Abstract
Fabry disease is an X-linked deficiency of the lysosomal hydrolase
alpha-galactosidase A (alpha-Gal). This results in an accumulation of
globotriaosylceramide (GL-3/Gb3) in a variety of cells with subsequent
functional impairment. The continuous progress of FD often leads to
decreased quality of life and premature death caused by multi-organic
complications. The overall aim of our study was to determine the amount
of circulating miRNAs in Fabry patients and to test whether ERT would
alter the level of individual circulating miRNAs. We used miRNA
sequencing by the HTG EdgeSeq System to identify the circulating miRNA
pool from Fabry patients with and without enzyme replacement therapy
(n = 6). In total, 296 miRNAs in serum of patients were identified.
Among them 9 miRNAs were further evaluated in extra serum samples
(n = 31) using real-time qPCR and 6 of them showed significant
differential expression. The resulting miRNA pattern may help to better
understand mechanisms involved in the beneficial effects of ERT and
these new miRNA markers could help to estimate the efficacy of ERT or
to identify Fabry patients with specific need for ERT.
Subject terms: Diagnostic markers, Cardiovascular biology
Introduction
Fabry disease (FD) is an X-chromosome linked disorder caused by
mutations in gene GLA coding for alpha-galactosidase-A enzyme
(alpha-Gal). The enzyme activity deficiency that results in an
accumulation of globotriaosylceramide (GL-3/Gb3) in a variety of cells
often leads to subsequent functional impairment^[44]1. The initial
manifestations of Fabry disease usually start in adolescence stage of
life, including neuropathic pain (acroparesthesia) and abdominal
discomfort^[45]2. The continuous progress of FD results in decreased
quality of life and premature death caused by multi-organic
complications^[46]3,[47]4. As a specific treatment, Enzyme replacement
therapy (ERT) has been shown to stabilize and reduce many signs and
symptoms of Fabry disease^[48]5–[49]7. More recently, oral chaperone
therapy was shown to be also effective in selected Fabry patients
depending on the underlying gene mutation^[50]8. Of clinical importance
is the fact that early diagnosis and treatment in the disease course
may delay or prevent the progression towards irreversible organ
dysfunction and the consequent life-threatening complications. This is
sometimes difficult due to the high variability of the severity and
multi-organ system involvement in Fabry disease^[51]9. Next to the
clinical features, enzyme activity tests and DNA sequencing are
available to confirm the diagnosis^[52]10. Globotriaosylsphingosine
(LysoGb3) serves as a useful biomarker to improve the diagnosis of
heterozygous Fabry disease for therapeutic evaluation and
monitoring^[53]11. In addition, circulating serum proteins in the blood
of Fabry patients may help to get more information about the underlying
pathophysiological mechanisms^[54]12.
Recently, a group of small RNA molecules known as microRNAs (miRNAs)
have been proved to play essential roles in the cardiac
function^[55]13,[56]14. Moreover, the expression levels of miRNAs that
present in circulating fluid usually differ between healthy and
diseased patients. Although the underlying biological function and
origin of these circulating molecules remains unclear, miRNAs are
becoming potential biomarkers for early stage diagnosis and treatment
response^[57]15. The overall aim of this study was to determine the
amount of circulating miRNAs in Fabry patients and to test whether ERT
would alter the level of individual circulating miRNAs.
Materials and Methods
We used RNA sequencing technologies to identify a specific miRNA
pattern in serum of Fabry patients (Fig. [58]1). The inclusion criteria
for this study were based on a confirmed mutation within the GLA gene
and a classical or non-classical/late-onset clinical phenotype. The
diagnostic criteria for FD were based on the recent publication by
Biegstraaten et al.^[59]16: a genetically confirmed GLA mutation
leading to deficient AGAL activity combined by one or more
characteristic FD signs/symptoms, or an increase of plasma lyso-Gb3, or
an additional family member with a definite FD diagnosis. Clinical
characteristics of recruited patients were summarized in Table [60]1.
Figure 1.
[61]Figure 1
[62]Open in a new tab
Screening strategy and the global expression pattern of miRNAs in the
serum of Fabry patients. (a) Schematic strategy for identification and
validation of the deregulated miRNAs. (b) The MA-plot illustrates the
log transformed fold change (y-axis) of miRNA expression between
patients with and without ERT versus normalized expression level
(x-axis) of the 296 miRNAs detected by global screening.
Table 1.
Overview of patient groups.
Case Nr. ERT Age at visit Gender Mutation type Mutation MSSI^a score
Classical/non-classical AGAL activity^b lyso-Gb3^c (ng/ml) IVSd^d (mm)
NYHA class eGFR^e FD-related pain
Screening by RNA-seq
S1 with 50 M missense p.R112C 54 classical 5 NA 14 III 8 +
S2 with 47 M missense p.L129P 45 classical 2.5 21.2 15 I 59 +
S3 with 45 M frameshift fs 66X 62 classical NA NA 16 III Haemodialysis
+
S4 without 42 F frameshift fs 268X 3 classical 55 7.52 10 I 98
S5 without 19 M frameshift fs 268X 22 classical 10 121 14 I 132 +
S6 without 47 F missense p.W236C 16 classical 57.5 6.73 14 I 95
Validation by qPCR
P1 with 17 M splice site IVS2+1 G > A 4 classical 3 19.9 8 136 +
P2 with 22 M splice site IVS2+1 G > T 13 classical 3 31.6 7 I 126 +
P3 with 28 M splice site IVS5 +3 A > T 22 classical 24 28.4 9 I 49 +
P4 with 34 M missense p.L45P 8 classical 15 37.6 13 114 +
P5 with 39 M missense p.C94S 6 classical 9 21.5 15 I 114 +
P6 with 39 M nonsense p.W399X 37 classical 5 107 11 II 38
P7 with 40 M missense p.G325S 19 classical 23 6.7 18 I 50
P8 with 47 M missense p.D170N 21 classical 12 32.1 17 II 106 +
P9 with 49 M missense p.P259R 33 classical 22 18.6 15 I 71 +
P10 with 50 M missense p.K213M 19 classical 32 10.4 13 I 32 +
P11 with 54 M splice site IVS3 +1 G > A 51 classical 5 22.8 18 III 29 +
P12 with 57 M missense p.N215S 14 non-classical 12.5 5.4 10 II 83
P13 with 57 F frameshift fs 338× 14 classical 77.5 8 9 II 90
P14 with 62 M missense p.C172G 34 classical <1 48.7 17 IV 26 +
P15 with 64 M missense p.N215S 15 late-onset 4 3.7 14 II 96
P16 with 73 F missense p.D136E 33 classical 37.5 11.9 11 II 56
P17 with 76 F missense p.G325S 29 non-classical 57.5 9 15 III 31
P18 without 18 M missense p.M267T 10 classical 35 NA 13 130
P19 without 23 M nonsense p.Y151X 4 classical 12 197 10 125 +
P20 without 32 M missense p.L45P 23 classical <1 48.8 13 123 +
P21 without 34 M missense p.G35E 11 classical 4 45.3 10 I 112
P22 without 35 M nonsense p.W349X 21 classical 12 164 13 I 105 +
P23 without 43 M missense p.W162G 21 classical 6 33.9 20 III 77 +
P24 without 45 F missense p.D136E 13 classical 60 5.6 8 I 89
P25 without 46 M nonsense p.Y216X 25 classical 8 173 15 I 82 +
P26 without 46 F missense p.W287S 28 classical 57.5 17.4 15 I 120
P27 without 49 M missense p.W162C 22 classical 12 25.4 36 III 79
P28 without 53 M missense p.R342Q 30 classical 12 120 14 II 38 +
P29 without 56 M missense p.I242V 21 non-classical 87 0.6 20 I 117 +
P30 without 57 M missense p.L68F 41 classical 5 150 18 III 100 +
P31 without 64 M missense p.R301Q 17 classical 28 26.7 12 II 66
[63]Open in a new tab
^aThe Mainz Severity Score Index.
^bThe AGAL activities were determined from leukocytes (normal value >32
nmol MU/h/mg protein) or dried blood spots (normal value > 2.5 µ
mol/l/h), patients’ AGAL activities are expressed as % of individual
AGAL normal values.
^cThe normal level of lyso-Gb3 in this study is between 0.9–1.9 ng/ml
or lower.
^dInterventricular septal thickness at end-diastole (mm).
^eEstimated glomerular filtration rate calculated using serum
creatinine and the CKD-EPI equation.
In brief, the HTG EdgeSeq system was first utilized to identify and
quantify the expression of regulated miRNAs directly in serum of 6
Fabry patients with and without ERT. After the bioinformatic analysis
of reads data generated from the high-throughput platform, selected
miRNA candidates were further evaluated in extra 31 serum samples
(Table [64]1) from 17 patients with ERT and 14 without. Recruited
patients for this study or their parents/legal guardian have signed
informed consent before participation. The study has been approved by
the local ethical committees of the University Hospital of Münster and
the University Hospital of Würzburg therefore were performed in
accordance with the Helsinki declaration.
The HTG EdgeSeq system utilizes a novel target capture and library prep
chemistry that enables easy and fast use of next-generation sequencers
such as Illumina for transcriptome analysis including miRNAs. The
automated extraction-free chemistry of HTG EdgeSeq reduces the input
requirement of samples and eliminates biases due to RNA extraction and
library preparation. This increases the reproducibility of libraries
prepared from raw precious samples such as serum used in this study.
The raw read counts data was then generated by combined NGS sequencer
for bioinformatic analyses and the selected candidates were validated
with a miRNA-specific RT-qPCR method in extra samples as described
previously^[65]17. All experiments were performed according to
corresponding manufacturer’s protocols or instructions.
MicroRNA Sequencing and quantification
15 µl serums from each of 6 patients including 3 treated with ERT for
more than one year and 3 without ERT were incubated with HTG lysis
buffer and Proteinase K (Ambion) at 20 °C for 2 hours. The sample
plates were then loaded into an HTG Edgeseq Processor. After the
automated preparation process, library were prepared with TruSeq Small
RNA Prep kit (Illumina) according to the manufacturer’s instruction.
Single-end reads of 51 bp in length were then sequenced on an Illumina
GAIIx instrument. For expression level quantification, trimmed reads
were mapped to the genome reference (hg19) allowing one mismatch and
quantified applying Avadis NGS software (v1.4). Reads mapped to
multiple locations in the genome were removed from further
quantification. Annotation from miRBase v20 were used to designate
reference mapped reads to miRNAs.
Data normalization and differential expression analysis
A scaling factor for each sample і, is obtained for each gene g and
samples m. The scaling factor S[i], is the median gene level expression
value for each sample-gene count adjusted by the geometric mean over
all genes. Note that any genes without expression over all samples are
necessarily excluded from this scaling calculation. The formula for the
scaling factor for the i^th sample can be written as Eq. ([66]1):
[MATH:
Si=median<
/mrow>gr
gi(∏v=1mrgv)1/m :MATH]
1
Where, r[gi] is the raw count for the i^th sample and g^th gene.
The scaling factor is then used to modify the original read counts to
obtain the normalized count value
[MATH:
rgi
nor :MATH]
in Eq. ([67]2):
[MATH:
rgi
nor=<
msub>rgiSi :MATH]
2
The normalized data,
[MATH: rginor :MATH]
, can then be used for differential expression analysis. This method is
included as part of the DESeq2 package when using Bioconductor and the
R statistical package. Information about this method and the used
packages has been described earlier^[68]18,[69]19. After normalization,
unpaired t-test was performed to detect the deregulated miRNAs. To
exclude the very low/unstable expressed miRNAs in each condition, with
or without ERT treatment, any miRNA shows no expression in at least 2
samples out of 6 were removed from further analysis.
Candidate microRNAs validation via Real-Time PCR
From the RNA-seq based profiling results we selected 9 miRNAs for
validation in serum samples collected from extra 31 Fabry patients
(Table [70]1). Specifically, the serum samples were centrifuged at
2000g for 10 min at room temperature, from which the liquid supernatant
were obtained and stored at −80 °C. MiRNA were then isolated using the
miRNeasy Serum/Plasma Advanced Kit (Qiagen) followed by reverse
transcription using TaqMan^TM Advanced miRNA cDNA synthesis kit (Thermo
Fisher Scientific) according to manufacturer’s instructions. For each
serum sample, synthetic Caenorhabditis elegans miR-39 was added as a
spike-in normalizer. To quantify the synthesized cDNAs, TaqMan MicroRNA
assays were performed using ViiA7 Real-Time PCR System (Thermo Fisher
Scientific).
Statistical analysis
To analyse the RT-qPCR validation results, we used ddCT method^[71]20
to normalize and calculate the relative expression of selected
candidate miRNAs. Statistical significance between groups was then
analyzed with unpaired t-test utilizing Graphpad Prism 7.
ClustVis^[72]21 was used to perform the Hierarchical Clustering and
Principal Component Analysis (PCA) with normalized read counts data
from HTG EdgeSeq system.
Results
To identify the circulating miRNA pool from Fabry patients, 6 FD
patients and 31 FD patients were recruited as screening cohort and
validation cohort, respectively. The clinical characteristics of all
patients were summarized in Table [73]1. At the time of visit there is
no significant difference between ERT treated and ERT-naïve patients in
age (p = 0.23), IVsd (p = 0.32), MSSI score (p = 0.1) and the ratio of
mutation types (p = 0.46 by Fisher’s exact test), while the lyso-Gb3
and eGFR in ERT treated group were significantly lower than ERT-naïve
patients with p = 0.02 and p = 0.01 respectively. Among the ERT-naïve
patients visited in our study, 2 out of 3 in screening cohort, and all
14 in validation cohort were treated with ERT afterwards.
By using this innovative extraction-free HTG EdgeSeq system and
intensive bioinformatical analyses, 296 miRNAs were detected in at
least 4 out of 6 serum samples from Fabry patients (Fig. [74]1b); among
them 269 miRNAs were expressed in both conditions; 145 miRNAs were
found to be regulated more than 1.5 fold independent of p-value
(Table [75]2). In addition, the overall expression pattern of the
deregulated miRNAs decently distinguishes between the serums of Fabry
patients with and without ERT by Hierarchical Clustering and Principal
Component Analysis (Fig. [76]2).
Table 2.
Top 100 Circulating miRNAs detected by RNA-seq based screening.
miRNA ID Average expression level^a Fold change p-value^b
miR-197-5p 4344.69 25.07 0.22
miR-4739 7930.01 17.38 0.20
miR-1287-5p 1022.23 10.20 0.25
miR-4741 1580.09 9.02 0.21
miR-4633-3p 502.73 −5.57 0.16
miR-4516 10597.82 4.50 0.18
miR-7107-5p 319.39 4.26 0.01
miR-4316 38887.06 4.21 0.31
miR-3141 276.24 3.82 0.15
miR-1255b-2-3p 672.50 3.75 0.29
miR-4651 4219.61 3.69 0.26
miR-940 238.90 −3.62 0.06
miR-6084 185.83 −3.36 0.19
miR-3197 2062.72 −3.19 0.38
miR-4443 655.07 −3.15 0.45
miR-6729-5p 2790.31 −3.10 0.05
miR-19b-3p 331.55 −2.95 0.27
miR-4792 9380.74 −2.83 0.27
miR-663a 4894.42 2.82 0.04
miR-3178 4778.00 −2.81 0.27
miR-23a-3p 180.03 −2.79 0.27
miR-26a-5p 257.18 −2.42 0.30
miR-6124 447.85 2.39 0.02
miR-6891-5p 3078.59 2.35 0.33
miR-6089 8881.77 −2.34 0.45
miR-126-3p 307.41 −2.32 0.21
miR-6131 3109.86 −2.30 0.34
miR-339-3p 253.52 −2.29 0.27
miR-4638-3p 637.50 −2.26 0.29
miR-149-3p 481.19 2.24 0.28
miR-4479 209.75 −2.24 0.08
miR-6087 1160.67 2.23 0.05
miR-6510-5p 514.82 −2.21 0.13
miR-4497 8499.77 −2.20 0.24
miR-6512-3p 1196.18 −2.17 0.32
miR-548d-5p 266.18 2.16 0.38
miR-19a-3p 129.45 −2.12 0.27
miR-4469 309.30 −2.12 0.18
miR-541-3p 366.03 −2.11 0.05
miR-7158-5p 372.75 −2.10 0.32
miR-638 4809.08 −2.08 0.18
miR-21-5p 148.52 −2.07 0.19
miR-4433b-5p 957.59 −2.07 0.10
miR-6512-5p 4124.62 −2.05 0.32
miR-6727-5p 256.21 2.05 NA
miR-1973 267.03 −2.05 0.24
miR-1181 1220.70 −2.04 0.07
miR-548at-5p 822.04 −2.01 0.38
miR-1286 1237.36 −2.01 0.26
miR-4787-3p 1609.37 −2.00 0.05
miR-2277-5p 236.23 −2.00 0.25
miR-4634 394.67 −1.98 0.09
miR-3151-3p 331.77 −1.97 0.29
miR-1273c 162.68 1.96 0.23
miR-486-5p 331.51 −1.94 0.39
miR-1245a 561.57 −1.94 0.38
miR-223-3p 407.46 −1.93 0.36
miR-4285 431.48 −1.93 0.09
miR-6789-5p 170.97 −1.93 NA
miR-152-5p 512.10 −1.91 0.11
miR-6732-3p 198.95 −1.91 0.05
miR-4534 169.87 1.90 NA
miR-210-3p 125.42 −1.90 0.10
let-7a-5p 175.29 −1.90 0.27
miR-6798-3p 1147.64 −1.89 0.08
miR-548at-3p 641.72 −1.87 0.34
miR-6746-3p 297.65 −1.87 0.25
miR-582-3p 396.36 −1.86 0.35
miR-6876-5p 181.81 −1.84 NA
miR-7855-5p 1164.79 −1.83 0.10
miR-6796-3p 295.95 −1.83 0.08
miR-185-5p 181.51 −1.82 0.20
miR-8072 569.10 1.81 0.06
miR-6730-3p 394.81 −1.81 0.34
miR-764 1195.93 −1.80 0.09
miR-1273h-5p 3464.16 1.80 0.27
miR-92a-3p 412.94 −1.80 0.37
miR-148a-5p 3475.90 −1.79 0.32
miR-561-3p 327.03 −1.79 0.26
miR-1307-3p 2669.88 −1.79 0.11
miR-4461 118.37 −1.79 NA
miR-6085 156.10 −1.79 0.10
miR-4284 374.30 −1.78 0.27
miR-6836-3p 789.31 −1.78 0.07
miR-3960 63948.48 −1.78 0.48
miR-8073 11211.83 −1.77 0.12
miR-8075 1564.40 −1.77 0.12
miR-4784 346.98 −1.76 0.12
miR-6870-3p 1492.88 −1.76 0.17
miR-326 341.75 −1.76 0.12
miR-7847-3p 270.00 1.75 0.05
miR-6077 1161.12 −1.75 0.25
miR-1273a 149.86 1.75 0.19
miR-4271 487.17 1.75 0.30
miR-762 999.82 −1.74 0.53
miR-6790-3p 257.52 −1.74 0.14
miR-1307-5p 247.21 −1.74 0.04
miR-6727-3p 188.30 −1.74 0.53
miR-1251-5p 244.22 −1.74 0.10
miR-8064 8581.74 −1.73 0.17
[77]Open in a new tab
^aAverage value of normalized miRNA read counts.
^bp-values were calculated by unpaired two tailed t-test. NA: not
available.
Figure 2.
[78]Figure 2
[79]Open in a new tab
The overall expression pattern of regulated miRNAs. (a) Heatmap
illustrates the differentially expressed miRNAs in serums of Fabry
patients with and without ERT. Rows (expression level of miRNAs) and
columns (serum samples) are clustered using correlation distance and
average linkage. (b) PCA plot of the miRNA expression data indicates
the distance between serum samples. X and Y axis show principal
component 1 and principal component 2 that explain 56.5% and 18.6% of
the total variance, respectively. Each dot in the plot represents one
of the six samples used for sequencing based screening.
Of interest many miRNAs were detected by the high-throughput approach
for which no clear role in biology or pathophysiology has been
described yet. However, some miRNAs were already known in the
literature. For instance, overexpression of miR-541 promote vascular
smooth muscle proliferation and invasion suggesting that lower miR-541
levels might be beneficial in various vascular and pulmonary
diseases^[80]22. Specific inhibition/silencing of miR-21 have been
proved to be able to effectively prevent the myocardial and renal
fibrosis^[81]14,[82]23. The miR-17-92 family that comprises miR-17,
miR-18a, miR-19a, miR-19b-1, miR-20a, and miR-92a-1 has been implicated
in the promotion of cell proliferation and the growth of renal
cysts^[83]24. Reduced levels of miR-26a were observed to be correlated
with kidney injury in renal vascular disease and the restored
expression could attenuate interstitial fibrosis and tubular apoptosis
hence rescuing the renal function^[84]25.
Taken together with the differential expression evidence from our
sequencing-based profiling results and the published data of
characterized miRNAs, we selected 9 candidate miRNAs (miR-1307-5p,
miR-541-3p, miR-4787-3p, miR-21-5p, miR-152-5p, miR-19a-3p, miR-19b-3p,
miR-26a-5p, and miR-486-5p) from the top 100 deregulated miRNAs
(Table [85]2) to perform RT-qPCR with serum samples in a validation
cohort (n = 31; 17 with ERT and 14 without). As results, 4 miRNAs,
miR-1307-5p, miR-21-5p, miR-152-5p and miR-26a-5p were found to be
significantly (p < 0.05) down-regulated in the serum of Fabry patient
after ERT (Fig. [86]3). MiR-19a-3p and miR-486-5p were also decreased
but not significantly.
Figure 3.
[87]Figure 3
[88]Open in a new tab
Validation of miRNA candidates in serum of Fabry patients. Illustration
of the relative expression of miRNA candidates validated in serum
samples of Fabry patients by RT-qPCR. Data from female patients and
male patients are presented by triangles and squares, respectively.
*p < 0.05.
Since Fabry disease is an X-chromosome linked genetic disorder that
affects male patients more severely than female, we made an additional
analysis to compare the expression level of candidate miRNAs in 26
serums of male patients (14 with ERT and 12 without). Of interest two
additional miRNAs, miR-19a-3p and miR-486-5p were found to be
significantly (p < 0.05) down-regulated in male patients with ERT
(Fig. [89]4). These findings are consistent with the facts that female
Fabry patients demonstrate more variable symptoms with a wider range of
disease severity^[90]26 and suggest that a gender specific
miRNA-expression pattern is necessary to develop the optimal markers
for female and male patients, respectively.
Figure 4.
[91]Figure 4
[92]Open in a new tab
Validation of miRNA candidates in serum of male Fabry patients.
Illustration of the relative expression of miRNA candidates validated
in serum samples of male Fabry patients by RT-qPCR. *p < 0.05.
Discussion
Although efficacy and clinical effects of ERT in patients with Fabry
disease have been investigated and reported^[93]5–[94]8, less is known
about the mechanism and effect on the molecular level. In this study we
performed a direct comparison of the miRNA expression pattern between
patients with and without ERT that provide novel ideas to unravel the
pathway underlying ERT.
To elucidate the putative underlying molecular mechanisms,
mirPath^[95]27 was utilized to make pathway enrichment analysis based
on top 100 deregulated miRNAs. Of interest, axon guidance and TGF-beta
signaling pathways were found to be targeted by the miRNAs
(Fig. [96]5). Although improvement of small nerve fibre function with
decreased neuropathic pain has been reported in FD patient with
ERT^[97]28, the pathogenesis of the peripheral neuropathy correlated
with Fabry disease is poorly understood. The predicted functional
changes in axon guidance molecules caused by dysregulated miRNAs could
affect the neural circuits developments that result in neurological
symptoms in FD patients.
Figure 5.
Figure 5
[98]Open in a new tab
Pathway analysis of the deregulated miRNAs. Significant targeted KEGG
pathways identified by top 100 deregulated miRNAs. X-axis indicates the
log transformed p-value (significant level) between miRNAs and each
pathway.
Renal impairment is often observed in later stage of Fabry disease,
which advances to kidney failure causes significant mortality in FD
patients. Improvement and slowing of the renal disease progression have
been reported after ERT treatment^[99]29. More recently, proteomic
studies demonstrated that VEGF receptor-2 in plasma of patients was
significantly higher than controls and decreased after ERT^[100]12;
increased expression TGF-β1 and VEGF were found to be associated with
the renal pathogenesis of Fabry mouse model^[101]30. These findings
suggest a putative function of TGF-β signaling pathway involved in
nephropathy of Fabry disease, which is in general consist with our
result from pathway enrichment analysis.
On the other hand, evaluation of the circulating miRNAs as biomarkers
have been performed either in the field of kidney disease or Fabry
disease. The concentration of circulating miRNAs in plasma including
miR-21 and miR-210 were found to be reduced in patients with chronic
renal failure, while no correlation was observed between urinary miRNAs
and kidney function^[102]31. In a recent case study of a young Fabry
patient without nephropathy manifestations, the expression level of
miR-29 and miR-200 were found to be decreased in urinary sediment while
the other TGF-β related miRNAs not^[103]32. Taken together, although
TGF-β signalling pathway was suggested to be associated with Fabry
nephropathy^[104]12,[105]28, there is no direct evidence to support the
putative involvement of TGF-β regulated miRNAs in ERT treatment.
In our study, a non-biased approach based on high-throughput sequencing
were applied instead of knowledge based candidates selection. Although
some known TGF-β related miRNAs e.g. miR-29, miR-192 and miR-200 were
excluded from further validation due to the extremely low abundance in
screening result, our result from pathway enrichment analysis still
successfully predicted many miRNAs including miR-21-5p and miR-19a-3p
that involved in the TGF-β signalling pathway. Although there were only
6 samples used in the screening step, we have proved the expression
changes of miRNA candidates in additional 31 serums. The whole strategy
applied in this study is based on a robust but unbiased approach from
the technique to the data analysis.
However, the small size of studied population, selection bias (males
and females with variable Fabry phenotypes), and the fact that
circulating miRNAs from serum could come from various cell types and
tissues are obvious limitations of this study. As the objects in this
study are diagnosed Fabry patients, and our major aim is to identify
miRNA pattern that involved in the beneficial effects of ERT, healthy
control group were not included. Future studies including healthy
controls could help to increase the specificity of our results to Fabry
disease.
In conclusion, the resulting miRNA pattern together with the validated
miRNAs are expected to improve the understanding of the mechanisms
involved in the beneficial effects of ERT or potentially to identify
Fabry patients with specific need for ERT. Further studies are needed
in greater patient cohorts and proper controls.
Author contributions
K.X. analysed the results. D.L., L.S., S.G., A.P. and S.T. conducted
the experiments. J.H., M.L., E.B. and P.N. prepared serum samples. T.T.
conceived the idea. All authors have reviewed the manuscript.
Data availability
All data analysed during this study are included in this article. The
datasets generated during the study are available on reasonable
request.
Competing interests
The study was partly sponsored by Sanofi/Genzyme. The authors declare
no competing interests.
Footnotes
Publisher’s note Springer Nature remains neutral with regard to
jurisdictional claims in published maps and institutional affiliations.
References