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Molecular Medicine, Genetics and Development
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Genotype-Renal Function Correlation in Type 2 Autosomal Dominant Polycystic Kidney Disease

Riccardo Magistroni, Ning He, Kairong Wang, Robin Andrew, Ann Johnson, Patricia Gabow, Elizabeth Dicks, Patrick Parfrey, Roser Torra, Jose L. San-Millan, Eliecer Coto, Marjan van Dijk, Martijn Breuning, Dorien Peters, Nadja Bogdanova, Giulia Ligabue, Alberto Albertazzi, Nick Hateboer, Kyproula Demetriou, Alkis Pierides, Constantinos Deltas, Peter St. George-Hyslop, David Ravine and York Pei
JASN May 2003, 14 (5) 1164-1174; DOI: https://doi.org/10.1097/01.ASN.0000061774.90975.25
Riccardo Magistroni
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Ning He
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Kairong Wang
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Robin Andrew
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Ann Johnson
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Patricia Gabow
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Elizabeth Dicks
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Patrick Parfrey
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Roser Torra
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Jose L. San-Millan
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Eliecer Coto
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Marjan van Dijk
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Martijn Breuning
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Dorien Peters
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Nadja Bogdanova
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Giulia Ligabue
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Alberto Albertazzi
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Nick Hateboer
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Kyproula Demetriou
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Alkis Pierides
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Constantinos Deltas
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Peter St. George-Hyslop
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David Ravine
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York Pei
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Abstract

ABSTRACT. Autosomal dominant polycystic kidney disease (ADPKD) is a common Mendelian disorder that affects approximately 1 in 1000 live births. Mutations of two genes, PKD1 and PKD2, account for the disease in approximately 80 to 85% and 10 to 15% of the cases, respectively. Significant interfamilial and intrafamilial renal disease variability in ADPKD has been well documented. Locus heterogeneity is a major determinant for interfamilial disease variability (i.e., patients from PKD1-linked families have a significantly earlier onset of ESRD compared with patients from PKD2-linked families). More recently, two studies have suggested that allelic heterogeneity might influence renal disease severity. The current study examined the genotype-renal function correlation in 461 affected individuals from 71 ADPKD families with known PKD2 mutations. Fifty different mutations were identified in these families, spanning between exon 1 and 14 of PKD2. Most (94%) of these mutations were predicted to be inactivating. The renal outcomes of these patients, including the age of onset of end-stage renal disease (ESRD) and chronic renal failure (CRF; defined as creatinine clearance ≤ 50 ml/min, calculated using the Cockroft and Gault formula), were analyzed. Of all the affected individuals clinically assessed, 117 (25.4%) had ESRD, 47 (10.2%) died without ESRD, 65 (14.0%) had CRF, and 232 (50.3%) had neither CRF nor ESRD at the last follow-up. Female patients, compared with male patients, had a later mean age of onset of ESRD (76.0 [95% CI, 73.8 to 78.1] versus 68.1 [95% CI, 66.0 to 70.2] yr) and CRF (72.5 [95% CI, 70.1 to 74.9] versus 63.7 [95% CI, 61.4 to 66.0] yr). Linear regression and renal survival analyses revealed that the location of PKD2 mutations did not influence the age of onset of ESRD. However, patients with splice site mutations appeared to have milder renal disease compared with patients with other mutation types (P < 0.04 by log rank test; adjusted for the gender effect). Considerable renal disease variability was also found among affected individuals with the same PKD2 mutations. This variability can confound the determination of allelic effects and supports the notion that additional genetic and/or environmental factors may modulate the renal disease severity in ADPKD. E-mail: york.pei@uhn.on.ca

Autosomal dominant polycystic kidney disease (ADPKD [MIM 173900]) is the most common hereditary kidney disorder, with an incidence of approximately 1 in 1000 live births, and accounts for approximately 5 to 8% of end-stage renal disease (ESRD) (1,2⇓). It is characterized by the progressive formation and enlargement of renal cysts, typically leading to chronic renal failure by late middle age. Other manifestations of this disorder, such as cyst formation in non-renal organs, cardiac valvular defects, colonic diverticulosis, and intracranial arterial aneurysms, accompany the renal disease variably. Linkage studies in ADPKD families have documented genetic heterogeneity (3,4⇓), and at least two disease genes (PKD1 [MIM 601313] on chromosome 16p13.3 and PKD2 [MIM 173910] on chromosome 4q13–23) have been identified and characterized (5–7⇓⇓). A rare putative third disease gene (PKD3 [MIM 600666]) has been implicated by the identification of a small number of families unlinked to the known gene loci (8,9⇓). Mutations of PKD1 and PKD2 account for the disease in approximately 80 to 85% and approximately 10 to 15% of Caucasian ADPKD families, respectively (1,10⇓). Polycystins 1 and 2, the gene products of PKD1 and PKD2, are transmembrane proteins that share sequence homology and are currently thought to be part of a novel signaling pathway that regulates intracellular calcium (11–13⇓⇓). Polycystin 1 is predicted to have a receptor-like structure and may be involved in cell-cell and/or cell-matrix interaction (12,13⇓). In contrast, polycystin 2 shares significant homology to and can function as a cation ion channel subunit, with nonselective permeability (12–14⇓⇓). Both proteins have been shown to interact in vitro through their cytoplasmic region, with polycystin 1 likely functioning as a regulator of polycystin 2 (11–14⇓⇓⇓).

Disease progression of ADPKD is highly variable, with age at onset of ESRD ranging from childhood to old age (1). Genetic locus heterogeneity is a major determinant for interfamilial disease variability: patients from PKD1-linked families have a significantly earlier onset of ESRD or death when compared with patients from PKD2-linked families (median age: 53 [95% CI, 51.2 to 54.8] versus 69 [95% CI, 66.9 to 71.3] yr) (15). More recently, two studies have suggested that allelic heterogeneity in ADPKD might also influence renal disease severity. In the first study, patients with mutations in the 3′ half of PKD1 had milder renal disease than patients with mutations in the 5′ half of the gene (16). In the second study, patients with mutations in the 3′ half of PKD2 had milder composite scores for renal complications (i.e., presence or absence of hypertension, hematuria, renal calculi, and urinary tract infection) than patients with mutations in the 5′ half of the gene (17). However, correlation of renal function with genotype data has not been assessed in the patients with PKD2 mutations. In the current study, we report a pooled analysis of genotype-renal function correlation in 461 affected individuals from 71 ADPKD families with known PKD2 mutations.

Materials and Methods

Study Patients

The clinical and genetic data of 461 affected members from 71 ADPKD families with known germline PKD2 mutations were analyzed. The PKD2 mutations in 50 families have been previously described (17–25⇓⇓⇓⇓⇓⇓⇓⇓), and the remaining mutations from 21 families are reported here for the first time. The diagnosis of ADPKD in the patients and at-risk individuals from each study family was established using well-established ultrasound-based criteria (26). Any affected individual with a concomitant renal disease (e.g., diabetic nephropathy) was excluded from this study. The demographic, clinical, and laboratory data (including serum creatinine and/or creatinine clearance) were obtained from all the participants after obtaining informed consent. All the research protocols used in the study have been approved by the institutional review boards of all the participating centers.

Definitions of Primary Renal Outcome

Two renal disease outcomes were used in this study. End-stage renal disease (ESRD) is defined as severe chronic renal failure with a serum creatinine value ≥ 500 uM (or 5.7 mg/dl) or the requirement of renal replacement therapy (chronic dialysis or renal transplantation). Chronic renal failure (CRF) is defined as moderately severe chronic renal failure with a calculated creatinine clearance ≤ 50 ml/min per 1.73 m2 by the formula of Cockroft and Gault (27). The study subjects were classified as hypertensive if their systolic or diastolic BP exceeded the 95th percentile predicted for age and gender or if they required anti-hypertensive treatment.

PKD2 Mutational Analyses

DNA isolation and mutation screening methods have been previously detailed (17–24⇓⇓⇓⇓⇓⇓⇓). Single-stranded conformational polymorphism (SSCP), heteroduplex analysis (HA), or direct sequencing was employed to screen all 15 exons and their flanking intronic sequences of PKD2 (28) for PKD2 mutations in one definitively affected individual from each study family. Whenever possible, segregation of a specific mutation with ADPKD was tested within each family by SSCP, HA, restriction-digestion, or allele-specific oligonucleotide hybridization. All nonconservative missense changes identified were also tested to determine whether they were present in at least 100 normal chromosomes. Both strands of the PCR templates containing any variants were sequenced by the dideoxy terminator method using an ABI 373 or 377 DNA Sequencer (Applied Biosystems). PKD2 mutations were considered 5′ mutations if they were located in the first half of the open reading frame (nucleotides 1 to 1452), or 3′ mutations if they were located in the second half of the open reading frame (nucleotides 1453 to 2904). Gross deletion, nonsense, and frameshift mutations were classified as truncating mutations, and missense and splice mutations were analyzed separately.

Statistical Analyses

Time from birth to ESRD (i.e., renal death) was computed by the product-limit (i.e., Kaplan-Meier) method of survival analysis. To assess the differences in renal survival (i.e., freedom from ESRD) between specific patient groups of interest, a two-sided log-rank test was used. Additionally, time to ESRD plus death was analyzed as an additional outcome measure. The effects of the covariates (i.e., gender and hypertension) on renal survival were tested using the univariate Cox proportional hazards model or the log-rank test for continuous or categorical variables, respectively (29). Linear regression analysis was also performed to assess the influence of the position of the PKD2 mutations on the age of onset of ESRD and CRF separately. The running average of the age of onset of ESRD and CRF in Figure 2 was based on the best fitting cubic spline function of the age versus nucleotide relationship. For the linear regression and renal survival analyses, the results based on ESRD alone or ESRD plus death were not significantly different. Thus, only the results based on ESRD alone will be presented because this outcome measure provides a more accurate assignment of renal survival. All the analyses were performed using the SPSS version 11.0.1 (SPSS, Chicago, IL) and PRISM version 3.0 (GraphPad Software, Inc. San Diego, CA) statistical packages.

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Figure 2. Renal survival (i.e., absence of ESRD) analysis. The probability of renal survival differs significantly between female (n = 221) than male (n = 174) patients with PKD2 mutations (χ2 = 27.9; P < 0.00005 by log-rank test). On average, female patients developed ESRD 8 yr later than male patients with PKD2 mutations.

Results

Clinical Characteristics of Study Patients

We analyzed the clinical and genetic data of 461 affected individuals (44.2% male; 55.8% female) from 71 families in which the germline PKD2 mutations were characterized. Overall, 117 of these affected individuals (25.4%) had ESRD, 47 died without ESRD (10.2%), 65 (14.0%) had CRF, and 232 (50.3%) had neither CRF nor ESRD at the last follow-up. Although ruptured intracranial arterial aneurysm was the primary cause of death in at least seven affected individuals who died without ESRD, the cause of death was not available for the remaining 40 patients. BP information was available in 103 of 182 individuals with either ESRD or CRF, and hypertension was present in 68 (66%) of these 103 individuals. Figure 1 shows the frequency distribution of the study patents by their age of onset of ESRD, CRF, and death. Typical of type 2 ADPKD, the mode of distribution of these events occurred at a relatively late age (i.e., age range of 60 to 79 yr). However, considerable renal disease variability (e.g., age range of onset of ESRD: 40 to 88 yr) was also evident between individual patients. In general, female patients had milder renal disease than male patients (i.e., the mean age of onset of ESRD and CRF was 76.0 [95% CI, 73.8 to 78.1] versus 68.1 [95% CI, 66.0 to 70.2] and 72.5 [95% CI, 70.1 to 74.9] versus 63.7 [95% CI, 61.4 to 66.0] yr, respectively). The renal survival (i.e., absence of ESRD) curves also differed significantly between the two gender groups (Figure 2).

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Figure 1. Frequency distribution of age of onset of end-stage renal disease (ESRD), death (without ESRD), and chronic renal failure (CRF) in the study patients. Typical of type 2 ADPKD, the mode of distribution of these events occurred at a relatively late age (age range, 60 to 79 yr). However, considerable renal disease variability (age range of onset of ESRD, 40 to 88 yr) was also evident between individual patients.

Spectrum of PKD2 Mutations

Fifty different mutations from 71 families were included in the current study (Table 1). These mutations spanned the entire PKD2, with the exception of exons 3 and 15, for which no mutations have been reported thus far. Among these 71 families, 27 (38.0%) had nonsense mutations, 27 (38.0%) had frameshift mutations, 12 (16.9%) had splice site mutations, 4 (5.6%) had missense mutations, and one (1.5%) had a complete deletion of PKD2. The four missense mutations (A356P; W414G; C632R; R807Q) included in this study all involved nonconservative amino acid changes, segregated only in the affected members of the same family and were not observed in at least 100 normal chromosomes. Several mutations recurred in apparently unrelated families. Of interest, a single nucleotide deletion or insertion of a polyadenosine tract (2152–2159delA and 2152–2159insA) on exon 11 accounted for frameshift mutations in six families. Additionally, the same splice site mutation in exon 5 (i.e. IVS5+1G→A) was responsible for the mutation in three Spanish and two Canadian families. The frequencies of various clinical events (i.e., ESRD, CRF, and death) in the patients with different types of PKD2 mutations are detailed in Table 2.

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Table 1. The spectrum of PKD2 mutations in study families

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Table 2. Distribution of patients with different clinical outcomes by PKD2 mutation typesa

Genotype-Renal Function Correlation

We analyzed the correlation between the age of onset of ESRD and the nucleotide position of the PKD2 mutation in the study patients (upper panel of Figure 3). Linear regression analysis showed a correlation coefficient (r) of 0.109 (r2 = 0.012), and the slope of the regression line did not differ significantly from zero (slope value: 0.001 [95% CI, −0.001 to 0.004]). Similarly, we analyzed the correlation between the age of onset of CRF and the nucleotide position of the PKD2 mutation in the study patients (upper panel of Figure 3). Linear regression analysis showed a correlation coefficient (r) of 0.036 (i.e., r2 = 0.001), and the slope did not differ significantly from zero (slope value: −0.0004 [95% CI, −0.004 to 0.003]). These results remained unchanged when the correlation was stratified by gender. At the last follow-up, 232 study patients had not developed either CRF or ESRD and a plot of their age by the position of the PKD2 mutations is shown in the lower panel of Figure 3. Considerable renal disease variability was noted among patients with the same mutations. For example, five patients (i.e., boxed in the upper panel of Figure 3) whose mutations clustered around the nucleotide position of 1000 to 1500 of the open reading frame of PKD2, had atypically severe renal disease (i.e., ESRD before 50 yr of age). However, on close inspection they represented cases at one end of the spectrum of disease severity among patients with the same PKD2 mutations (Figure 4). In contrast, several patients, who did not have CRF even after 70 yr of age (lower panel of Figure 3), represented cases with exceptionally mild disease.

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Figure 3. Linear regression analysis of renal disease severity and nucleotide position of PKD2 mutations in the study patients. The slope of the regression line for patients with ESRD (blue square) and CRF (red diamond) did not significantly differ from zero (upper panel). Considerable disease variability was noted among patients with the same mutations. For example, five patients with four different PKD2 mutations (boxed in the upper panel) had atypically severe disease with ESRD before 50 yr of age. However, these patients represented discordant cases among patients with the same PKD2 mutation (see Figure 4). In contrast, several patients (green triangles in lower panel), who did not have CRF even after 70 yr of age, represented cases with exceptionally mild disease.

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Figure 4. Significant renal disease variability among patients with the same PKD2 mutations. Five patients (see Figure 3), whose mutations clustered around the nucleotide position of 1000 to 1500 of the open reading frame of PKD2, had atypically severe renal disease. However, they represented discordant cases among patients with the same PKD2 mutations. One or more older patients with the same mutations had mild renal disease typical of type 2 ADPKD (square denotes ESRD; diamond denotes CRF).

We also analyzed the renal survival of the study patients by the types (i.e., missense, truncating, and splice site) as well as location (i.e., 5′ or nt 1–1452 versus 3′ or nt 1453–2904) of their PKD2 mutations (Table 3; Figure 5). We found that neither the types (P = 0.26 by log-rank test; upper panel) nor the location (P = 0.78 by log-rank test; lower panel) of the PKD2 mutations influence the renal survival of our patients. Gender was a significant determinant of renal survival; we therefore also repeated the survival analyses using univariate proportional-hazards models to include gender as a covariate. In the gender-adjusted analysis, we found that patients with splice site mutations appeared to have a more favorable renal survival compared with patients with other mutation types (i.e., P = 0.046; Figure 6). On the other hand, the 5′ and 3′ location of the PKD2 mutations did not influence renal survival. Hypertension (i.e., presence or absence), included as a covariate in univariate proportional-hazards models, did not change our findings.

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Table 3. Time to ESRD or ESRD plus death by gender and mutation locationa

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Figure 5. Renal survival (i.e., absence of ESRD) of the study patients by the types (i.e., missense, truncating, or splice site mutations) and location (i.e., 5′ half versus 3′ half) of their PKD2 mutations. Neither the types (P = 0.26 by log-rank test; upper panel) nor the location (P = 0.78 by log-rank test; lower panel) of the mutations appeared to influence the renal survival of the study patients.

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Figure 6. Gender-adjusted renal survival analysis suggests a more favorable outcome in patients with splice site mutations. Univariate Cox proportionate hazards analysis with gender included as a covariate indicates that patients with splice site mutations may have a more favorable renal survival (i.e., absence of ESRD) than patients with missense and truncating mutations (P = 0.046).

Discussion

In this study, we have examined the genotype-renal function correlation in a large cohort of patients from families with known PKD2 mutations. Consistent with the published literature (3,15⇓), we found in our study patients a late age of onset of ESRD (i.e., mean age of 72 yr) and a strong gender effect on renal disease severity (i.e., P < 0.00005 by log-rank test). The mutations identified in the study families, spanning between exons 1 and 14, also covered the entire spectrum of PKD2 mutations reported to date (25). Several of these mutations are of particular interest (Table 1). For example, the four missense mutations (A356P; W414G; C632R; R807Q) included in this study all involved nonconservative amino acid changes, segregated only in the affected members of the family, and were not observed in the normal population. They are also predicted to change within the mutant polycystin 2–specific amino acids that are evolutionarily conserved between different organisms (data not shown). However, structural-functional analyses have not been performed on these mutations. Nonetheless, W414G, by virtue of its location within the polycystin domain, may disrupt the dimerization of polycystin 2 with itself and with polycystin 1 (12,14⇓). In contrast, C632R and R807Q, located in the pore region and endoplasmic reticulum retention domain, may disrupt the channel function of polycystin 2 (11,14⇓). It is also conceivable that some of these missense changes may in fact result in aberrant splicing, as recently described in another PKD2 mutation: nt A2657G (30). Of the recurring mutations, two involving an insertion or deletion of a polyadenosine tract (i.e., 2152–2159delA and 2152–2159insA) are of interest. These mutations were observed in six apparently unrelated families from different geographical regions, suggesting that the polyadenosine tract (p(A)8: nt 2152–2159) on exon 11 is a regional hot spot within PKD2 that predisposes to both germline (Table 1) and somatic mutations (31), presumably by “slipped strand mispairing” (20).

The location but not the types of PKD1 mutations has been recently reported to influence renal disease severity in a large cohort of patients with type 1 ADPKD (16). Specifically, patients with mutations localized to the 5′ half of PKD1 had an earlier onset of ESRD compared with patients with mutations localized to the 3′ half of the gene (i.e., median age of onset of ESRD: 53 versus 56 yr, respectively; P = 0.025). However, this effect is weak compared with the locus effect between PKD1 and PKD2 mutations (15). Given that most PKD1 mutations are predicted to be protein-truncating, these data have led to the suggestion that mutations in the 3′-end of this gene may result in partially functional gene products (16). In the current study, we were unable to detect a position effect in our patients by either linear regression or renal survival analyses. With a large patient sample size and adjustment for the gender effect, we believe that our analyses are robust. Most PKD2 mutations are also predicted to truncate the C′-terminus of polycystin 2; it therefore appears that the loss of the coil-coil interaction region with polycystin 1 (i.e., the most distal C′-terminal functional domain so far identified) may be sufficient to completely inactivate the mutant protein (11,12,14⇓⇓). Recent human (31–33⇓⇓) and knockout mouse (34,35⇓) studies have suggested that a common mechanism for individual cyst formation in ADPKD results from the inactivation of PKD1 or PKD2 within an epithelial cell, through germline and somatic mutations. Our data are consistent with this classical two-hit model of cystogenesis in ADPKD and suggest that most PKD2 mutations are completely inactivating.

In contrast to the lack of correlation between the mutation types and renal disease severity seen in type 1 ADPKD (16), we found that our patients with PKD2 splice site mutations appeared to have milder renal disease compared with patients with other mutation types (P = 0.046 by log-rank test; Figure 6). Among the families with the splice site mutations, one family (family 61; IVS12–7T→A; Table 1) had notably mild disease, with five elderly affected individuals developing only CRF at age 70, 71, 79, 80, and 83 yr, respectively. It is conceivable that certain splice site mutations may be “leaky,” so that low levels of a normal protein product can still be generated by the mutant allele. Should this be the case, a threshold model for polycystin 2 within individual epithelial cells of patients with such mutations may provide an additional mechanism for the cystogenic process. Under this model, individual cells with low levels of a functional polycystin may be triggered into a cystogenic pathway by local stresses and other stochastic factors (36,37⇓). Alternatively, it is possible that the above observation may be spurious, given the borderline statistical association and the presence of a significant “modifier effect” (see below).

The most definitive conclusion of our study is that significant renal disease variability exists among the patients with the same PKD2 mutations (Figures 1 and 3). Within individual families, we have observed both elderly patients with very mild renal disease and younger patients with ESRD (Figure 4). This is consistent with the finding of significant renal disease variability within families with PKD1-linkage (38) and among patients with the same PKD1 mutations (16). Taken together, these data suggest the existence of a modifier effect for ADPKD (17,38,39⇓⇓). Recent studies have shown that the phenotypic variability of a number of Mendelian disorders is in fact complex because of the existence and interaction of genetic and environmental modifiers (40). Some recent examples include cystic fibrosis (41) and Hirschsprung disease (42), in which one or more modifier loci/genes have been implicated from both animal models and patients. Indeed, several population-based studies have recently examined the polymorphic variants of the angiotensin-converting enzyme (ACE) (16,43–46⇓⇓⇓⇓) and endothelial nitric oxide synthase (eNOS) (47,48⇓) genes as modifiers of renal disease progression in ADPKD. However, these studies are limited by their research study design and small patient sample size, and they have produced conflicting results. Future studies using a family-based research design (49) and properly-powered patient sample size will be required to dissect the individual components of this modifier effect. The identification of specific genetic and environmental modifiers will have important relevance for individual patient prognostication and mechanism-based therapy in ADPKD.

Acknowledgments

We are indebted to all the participating members of the ADPKD families. Supported by grants from Polycystic Kidney Research Foundation, Canadian Institutes of Health Research (MOP53324), and Kidney Foundation of Canada (Y.P.); Department of Health and Human Services, Public Health Service, USA, and General Clinical Research Centers Program of the Division of Research Resources, National Institutes of Health, USA (A.J. and P.G.); Cyprus Kidney Association (C.D.).

Electronic Database Information

The accession number and URL for data in this article are as follows:

Online Mendelian Inheritance of Man (OMIM): http://www.ncbi. nim.nih.gov/Omim (for PKD [MIM173900]; PKD1 [MIM 601313]; PKD2 [MIM 173910]; and PKD3 [MIM 600666]).

  • © 2003 American Society of Nephrology

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Journal of the American Society of Nephrology: 14 (5)
Journal of the American Society of Nephrology
Vol. 14, Issue 5
1 May 2003
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Genotype-Renal Function Correlation in Type 2 Autosomal Dominant Polycystic Kidney Disease
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Genotype-Renal Function Correlation in Type 2 Autosomal Dominant Polycystic Kidney Disease
Riccardo Magistroni, Ning He, Kairong Wang, Robin Andrew, Ann Johnson, Patricia Gabow, Elizabeth Dicks, Patrick Parfrey, Roser Torra, Jose L. San-Millan, Eliecer Coto, Marjan van Dijk, Martijn Breuning, Dorien Peters, Nadja Bogdanova, Giulia Ligabue, Alberto Albertazzi, Nick Hateboer, Kyproula Demetriou, Alkis Pierides, Constantinos Deltas, Peter St. George-Hyslop, David Ravine, York Pei
JASN May 2003, 14 (5) 1164-1174; DOI: 10.1097/01.ASN.0000061774.90975.25

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Genotype-Renal Function Correlation in Type 2 Autosomal Dominant Polycystic Kidney Disease
Riccardo Magistroni, Ning He, Kairong Wang, Robin Andrew, Ann Johnson, Patricia Gabow, Elizabeth Dicks, Patrick Parfrey, Roser Torra, Jose L. San-Millan, Eliecer Coto, Marjan van Dijk, Martijn Breuning, Dorien Peters, Nadja Bogdanova, Giulia Ligabue, Alberto Albertazzi, Nick Hateboer, Kyproula Demetriou, Alkis Pierides, Constantinos Deltas, Peter St. George-Hyslop, David Ravine, York Pei
JASN May 2003, 14 (5) 1164-1174; DOI: 10.1097/01.ASN.0000061774.90975.25
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