}\left(\mathrm{years}\right)}$

(11) 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.

(12) Cross-Sectional Analyses Between MR-PENK and Kidney Function at MDC Baseline (1991-1994)

(13) 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.

(14) TABLE-US-00003 TABLE 1 Cross-sectional relationship between tertiles of MR-PENK levels and phenotypic characteristics of Malmo 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 4252 93.33 (0.302) 89.82 (0.302) 85.20 (0.305) <0.000001 2012 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
Prospective Changes in Kidney Function at Follow-Up Re-Examination in Relation to Fasting Plasma MR-PENK Concentration at Baseline Examination

(15) 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).

(16) 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 Malmo Diet and Cancer Study Fasting plasma MR-proenkephalin concentration n Low Medium High P-trend.sup.1 N (%)  971 (33.4)  965 (33.2)  972 (33.2) 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 2601 −1.412 (0.026)  −1.412 (0.0269) −1.543 (0.026)  0.000593 CKD-EPI 2012 Incidence of 2819  233 (24.4)  298 (31.3)  422 (44.3) <0.0001 CKD (%) .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;
Prospective Analysis of the Association Between Fasting Plasma MR-PENK Levels at Baseline and CKD at Follow-Up Re-Examination

(17) 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).