Globotriaosylceramide concentrations were assessed as potential predictors of change from baseline after 12 months by estimated glomerular filtration rate and left-ventricular mass index using pooled data from three randomized, placebo-controlled agalsidase alfa trials and open-label extensions of patients with Fabry disease.
Males (aged 18 years or older) with Fabry disease received agalsidase alfa (0.2 mg/kg every other week for 12 months). A backward-elimination approach evaluated potential predictors (baseline estimated glomerular filtration rate and left-ventricular mass index; age at first dose; baseline and change from baseline at 12 months of globotriaosylceramide (urine, plasma); urine protein excretion; and systolic and diastolic blood pressure). Subgroups included patients randomized to placebo or agalsidase alfa (double-blind phase), then to agalsidase alfa (open-label extensions; placeboagalsidase alfa or agalsidase alfaagalsidase alfa, respectively) and stage 2/3 chronic kidney disease patients.
Baseline estimated glomerular filtration rate, age at first dose, baseline urine globotriaosylceramide excretion, and baseline and change from baseline urine protein excretion significantly predicted change from baseline estimated glomerular filtration rate in the analysis population (N = 73; all P<0.05), although not in all subgroups. Change from baseline urine and plasma globotriaosylceramide (baseline and change from baseline) concentrations did not predict change from baseline estimated glomerular filtration rate. No predictors of left-ventricular mass index were significant.
Changes in globotriaosylceramide concentrations do not appear to be useful biomarkers for prediction of Fabry disease–related changes in estimated glomerular filtration rate or left-ventricular mass index.
Genet Med 15 12, 983–989.
agalsidase alfa; biomarkers; enzyme replacement therapy; Fabry disease; globotriaosylceramide
Globotriaosylceramide (Gb3) is often elevated in the urine of patients with Fabry disease,1 and some studies support its use as a diagnostic biomarker.2,3,4 Plasma Gb3 concentration has been found to be consistently elevated in hemizygous males with classic Fabry disease but variably elevated in some variant hemizygous males with residual enzyme activity and in heterozygous females.5,6 No evidence has been published supporting the use of plasma or urine Gb3 concentrations as a biomarker for disease progression or response to treatment. For patients with elevated plasma or urine Gb3 concentrations before treatment, enzyme replacement therapy (ERT) results in an initial drop in Gb3 concentrations.5,7 The lower Gb3 concentrations do not remain low in all patients and do not always coincide with clinical improvement.8
The goal of this study was to assess the relationship of plasma and urine Gb3 concentrations with renal or cardiac outcome measures. A previous analysis of pooled data from three randomized, placebo-controlled clinical trials and their open-label extensions (sponsored by Shire Human Genetic Therapies) of male patients with Fabry disease suggested a stabilizing effect of agalsidase alfa (agalα) on renal function assessed by measured glomerular filtration rate (GFR).11 In that analysis, baseline GFR or elevated proteinuria category (≥1 g/24 h) significantly predicted GFR decline during treatment. Using a suitable selection approach of pooled data from the same three clinical trials, we asked whether Gb3 concentrations could also be a predictor of changes in kidney function and/or left-ventricular mass index (LVMI) in a large study population of patients with Fabry disease receiving agalα ERT.
Materials and Methods
Clinical trial designs and treatments
Data were pooled from three 24-week, randomized, double-blind, placebo-controlled trials (RCTs) and their open-label extension studies (EXTs; TKT003/TKT006; TKT005/TKT007; TKT010/TKT013; and TKT015). Two of these trials (TKT003 and extension12 and TKT005 and extension)13 were single-center phase II trials, and one was a multicenter phase III trial (TKT010 and extension).
Treatments in these trials included agalα (0.2 mg/kg body weight) infused intravenously over a 40-min period every other week or placebo (infused on the same schedule). For these analyses, patient data were analyzed for 12 months of total agalα treatment (Figure 1). Patients were either treated with agalα for 6 months (RCTs), followed by an additional 6 months of agalα (EXTs), or they received placebo for 6 months (RCTs) and then transitioned to 12 months of agalα (EXTs).
Patients were adult males (aged 18 years or older) with Fabry disease (OMIM 301500) confirmed by clinical characteristics and alpha-galactosidase A deficiency, who were otherwise considered to have adequate general health. Each individual RCT also had specific inclusion criteria, including symptoms of neuropathic pain (TKT003, TKT010), medication for neuropathic pain at screening (TKT010), and left-ventricular hypertrophy (TKT005). None of these trials had specific renal inclusion criteria.
For inclusion in these post hoc analyses, patients in the renal analysis population were required to have available data on estimated GFR (eGFR),14 plasma Gb3 concentration, urine Gb3 excretion, urine protein excretion, systolic and diastolic blood pressure, and age at baseline and 12 months of agalα treatment. The cardiac analysis population must have had cardiac magnetic resonance imaging measurements for LVMI. All patients should have received at least one dose of agalα during the treatment period assessed. In addition, subpopulations were evaluated comprising patients who were initially randomized to the placebo group in the 6-month RCTs and transitioned to 12 months of agalα in the EXTs (placeboagalα; Figure 1), who were initially randomized to agalα (6-month RCTs) and continued on to 6 months of agalα during the EXTs (agalαagalα; Figure 1), or who had stage 2/3 chronic kidney disease (CKD 2/3) at baseline (defined as patients with baseline eGFR of 30−90 ml/min/1.73 m2).
All studies included in these analyses were approved by the appropriate institutional review boards of the investigators’ institutions, and all patients provided written informed consent.
Measurement of eGFR and LVMI
These analyses use eGFR instead of measured GFR because eGFR allows for the inclusion of more patients in the analysis population. eGFR (ml/min/1.73 m2) was calculated using the Chronic Kidney Disease Epidemiology Collaboration equation,14 which incorporates serum creatinine (SCr [mg/dl]), the patient’s age, sex, and race. κ Corresponds to a value of 0.7 (females) or 0.9 (males), and α is –0.329 (females) or –0.411 (males). The “min” value indicates the minimum of SCr/κ or 1, and “max” is the maximum of SCr/κ or 1. The Chronic Kidney Disease Epidemiology Collaboration formula can be expressed as a single equation as follows:
SCr was measured in local laboratories as part of the standard assessments. A local clinical laboratory quantitatively determined 24-h urine protein excretion. Renal disease was staged into CKD subgroups.15 LVMI was calculated using cardiac magnetic resonance imaging measurements and using techniques described previously.13
Measurement of Gb3 concentration
Plasma samples were collected for assessment of Gb3 after 8 h of fasting before drawing the blood for analyses. Urine Gb3 excretion was evaluated in 24-h urine sediment. Both plasma and urine samples were analyzed with high-performance liquid chromatography using a validated assay, as described previously.16
In the renal analysis population, the primary outcome measure was the change from baseline (CFB) value in eGFR at 12 months. The potential predictors considered for renal outcomes included baseline (before agalα treatment) eGFR and age at start of agalα, as well as baseline and CFB (at month 12) plasma Gb3 concentrations, urine Gb3 excretion, natural log (ln) of urine protein excretion, and systolic and diastolic blood pressure. In the cardiac analysis population, the same potential predictors (except baseline eGFR) as well as baseline LVMI were evaluated for CFB in LVMI (g/m2.7) at month 12. Interaction effects were also evaluated as described below.
The significance of potential predictors of renal outcomes was assessed via a backward-elimination linear regression model, which started with the full model, including interaction terms, and systematically and sequentially factored out all nonsignificant potential explanatory variables one by one, starting with the least significant variable. Nonsignificant (P > 0.05) interaction terms were removed initially, followed by the removal of nonsignificant (P > 0.05) main effects that were not a component of a statistically significant interaction term. Because the starting model contains interaction terms, the elimination process did not permit the removal of a main effect term before all interactions related to that main effect were removed. The elimination model was terminated when all remaining main effect terms were either significant or part of a significant interaction term (Pelimination > 0.05). The backward-elimination approach was chosen because it selects models that are more explanatory. A similar approach was used for the cardiac outcomes, with the exception of inclusion of interaction terms due to small sample size. The robustness of the model was also assessed using a linear regression analysis in the three patient subpopulations: placeboagalα, agalαagalα, and CKD 2/3 subgroups. A Student’s t-test was used to calculate P values, assessing whether parameters (intercepts and slopes) were significantly different from zero. Statistical significance levels were set at α = 0.05 (two-sided).
Baseline demographic and clinical characteristics are shown in Table 1. These characteristics were similar among the entire renal analysis population and the placeboagalα and agalαagalα subgroups. Patients in the CKD 2/3 subgroup had lower baseline eGFR than the whole analysis population and other subpopulations, as expected from the criteria for defining CKD 2/3 (baseline eGFR of 30−90 ml/min/1.73 m2).
Baseline and CFB values at month 12 are shown for each of the parameters evaluated as a potential predictor of renal function (Table 2). The backward-elimination approach identified baseline eGFR, age at start of agalα, baseline urine Gb3 excretion, log-transformed baseline, and CFB of urine protein excretion at month 12 as significant predictors of renal function in the renal analysis population (all P < 0.05; Table 3). Furthermore, significant interactions were found between baseline eGFR and log-transformed baseline and CFB in urine protein excretion at month 12 (both P < 0.005; Table 3). No other variables assessed were significant predictors of renal function. Most of these potential parameters and interactions were found to be statistically significant predictors of renal function in the placeboagalα subgroup (all P < 0.05), with the exception of age at start of agalα (P = 0.0571; Table 4). Patients in the agalαagalα subgroup retained only baseline eGFR and log-transformed baseline urine protein excretion as potential predictors (both P < 0.05), with a significant interaction found between these two parameters (P = 0.0153; Table 4). For CKD 2/3 patients, only urine Gb3 was determined to be a significant predictor of CFB eGFR at month 12 (P = 0.0105; Table 4).
The backward-elimination approach did not identify any predictors of CFB LVMI at month 12 (Supplementary Table S1 online).
A large unmet need exists for finding and validating accurate biomarkers in lysosomal storage disorders and, in particular, for Fabry disease.17,18 Individual lysosomal diseases exhibit great variability in clinical expression that contributes to the current inability to predict their rate of progression, severity, and response to therapy, which underscores the need for biomarkers.19 A biomarker is defined as a laboratory measurement that reflects the activity of a disease process. Urine or plasma Gb3 concentrations have been used as biomarkers for diagnostic purposes and to follow the effect of specific therapies such as ERT.1,2 In addition, the measurement of plasma Gb3 concentration was used as a pharmacodynamic marker to demonstrate the biological activity of agalα in vivo.20 For patients with elevated plasma or urine Gb3 concentrations before treatment, ERT resulted in an initial drop in Gb3 concentrations.7,8 Lower Gb3 concentrations did not always coincide with clinical improvement.
In this post hoc analysis of prospective RCTs of agalα ERT in Fabry disease, plasma Gb3 concentration was not found to be a significant predictor at month 12 of CFB eGFR (for renal function) or CFB LVMI (for cardiac structure) in the analysis population or any subgroup. Urine Gb3 excretion also failed to predict CFB LVMI at month 12. However, baseline urine Gb3 excretion did appear to be a predictor of change in renal function, but when analyzed by subgroup, urine Gb3 excretion did not consistently correlate with disease stage, progression, or response to ERT (e.g., baseline urine Gb3 excretion predicted renal function in the placeboagalα and CKD 2/3 subgroups but not in the agalαagalα subgroup). CFB of urine Gb3 excretion at month 12, however, was not found to be a predictor of renal function, suggesting that change in Gb3 concentrations during the course of therapy would not be a good biomarker for response to therapy or Fabry disease progression. Urine protein excretion (baseline and CFB at month 12) was retained in the model as a predictor of renal function in the overall renal analysis population, with statistically significant interaction effects detected with baseline eGFR. In addition, baseline urine protein excretion predicted renal function in the placeboagalα and agalαagalα subgroups, and CFB in urine protein excretion at month 12 was found to be a predictor in the placeboagalα subgroup.
Currently available published evidence does not support the use of plasma or urine Gb3 concentrations as predictive biomarkers for disease progression in patients with Fabry disease. For example, in a cross-sectional analysis in a population of 96 Dutch patients with Fabry disease, concentrations of Gb3 in plasma and urine did not correlate with any clinical symptoms assessed, including renal dysfunction.8 The findings of the present analyses are consistent with these studies. Although baseline urine Gb3 excretion was found to be a significant predictor, this may have been of a reflection of baseline Fabry disease severity before agalα treatment initiation; e.g., patients with more severe Fabry disease at baseline may have experienced worse disease outcomes than patients with less progressed Fabry disease before treatment. To assess formally whether plasma and urine Gb3 concentrations would be predictive biomarkers over the longer term for the clinical outcome in the natural history of Fabry disease, a longitudinal study in untreated subjects would be necessary.
The present study has several limitations. Because three trials were analyzed, the pooled patient population was heterogeneous because of differences in inclusion/exclusion criteria. These trials were not designed to evaluate renal function as a primary end point. The primary end point of one trial (TKT010) was changed from neuropathic pain to renal function after 15 months. The original inclusion criteria of this trial, however, were not modified to coincide with this change. In addition, study subjects with Fabry disease were not required to have abnormal baseline eGFR and LVMI, which might leave them at lower risk of developing progressive kidney disease or cardiac deterioration during the course of these relatively short-term studies. Although a few significant predictors of renal function were found in the overall analysis population (e.g., baseline eGFR, age at start of agalα, baseline urine Gb3 excretion, baseline and CFB at month 12 in urine protein excretion), further research is needed to determine if the lack of statistically significant differences in these same predictors in the subgroups were due to any specific characteristic(s) of these subgroups or were attributable to the patient number being too small to detect an effect. One indication that the patient numbers may have been insufficient in the subgroups is that only the renal analysis population and the placeboagalα subgroup retained CFB at month 12 in urine protein excretion as a statistically significant predictor. Furthermore, a backward-elimination regression model is not a hypothesis-driven model; nevertheless, we consider it the best choice for these exploratory post hoc analyses; however, the follow-up period on ERT was relatively short, so additional analyses may be needed to assess long-term effects. Finally, although some studies support globotriaosylsphingosine as a potentially useful biomarker for monitoring Fabry disease, this evidence has been generated in relatively recent years.6,21,22 At the time of the design of the clinical trials included in the current report, globotriaosylsphingosine was not considered a potential surrogate marker of Fabry disease progression or response to treatment and, thus, was not included as a measured end point.
The biological reason why changes in plasma or urine Gb3 concentrations are not useful as biomarkers is not clear. Blood and urine Gb3 concentrations are not mechanistically directly related to the outcome measures used in the current study; urine Gb3 excretion is mostly derived from the renal collecting system, whereas the outcome (eGFR) reflects glomerular function. Likewise, changes in plasma Gb3 do not necessarily represent its turnover in the heart muscle. Because renal function in most patients was not in the rapidly declining stage, the possibility exists that significant reduction in urine or plasma Gb3 concentrations could not be reflected in changes in eGFR over a relatively short period of 12 months. Another possible explanation for our findings is that Gb3 concentrations may not participate in the pathogenic process of renal glomerulopathy or hypertrophic cardiomyopathy of Fabry disease. Therefore, Gb3 may be an example of a biomarker that is not entirely in the causal pathway of the disease process.23
In conclusion, the lack of correlation between CFB at month 12 of urine and plasma Gb3 concentrations and renal outcomes suggests that changes in their levels do not predict clinical progression in Fabry disease; however, the discordant baseline urine Gb3 excretion results in the subgroup analyses raises some question as to whether such a relationship exists and requires additional study. Other molecules, for example, globotriaosylsphingosine or reactive oxygen species, may also likely be active participants in the Fabry pathogenic cascade in the kidney and the heart.21,24,25
R.S. has received honoraria and research support from Shire Human Genetic Therapies (HGT), Amicus Therapeutics, and Genzyme. K.N. has served on the Fabry Outcomes Survey advisory board that is funded by Shire HGT and has received travel and research support from Shire HGT, Genzyme, and Amicus; her center participates in clinical trials funded by Shire HGT and Amicus. A.M. has received research support and speaking honoraria from Shire HGT, Genzyme, and Actelion. J.T.R.C. has received research funding, consultancy fees, and/or speaker fees from Shire HGT, Genzyme, and Actelion. R.D.S. has participated in clinical trials funded by TKT/Shire HGT, Actelion, Genzyme, Protalix/Pfizer, and BioMarin. He has had research support from TKT and has received speaking or consulting fees from TKT/Shire HGT, Amicus, Actelion, Genzyme, Zacharon, and BioMarin. M.B. has received unrestricted grants, honoraria, and travel support from Shire HGT, Genzyme, BioMarin, and Actelion. B.A.B. has received research support from Genzyme and has served on an advisory board for BioMarin. W.R. has received research funding, consultancy fees, and/or speaker fees from Shire HGT, Genzyme, Hyperion, Ucyclyd, and Actelion and has served on advisory boards for Shire HGT. M.W. has received research support from Shire HGT and Genzyme; has received speaking honoraria from Shire HGT, Genzyme, Amicus Therapeutics, and Sumitomo Pharma; and has participated in advisory boards for Shire HGT. M.R. was an employee of Shire HGT from 2006 to 2009; he has served on advisory boards for Alexion, GSK, and Amicus and has received consultancy honoraria from Alexion, Oxyrane, and Shire HGT. P.H. was an employee of Shire HGT from 2008 to 2011. R.M. and N.N are employees of Shire HGT. D.A. was an employee of Shire HGT from 2010 to 2012. D.B. declares no potential competing interests.
- Urinary lipid profiling for the identification of Fabry hemizygotes and heterozygotes. Clin Chem 2005;51:688–694. , , , et al.
- Development of a filter paper method potentially applicable to mass and high-risk urinary screenings for Fabry disease. J Inherit Metab Dis 2007;30:106. , , , , .
- Urinary globotriaosylceramide excretion correlates with the genotype in children and adults with Fabry disease. Mol Genet Metab 2008;93:331–340. , , , et al.
- Proposed high-risk screening protocol for Fabry disease in patients with renal and vascular disease. J Inherit Metab Dis 2009;32:303–308. , , , , .
- Is globotriaosylceramide a useful biomarker in Fabry disease? Acta Paediatr Suppl 2005;94:51–4; discussion 37. , , , et al.
- Plasma globotriaosylsphingosine as a biomarker of Fabry disease. Mol Genet Metab 2010;100:257–261. , , , et al.
- Long-term therapy with agalsidase alfa for Fabry disease: safety and effects on renal function in a home infusion setting. Nephrol Dial Transplant 2006;21:345–354. , , , , .
- The Dutch Fabry cohort: diversity of clinical manifestations and Gb3 levels. J Inherit Metab Dis 2007;30:68–78. , , , et al.
- Biomarkers and surrogate markers: an FDA perspective. NeuroRx 2004;1:189–195. .
- Guidance for Industry - qualification process for drug development tools. http://www.fda.gov/downloads/Drugs/
GuidanceComplianceRegulatoryInformation/Guidances/UCM230597.pdf. Accessed 21 November 2012.
- Agalsidase alfa and kidney dysfunction in Fabry disease. J Am Soc Nephrol 2009;20:1132–1139. , , , et al.
- Enzyme replacement therapy in Fabry disease: a randomized controlled trial. JAMA 2001;285:2743–2749. , , , et al.
- Effects of enzyme replacement therapy on the cardiomyopathy of Anderson-Fabry disease: a randomised, double-blind, placebo-controlled clinical trial of agalsidase alfa. Heart 2008;94:153–158. , , , et al.
- A new equation to estimate glomerular filtration rate. Ann Intern Med 2009;150:604–612. , , , et al.; .
- K/DOQI clinical practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Am J Kidney Dis 2002;39:S1–S266. .
- Infusion of alpha-galactosidase A reduces tissue globotriaosylceramide storage in patients with Fabry disease. Proc Natl Acad Sci USA 2000;97:365–370. , , , et al.
- Biomarkers in the diagnosis of lysosomal storage disorders: proteins, lipids, and inhibodies. J Inherit Metab Dis 2011;34:605–619. , , , et al.
- Biomarkers in lysosomal storage diseases. In: , , (eds). Fabry Disease: Perspectives From 5 Years of FOS. Oxford PharmaGenesis: Oxford, England, 2006. .
- Treatment perspectives for the lysosomal storage diseases. Expert Opin Emerg Drugs 2008;13:197–211. .
- Enzyme replacement in Fabry disease: pharmacokinetics and pharmacodynamics of agalsidase alpha in children and adolescents. J Clin Pharmacol 2007;47:1222–1230. , , , et al.
- Elevated globotriaosylsphingosine is a hallmark of Fabry disease. Proc Natl Acad Sci USA 2008;105:2812–2817. , , , et al.
- Plasma globotriaosylsphingosine: diagnostic value and relation to clinical manifestations of Fabry disease. Biochim Biophys Acta 2010;1802:741–748. , , , et al.
- Surrogate end points in clinical trials: are we being misled? Ann Intern Med 1996;125:605–613. , .
- How well does urinary lyso-Gb3 function as a biomarker in Fabry disease? Clin Chim Acta 2010;411:1906–1914. , , , et al.
- Globotriaosylceramide induces oxidative stress and up-regulates cell adhesion molecule expression in Fabry disease endothelial cells. Mol Genet Metab 2008;95:163–168. , , , et al.
These studies and analyses were funded by Shire Human Genetic Therapies (HGT). Medical writing support for this article was provided by Ray Beck of UBC-Envision Group and was funded by Shire HGT.