| Literature DB >> 36090483 |
Jens Christian König1, Rebeka Karsay1, Joachim Gerß2, Karl-Peter Schlingmann1, Mareike Dahmer-Heath1, Anna-Katharina Telgmann1, Sabine Kollmann1, Gema Ariceta3, Valentine Gillion4, Detlef Bockenhauer5,6, Aurélia Bertholet-Thomas7, Antonio Mastrangelo8, Olivia Boyer9, Marc Lilien10, Stéphane Decramer11, Joost P Schanstra11,12, Martin Pohl13, Raphael Schild14, Stefanie Weber15, Julia Hoefele16, Jens Drube17, Metin Cetiner18, Matthias Hansen19, Julia Thumfart20, Burkhard Tönshoff21, Sandra Habbig22, Max Christoph Liebau22,23, Martin Bald24, Carsten Bergmann25,26, Petra Pennekamp1, Martin Konrad1.
Abstract
Introduction: Nephronophthisis (NPH) comprises a group of rare disorders accounting for up to 10% of end-stage kidney disease (ESKD) in children. Prediction of kidney prognosis poses a major challenge. We assessed differences in kidney survival, impact of variant type, and the association of clinical characteristics with declining kidney function.Entities:
Keywords: end-stage kidney disease; genetic variant severity; genotype-phenotype correlations; kidney survival; nephronophthisis; prognostic factors
Year: 2022 PMID: 36090483 PMCID: PMC9459005 DOI: 10.1016/j.ekir.2022.05.035
Source DB: PubMed Journal: Kidney Int Rep ISSN: 2468-0249
Figure 1Patient recruitment. Phenotypic data of 383 genetically characterized individuals was obtained from 3 independent sources: the Network of Early Onset Cystic Kidney Diseases clinical registry (n = 105), an online survey sent out to the members of the ERKNet (n = 60) and a complementary literature search (n = 218). Homogeneous data from 116 NPHP1 patients obtained from the Network of Early Onset Cystic Kidney Diseases registry (n = 80) and the online survey (n = 36) was fused for analyzes of impact of clinical factors. Gene-specific and variant-related kidney survival was analyzed including all 383 genetically characterized individuals (NPHP1: n = 116; NPHP3: n = 101; NPHP4: n = 81; NPHP11/TMEM67: n = 85) originating from the Network of Early Onset Cystic Kidney Diseases registry (n = 105), the online survey (n = 60) and a comprehensive literature search (n = 218). ERKNet, European Reference Network for Rare Kidney Diseases.
Figure 2Gene-related kidney survival. Differences in gene-related kidney survival displayed as Kaplan–Meier survival curve (a) and median age (black line)/interquartile range for the onset of ESKD in 50%, 25% and 75% of participants (b). Significant statements: NPHP1 vs. NPHP3: P < 0.0001; NPHP1 versus NPHP4: P < 0.003; NPHP1 versus NPHP11: P = 0.057; NPHP3 versus NPHP4: P < 0.0001; NPHP3 versus NPHP11: P < 0.0001; NPHP4 versus NPHP11: P = 0.539; NPHP1 versus NPHP3 vs. NPHP4 versus NPHP11: P < 0.0001. ESKD, end-stage kidney disease.
Kidney survival of genetically defined NPH cohorts
| Patient characteristics | Unsolved | ||||
|---|---|---|---|---|---|
| Total number of participants | 116 | 101 | 81 | 85 | 44 |
| Participants with ESKD (%) | 70% | 81% | 100% | 45% | 57% |
| Mean age at onset of ESKD (years/ range) | 12.5 (5.3–27.6) | 7.7 (0–47) | 17.1 (6–54) | 11.9 (0–32) | 11.1 (2.1–18.6) |
| Median age and interquartile range (IQR) for the onset of ESKD (years) | 13.5 (10.5–16.5) | 4.0 (0.25–12.0) | 16.0 (11.0–25.0) | 19.0 (8.7–28.0) | 15.4 (9.7–n.a.) |
ESKD, end-stage kidney disease; IQR, interquartile range; n.a., not assessed; NPH, nephronophthisis.
Figure 3Variant-related kidney survival. Genetic variants for NPHP3, NPHP4, and NPHP11/TMEM67 were subclassified into truncating/truncating, truncating/missense or missense/missense, defined by the presence of either 2 loss of function, 1 loss of function and 1 missense mutation or 2 missense mutations. The NPHP1 group was divided into biallelic truncating including a homozygous deletion and others. NPHP3 (n = 98) (a); NPHP4 (n = 81) (b); NPHP1 (n = 116) (c); NPHP11 (n = 85) (d).
Figure 4Cross-sectional analysis of NPHP1 patients identifying clinical factors. Multivariate cross-sectional analysis identifying clinical factors for an early onset of ESKD in patients with NPHP1 gene variations (a). Univariate cross-sectional analysis of NPHP1 patients displaying the differences in annual deltaGFR (e.g., eGFR slope = deltaGFR male - deltaGFR female) for multiple clinical characteristics: ACEI treatment and most strikingly arterial hypertension were associated with an accelerated GFR decline; however, in a multivariate approach adjusted for each characteristic, only the influence of arterial hypertension remained significant (b). ACEI, angiotensin-converting enzyme inhibitor; eGFR, estimated glomerular filtration rate; ESKD, end-stage kidney disease; HR, hazard ratio.
Clinical characteristics of NPHP1 patients at the time point when classified “hypertensive”
| Characteristics | Patients |
|---|---|
| Sex | |
| Female | 27 |
| Male | 35 |
| Age at diagnosis (yrs) | 11.2 (2.4–33.4) |
| CKD stage | |
| CKD I | 2 |
| CKD II | 1 |
| CKD III | 16 |
| CKD IV | 17 |
| CKD V | 26 |
| Average time from diagnosis hypertension to ESKD (yrs) | 1.52 (0–7.1) |
| Pre-RRT antihypertensive treatment | |
| No | 14 |
| Mono | 32 |
| Dual | 8 |
| Triple | 8 |
| Calcium antagonist | 23 |
| Beta blocker | 18 |
| ACEIs | 27 |
| Other | 4 |
ACEI, angiotensin-converting enzyme inhibitor; CKD, chronic kidney disease; EKSD, end-stage kidney disease; RRT, renal replacement therapy.
Arterial hypertension was either defined by the start of antihypertensive treatment before the onset of ESKD (n = 48) or simultaneously with the start of RRT.
Clinical characteristics of 85 NPHP1 patients with subsequent eGFR values on and off ACEI treatment.
| Patient characteristics | ACEI− | ACEI+ |
|---|---|---|
| Number of patients ( | 62 | 23 |
| DeltaGFR values ( | 125 | 47 |
| Male/female | 33/29 | 12/11 |
| Age at study entry (yrs) | 10.2 ± 3.7 (2.4–20.8) | 13.9 ± 7.9 (4.4–33.4) |
| CKD stage, | ||
| CKD1 | 3 (4) | 2 (9) |
| CKD2 | 7 (10) | 1 (4) |
| CKD3 | 26 (38) | 11 (48) |
| CKD4 | 23 (34) | 10 (43) |
| CKD5 | 9 (13) | 3 (13) |
| Absolute GFR loss/yr (ml/min per 1.73 m2cBSA) | 5.2 ± 0.6 | 7.2 ± 0.4 |
ACEI, angiotensin-converting enzyme inhibitor; BSA, body surface area; CKD, chronic kidney disease; GFR, glomerular filtration rate.
DeltaGFR values were determined for individuals with at least 2 subsequent eGFR values in intervals of minimum 3 months. This way we were able to generate 125 deltaGFR values from 62 patients without and 47 deltaGFR values from 23 patients with the influence of ACEI treatment.
Figure 5Representative eGFR trajectories from 4 patients with biallelic NPHP1 variants and temporary ACEI treatment. In all 4 cases, eGFR decline was more pronounced under the influence of ACEIs compared with no treatment-irrespective of CKD stage and age. However, no statistical significance was reached. ACEI, angiotensin-converting enzyme inhibitor; CKD, chronic kidney disease; eGFR, estimated glomerular filtration rate.