Online Appendix
PRECISION MEDICINE IN PATIENTS WITH RESISTANT
HYPERTENSION AND OBSTRUCTIVE SLEEP APNEA: BLOOD
PRESSURE RESPONSE TO CPAP TREATMENT
Manuel Sánchez-de-la-Torre PhD1,2; Abdelnaby Khalyfa PhD3,4; Alicia Sánchez-de-la-Torre BSc1,2;
Montserrat Martinez-Alonso PhD1,2; Miguel Ángel Martinez-García MD5,2; Antonia Barceló MD6,2;
Patricia Lloberes MD7,2; Francisco Campos-Rodriguez MD8; Francisco Capote MD9,2; Maria José Diazde-Atauri MD10; Maria Somoza MD11; Mónica González12,2, MD; Juan-Fernando Masa13,2, MD; David
Gozal3, MD; and Ferran Barbé1,2, MD, on behalf of the Spanish Sleep Network
1.- Methods
1.1. miRNA PCR Array for Cardiovascular Disease
1.2. miRNA Detection in Plasma
1.3.-Plasma Levels of Peptides Related to Cardiovascular Function
1.4. -Enrichment pathway analysis and target gene prediction
2.- Results
2.1 Analysis of Non-linear Relationships of Plasma Levels of Peptides and Hormones
Related to Cardiovascular Function with Blood Pressure Response to Adherent Use of
CPAP
2.2.- HIPARCO-Score Behavior in Women
2.3. Complementary Analysis of Unsupervised Hierarchical Clustering of miRNA
Microarrays
3. Discussion
3.1- Biological Relevance of Differentially Expressed miRNAs in Favorable Blood
Pressure Responders to Adherent Use of CPAP
4.- References
1
1. Methods
1.1 miRNA Extraction from Plasma
Total RNA, including miRNA, was isolated from plasma using an miRNeasy Mini Kit columnbased system according to the manufacturer’s instructions (Qiagen, Turnberry Lane, Valencia,
CA, USA). Venous blood samples were obtained from patients between 8:00 am and 10:00 am
after fasting overnight. The blood was centrifuged, and the plasma was immediately separated
into aliquots and stored at -80ºC until analysis. Plasma was thawed on ice and centrifuged at
3000 x g for 5 min at 4°C in a microcentrifuge. Briefly, for each sample, an aliquot of 200 μl of
plasma was transferred to a new microcentrifuge tube, and 1000 μl of QIAzol reagent
containing 3.5 µL of synthetic C. elegans miRNAs cel-miR-39 (spike-ins) was added to all
samples to normalize possible sample-to-sample variation caused by RNA isolation. The
column was dried for 5 min after the last washing step before elution. Total RNA was eluted by
adding 14 μL of DNase-RNase-free water to the membrane of the spin column and incubating
for 1 min before centrifugation at 15000 x g for 1 min at room temperature.
1.2.-miRNA Detection in Plasma
miRNA arrays (84 mature miRNAs) (Qiagen, Turnberry Lane) that were pathway-specific for
the human cardiovascular system were analyzed in age-, gender-, ethnicity-, BMI score- and
participant center-matched OSA patients with resistant hypertension (RH). The analysis was
performed for 8 patients with the best blood pressure responses to CPAP and 8 patients with the
worst responses to screen for the initial selection of miRNAs. Each of the arrays contained a
specific set of selected cardiovascular disease-related miRNAs based on published studies. A
set of 12 miRNAs controls on the array (96-well plates) enabled data analysis using the CT
method of relative quantification, assessment of reverse transcription performance, and
assessment of PCR performance using SYBR Green real-time PCR. In this assay, a pool of 84
candidate human miRNAs, two C. elegans miRNAs, six housekeeping miRNAs (five SNORDs
2
and one RNU), two reverse transcription controls and two positive PCR controls were assessed.
A similar PCR assay was used for the 5 patients from the screening groups with the best and
worst mean blood pressure level changes to evaluate the effect of CPAP adherent treatment on
the miRNA profiles.
Quantitative real time RT-PCR (qRT-PCR) analyses were performed using an ABI 7500
system (Applied Biosystems, Foster City, CA). cDNA synthesis was performed using a
miScript SYBR Green PCR Kit as described in the manufacturer’s protocols (Qiagen,
Turnberry Lane). Ten nanograms (10 ng) of total RNA including miRNAs from the samples,
were used to generate cDNA templates for RT-PCR. The miScript SYBR Green PCR Kit
(Qiagen, Turnberry Lane, Valencia, CA, USA) was used to amplify and quantify each miRNA
of interest in 25-l reactions in 96-well plates. The following steps were involved in the
reaction program: an initial step of 15 min at 95°C, denaturation at 94°C for 15 sec, and 40
cycles of denaturation (15 seconds at 94°C), annealing (35 seconds at 55°C) and elongation (35
seconds at 70°C). The expression values were obtained from the cycle number value using
Biosystems analysis software. The threshold cycle (CT) values were averaged from each
reaction, and each miRNA was normalized to the average of the housekeeping miRNAs on the
arrays. The endogenous normalizer SNORD95 exhibited relatively stable expression across the
responder and non-responder patient samples. The miScript miRNA PCR Array Data Analysis
Web Portal (http://pcrdataanalysis.sabiosciences.com/mirna/arrayanalysis.php) was used to
analyze the microarray data. The cut-off Ct values selected for miRNA expression were
detectable if the Ct value was <35 or undetectable if the Ct value was >35. The relative
expression of the gene of interest was analyzed using the 2-CT method (1).
3
1.3.-Plasma Levels of Peptides Related to Cardiovascular Function
Fasting blood samples were drawn by venipuncture in the morning after the sleep study. Blood
samples were immediately centrifuged and frozen at -80°C until use in assays. Aldosterone and
renin levels were measured by chemiluminescence, and the aldosterone-to-renin ratio was
calculated (ratios higher than the cutoff of 1.2 indicate hyperaldosteronism). MRP 8/14 and
adropin levels were measured using commercial enzyme-linked immunosorbent assay kits.
Plasma levels of aldosterone and renin were measured by chemiluminescence on an iSYS
(Immunodiagnostic Systems-iSYS, Boldon, United Kingdom) automated analyzer. The
aldosterone and renin assays had sensitivities of 3.7 ng/dl and 1.8 uUI/ml, respectively. The
inter-assay and intra-assay coefficients of variation were 7.2% and 2.6%, respectively, for
aldosterone and 6.6% and 4.4%, respectively, for renin. The plasma levels of adropin and MRP
8/14 were measured using commercial enzyme-linked immunosorbent assay kits (for MRP
8/14, ALPCO Diagnostics, Salem, NH; for adropin, Peninsula Laboratories, Bachem, San
Carlos, CA). The MRP 8/14 and adropin assays had sensitivities of 0.4 μg/ml and 0.25 ng/ml,
respectively. The inter-assay and intra-assay coefficients of variation for MRP 8/14 were 5.8%
and 4.3%, respectively. For adropin, the intra-assay coefficient of variation (CV) determined
using quality control human plasma samples with adropin values of 0.5-5 ng/ml was 10.4%,
and the inter-assay CV was 22%.
1.4. -Enrichment pathway analysis and target gene prediction
The web-based computational tool DIANA-mirPath v2.1(25) was used to predict the target
genes and altered pathways of the differentially expressed miRNAs. The software performs an
enrichment analysis of multiple miRNA target genes by comparing each set of miRNA targets
to all known KEGG pathways (Kyoto Encyclopedia of Genes and Genomes). The pathways
exhibiting a false discovery rate adjusted p-value of <0.05 were considered significantly
enriched between the compared classes.
4
2. Results
2.1 Analysis of Non-linear Relationships of Plasma Levels of Peptides and Hormones
Related to Cardiovascular Function with Blood Pressure Response to Adherent Use of
CPAP
The analysis of non-linear relationships between BP responses and adherent CPAP use revealed
a significant relationship with post-CPAP renin levels higher than 14.7 uUI/ml, with an odds
ratio of treatment response of 7.3 and a significant relationship with a change (pre- minus postCPAP) in the aldosterone-to-renin ratio of more than -0.13, with an odds ratio of treatment
response of 9.8 (Table E12). A complementary analysis to identify the changes in mean blood
pressure most significantly related with plasma levels of peptides and hormones revealed
significant relationships between 1) a change in mean blood pressure above 12.5 mmHg and
both aldosterone at baseline (low in responders group) and the change in aldosterone
(increasing in responders group), 2) a change in mean blood pressure >10 mmHg and postCPAP renin levels (high in the responders group), 3) a change in mean blood pressure >0.5
mmHg and the change in MRP8/14 (increased in the responders group), and 4) a change in
mean blood pressure >3 mmHg and the change in the aldosterone-to-renin ratio (decreased in
the responders group) (Table E13).
2.2.- HIPARCO-Score Behavior in Women
We evaluated the behavior of the HIPARCO-Score in 14 women with OSA and RH and
adherent use of CPAP treatment who were recruited for the HIPARCO study (NCT00616265).
Model M3, which was used for HIPARCO-Score definition, showed poor calibration (with
Hosmer-Lemeshow test p-value=0.0138) and poor discrimination (with AUC of 0.55, 95% CI:
[0.13, 0.92]) when the model was applied to women. Given the sex differences observed, the
model to predict response to CPAP was limited to men.
5
2.3. Complementary Analysis of Unsupervised Hierarchical miRNA Microarray
Clustering
We performed an additional unsupervised hierarchical clustering of the human cardiovascular
system pathway-specific miRNA arrays, including miRNAs with less than 50% missing values
(68 mature miRNAs). It was evaluated from samples from OSA patients with RH with
favorable (responders) and unfavorable (non-responders) blood pressure responses to adherent
use of CPAP (Online Figure 2). The first cluster included patients with mean blood pressure
changes (pre-CPAP treatment value minus the post-CPAP treatment value) ranging from -9 to
13.5 mmHg. The second cluster included patients with mean blood pressure changes ranging
from 17 to 22 mmHg. The results of this unsupervised analysis suggest that the most significant
effect of CPAP treatment on miRNA profiles occurs for those patients with greater decreases in
mean blood pressure.
3. Discussion
3.1- Biological Relevance of Differentially Expressed miRNAs in Favorable Blood
Pressure Responders to Adherent Use of CPAP.
The miRNAs that were differentially expressed at baseline between the favorable blood
pressure responders and non-responders are known to exhibit altered expression during
cardiovascular disease and development. The expression of miR-7-5p inhibits vascular
endothelial cell proliferation (2), which has relevant implications for endothelial function and
repair capabilities. Endothelial dysfunction occurs in OSA patients and has been identified as
an important intermediate mechanism linking OSA consequences with cardiovascular diseases
(3). The downregulation of this miR-7-5p may involve the overexpression of the RAF1 gene
and, consequently, dilated cardiomyopathy (4). The downregulation of miR-92a-3p prevents
6
endothelial dysfunction in mice (5) and does not inhibit bone morphogenetic protein receptor
(BMPR) genes that should be activated in the heart remodeling process after infarction (6).
Conversely, upregulated miR-100-5p inhibits BMPR genes (6). These responses are signals of
BMPR dysregulation, a hallmark of pulmonary hypertension (7). The upregulation of miR-1443p accelerates plaque formation by impairing reverse cholesterol transport and promoting proinflammatory cytokine production (8). miR-150-5p may participate in B-cell activation and
differentiation processes affecting several systems, including the heart and its functions (9). In
addition, miR-150-5p is dysregulated in myocardial infarction (9, 10). miR-378a-3p is
downregulated in myotonic dystrophy type 2 (11), cardiac hypertrophy and cardiomyopathy
and also participates in some differentiation processes, such as enhancing adipogenesis (12).
Finally, miR-486-5p is related to erythropoiesis (13) and systemic ventricular myocardial
acceleration during isovolumetric contraction (14).
7
Table 1. Between-group comparison at baseline in the training set.
Sex, male, n(%)
Age, years
Stroke, n(%)
Coronary heart disease, n(%)
Peripheral arterial disease, n(%)
Diabetes, n(%)
Dyslipidemia, n(%)
Tobacco use, pack-year
BMI, kg·m-2
Neck perimeter, cm
Apnea-hypopnea index, event/h
TSat90
Epworth sleep scale score
CPAP mean use, h/day
24-h mean blood pressure, mm Hg
SBP, mmHg
DBP, mmHg
Nocturnal blood pressure pattern, n(%)
Dipper
Non-dipper
Riser
Years since diagnosis of resistant
hypertension
No. of systemic hypertension drugs
Calcium channel blockers, n(%)
Angiotensin II receptor blockers, n(%)
β-Blockers, n(%)
Angiotensin-converting enzyme
inhibitor, n(%)
α1-Blockers, n(%)
Renin blockers, n(%)
Type of diuretic, n(%)
None
Thiazides/Xipamide no loop diuretics
Loop diuretics without Thiazides
Potassium sparing/Anti-aldosterone
Thiazides & loop diuretics
Non-responders
(n=12)
12 (100)
63 [55;66.2]
1 (8.33)
4 (33.3)
0 (0)
5 (41.7)
9 (75)
15 [0;30.5]
31.5 [30.1;34]
43 [42;46]
34.5 [26;41.8]
6 [3.5;10.2]
8 [6.75;11.2]
5.5 [4.5;6.12]
113 [107;114]
142 [136;147]
80.5 [74.8;84.5]
Responders
(n=12)
12 (100)
55 [50;63]
1 (8.33)
2 (16.7)
2 (16.7)
6 (50)
9 (75)
0 [0;0]
32.1 [30.5;37.9]
43.5 [41.8;46]
45 [29.5;52.2]
7 [1.75;30.2]
8 [5.00;12]
5.5 [5.00;6.12]
116 [111;119]
146 [137;150]
88.5 [83.8;94.8]
3 (25)
6 (50)
3 (25)
12.5 [12;23]
5 (41.7)
5 (41.7)
2 (16.7)
9 [4;13.5]
0.041
3 [3;4]
8 (66.7)
9 (75)
5 (41.7)
3.5 [3;4]
7 (58.3)
9 (75)
6 (50)
1
1
1
1
4 (33.3)
4 (33.3)
2 (16.7)
2 (16.7)
4 (33.3)
1 (8.33)
0.64
1
1
0.384
2 (16.7)
5 (41.7)
4 (33.3)
0 (0)
1 (8.33)
0 (0)
9 (75)
2 (16.7)
0 (0)
1 (8.33)
p-value
1
0.09
1
0.64
0.478
1
1
0.09
0.43
0.77
0.4
0.43
0.66
0.97
0.21
0.52
0.06
0.76
Qualitative variables are described by frequencies and percentages. Quantitative variables are described by
medians and interquartile ranges. Non-parametric tests (the Mann-Whitney test and Fisher’s exact test were used
for comparability assessments). Abbreviations: BMI, body mass index (calculated as weight in kilograms divided
by height in meters squared); DBP, diastolic blood pressure; SBP, systolic blood pressure; TSat 90, nighttime spent
with an oxygen saturation below 90%.
8
Table 2. Between-group comparison at baseline in the validation set.
Non-responders
Responders
(n=6)
(n=8)
Sex, male, n(%)
6 (100)
8 (100)
Age, years
55.5 [49.8;62]
52.5 [51;60]
Stroke, n(%)
0 (0)
1 (12.5)
Coronary heart disease, n(%)
0 (0)
1 (12.5)
Peripheral arterial disease, n(%)
1 (16.7)
0 (0)
Diabetes, n(%)
2 (33.3)
3 (37.5)
Dyslipidemia, n(%)
2 (33.3)
4 (50)
Tobacco use, pack-year
0 [0;0]
14 [0;39.8]
BMI, kg·m-2
32.3 [30.7;34.5]
33.3 [31.2;36.4]
Neck perimeter, cm
42 [42.0;42.2]
45 [42.0;46.0]
Apnea-hypopnea index, event/h
35.5 [21.2;60.2]
56 [49.5;62.8]
TSat90
6 [0;18.8]
18 [6;22]
Epworth sleep scale score
12 [9;14.5]
8 [5;9]
CPAP mean use, h/day
5 [4;5.5]
5.54 [3;7]
24-h mean blood pressure, mm Hg
111 [104;115]
120 [111;122]
142 [136;153]
149 [141;152]
SBP, mmHg
DBP, mmHg
83.5 [73.8;90.2]
88 [82.5;93.2]
Nocturnal blood pressure pattern, n(%)
Dipper
1 (16.7)
2 (25)
Non-dipper
3 (50)
4 (50)
Riser
2 (33.3)
2 (25)
Years since diagnosis of resistant
8.00 [6.5;15]
12.5 [7.00;17.5]
hypertension
No. of systemic hypertension drugs
3 [3;3]
3.50 [3.00;4.25]
Calcium channel blockers, n(%)
2 (33.3%)
8 (100)
Angiotensin II receptor blockers, n(%)
4 (66.7%)
2 (25)
β-Blockers, n(%)
4 (66.7%)
7 (87.5)
Angiotensin-converting enzyme
inhibitor, n(%)
1 (16.7%)
3 (37.5)
α1-Blockers, n(%)
1 (16.7%)
1 (12.5)
Renin blockers, n(%)
0 (0%)
0 (0)
Type of diuretic, n(%)
None
0 (0.0%)
0 ( 0)
Thiazides/Xipamide no loop diuretics
2 (33.3%)
2 (25)
Loop diuretics without Thiazides
4 (66.7%)
5 (62.5)
Potassium sparing/Anti-aldosterone
0 (0.0%)
0 (0)
Thiazides & loop diuretics
0 (0.00%)
1 (12.5)
p-value
1
0.89
1
1
0.43
1
0.62
0.22
0.77
0.37
0.33
0.38
0.17
0.94
0.19
0.74
0.27
1
0.85
0.052
0.015
0.27
0.53
0.58
1
NA
1
Qualitative variables are described by frequencies and percentages. Quantitative variables are described by
medians and interquartile ranges. Non-parametric tests (the Mann-Whitney test and Fisher’s exact test were used
for comparability assessments). Abbreviations: BMI, body mass index (calculated as weight in kilograms divided
by height in meters squared); DBP, diastolic blood pressure; SBP, systolic blood pressure; TSat 90, nighttime spent
with an oxygen saturation below 90%; NA, not assessable.
9
Table 3. Interassay reproducibility assessment of miRNA expression.
miRNA
miR-144-3p
miR-100-5p
miR-29a-3p
miR-150-5p
miR-7-5p
miR-378a-3p
miR-92a-3p
miR-486-5p
ICC
0.646
0.384
0.043
0.671
0.948
0.453
0.823
0.831
p-value
0.002
0.048
0.25
0.002
<0.001
0.05
<0.001
<0.001
Two-way intraclass correlation coefficients (ICC) between the 84 miRNA array and the individual miRNA
expression assessment of the 8 miRNA candidates to distinguish responders from non-responders. High values of
ICC indicate good reproducibility (from 0 to 1).
Table 4. Univariate logistic regression analysis of the study sample (n=38).
dCt(miR-378a-3p)<2.6
dCt(miR-486-5p)>-7.1
dCt(miR-100-5p)≤ 0.4
Univariate logistic regression
Estimate
OR
p-value
2.86(1.14)
17.5
0.012
1.31(0.69)
3.7
0.056
1.23(0.69)
3.4
0.076
OR, odds ratio. dCt was normalized by SNORD95 as dCt = Ct(miRNA) – Ct(SNORD95). Because higher Ct
values are indicative of lower expression levels, a low dCt value indicates high miRNA expression, whereas a high
dCt indicates low miRNA expression.
Table 5. Evaluation of the contribution of miR-100-5p to reclassification into responder and
non-responder groups.
Model with miR-100-5p
Non-responders
Responders
Initial Model [0,0.333) [0.333,0.667) [0.667,1] [0,
[0.333,0.667) [0.667,1]
0.333)
[0,0.333)
7
0
0
1
0
0
[0.333,0.667) 0
2
1
0
2
2
[0.667,1]
0
0
1
0
0
6
NRI (categorical) 0.09, (95% CI, -0.19 - 0.37), with a p-value of 0.53; NRI (continuous) 0.72 (95% CI, 0.04 - 1.5),
with a p-value of 0.06.
10
Table 6. Effect of continuous positive airway pressure on sleep and anthropometry.
Before CPAP
After CPAP
Paired p-value
-2
BMI, kg·m
32.1 [30.5;35.6]
33.0 [30.3;35.1]
0.39
24-h mean blood pressure,
114.0 [108.3;118.0]
109.5 [103.3;113.6]
0.0005
mmHg
SPB, mmHg
145.0 [137.3;152.0]
137.5 [130;146.5]
0.008
DBP, mmHg
85.0 [77.3;92.0]
80.0 [74.3;84.8]
0.001
Epworth sleep scale score
8.0 [5.8;12.0]
4.5 [3;6]
<0.0001
Number of antihypertensive
3.0 [3.0;4.0]
3 [3;4]
1
drugs
Nocturnal blood pressure dipper 11 (28.9)
14 (36.8)
0.5
pattern, n(%)
Nocturnal blood pressure riser
9 (23.7)
10 (26.3)
1
pattern, n(%)
Median and interquartile ranges are shown for pre and post-treatment with CPAP patient characteristics. The Wilcoxon test
for paired comparisons on quantitative variables was applied, and its p-value is shown. For changes in the percentages of
dipper or riser patterns, the McNemar test p-value is calculated. Abbreviations: CPAP, continuous positive airway pressure;
BMI, body mass index (calculated as weight in kilograms divided by height in meters squared); DBP, diastolic blood
pressure; IQR, interquartile range; SBP, systolic blood pressure; TSat90, nighttime spent with an oxygen saturation below
90%; NA, not assessable.
Table 7. Differences in change (post-continuous positive airway pressure (CPAP) minus PreCPAP) in the expression of cardiovascular system-focused miRNAs in favorable blood pressure
responders vs. non-responders to adherent use of CPAP.
let-7a-5p
let-7b-5p
let-7c
let-7d-5p
let-7e-5p
let-7f-5p
miR-100-5p
miR-103a-3p
miR-107
miR-10b-5p
miR-122-5p
miR-124-3p
miR-125a-5p
miR-125b-5p
miR-126-3p
miR-130a-3p
miR-140-5p
miR-142-3p
miR-143-3p
miR-144-3p
miR-145-5p
miR-146a-5p
DddCt [95%CI]
2-ΔddCt [95%CI]
p-value
2.97 [1.97, 3.93]
2.65 [0.32, 4.89]
1.66 [0.40, 3.19]
3.42 [1.84, 4.83]
2.88 [1.25, 4.16]
2.28 [1.56, 3.71]
3.65 [1.38, 6.53]
3.00 [0.03, 6.23]
2.46 [NE]
1.64 [-1.61, 6.31]
1.91 [-1.05, 4.59]
3.90 [-2.89, 9.24]
2.87 [1.57, 6.12]
1.29 [-2.47, 3.99]
2.33 [0.86, 4.40]
2.22 [0.78, 4.54]
4.18 [-1.17, 10.81]
2.70 [0.77, 4.80]
1.43 [-0.61, 4.32]
1.29 [0.00, 2.36]
2.51 [0.55, 4.93]
3.42 [1.09, 6.21]
0.13 [0.07, 0.25]
0.16 [0.03, 0.80]
0.32 [0.11, 0.76]
0.09 [0.04, 0.28]
0.14 [0.06, 0.42]
0.21 [0.08, 0.34]
0.08 [0.01, 0.38]
0.12 [0.01, 0.98]
0.18 [NE]
0.32 [0.01, 3.05]
0.27 [0.04, 2.07]
0.07 [0.00, 7.40]
0.14 [0.01, 0.34]
0.41 [0.06, 5.54]
0.20 [0.05, 0.55]
0.21 [0.04, 0.58]
0.06 [0.00, 2.25]
0.15 [0.04, 0.59]
0.37 [0.05, 1.53]
0.41 [0.20, 1.00]
0.18 [0.03, 0.68]
0.09 [0.01, 0.47]
0.0079
0.0159
0.0317
0.0079
0.0159
0.0079
0.0079
0.0317
1.0000
0.2286
0.3095
0.4206
0.0079
0.6905
0.0079
0.0159
0.2286
0.0079
0.1143
0.0556
0.0317
0.0079
11
Adjusted
p-value
0.0192
0.0283
0.0492
0.0192
0.0283
0.0192
0.0192
0.0492
1.0000
0.2828
0.3766
0.4724
0.0192
0.7305
0.0192
0.0283
0.2828
0.0192
0.1605
0.0846
0.0492
0.0192
miR-150-5p
miR-155-5p
miR-15b-5p
miR-16-5p
miR-17-5p
miR-181a-5p
miR-181b-5p
miR-183-5p
miR-185-5p
miR-18b-5p
miR-195-5p
miR-199a-5p
miR-21-5p
miR-210
miR-214-3p
miR-22-3p
miR-221-3p
miR-222-3p
miR-223-3p
miR-224-5p
miR-23a-3p
miR-23b-3p
miR-24-3p
miR-25-3p
miR-26a-5p
miR-26b-5p
miR-27a-3p
miR-27b-3p
miR-29a-3p
miR-29b-3p
miR-29c-3p
miR-30a-5p
miR-30c-5p
miR-30d-5p
miR-30e-5p
miR-31-5p
miR-320a
miR-328
miR-342-3p
miR-365b-3p
miR-378a-3p
miR-423-3p
miR-424-5p
miR-451a
miR-486-5p
miR-494
DddCt [95%CI]
2-ΔddCt [95%CI]
p-value
1.84 [0.53, 4.18]
4.32 [NE]
2.25 [1.17, 4.25]
1.98 [0.40, 3.56]
2.53 [1.03, 4.31]
1.32 [-0.40, 3.54]
2.69 [0.35, 5.10]
3.95 [NE]
2.49 [0.35, 4.43]
3.75 [0.01, 7.44]
2.20 [0.55, 3.54]
1.34 [NE]
2.64 [0.93, 4.77]
-0.09 [-1.54, 5.43]
0.73 [NE]
1.76 [0.19, 4.84]
2.99 [1.47, 5.47]
2.15 [-0.37, 4.13]
3.76 [2.23, 5.90]
4.17 [NE]
2.55 [0.98, 4.78]
2.88 [0.90, 6.29]
2.70 [0.99, 4.86]
2.11 [0.50, 3.65]
3.07 [1.28, 5.44]
2.73 [1.59, 4.77]
2.59 [1.61, 5.25]
3.23 [0.59, 5.90]
2.54 [0.48, 4.27]
2.04 [0.15, 4.14]
1.94 [0.57, 4.27]
3.12 [1.56, 4.46]
2.78 [0.52, 5.60]
2.73 [1.00, 4.54]
2.18 [1.27, 3.65]
2.15 [NE]
2.38 [0.75, 4.79]
-1.73 [-5.64, 6.03]
2.07 [0.64, 3.83]
3.53 [NE]
1.09 [-12.93, 5.91]
1.82 [-0.12, 3.71]
0.98 [-1.95, 3.06]
2.30 [0.72, 3.45]
2.83 [0.67, 5.44]
4.21 [-3.56, 7.24]
0.28 [0.06, 0.69]
0.05 [NE]
0.21 [0.05, 0.45]
0.25 [0.09, 0.76]
0.17 [0.05, 0.49]
0.40 [0.09, 1.32]
0.16 [0.03, 0.79]
0.06 [NE]
0.18 [0.05, 0.79]
0.07 [0.01, 0.99]
0.22 [0.09, 0.69]
0.39 [NE]
0.16 [0.04, 0.52]
1.06 [0.02, 2.91]
0.60 [NE]
0.30 [0.03, 0.88]
0.13 [0.02, 0.36]
0.22 [0.06, 1.29]
0.07 [0.02, 0.21]
0.06 [NE]
0.17 [0.04, 0.51]
0.14 [0.01, 0.54]
0.15 [0.03, 0.50]
0.23 [0.08, 0.71]
0.12 [0.02, 0.41]
0.15 [0.04, 0.33]
0.17 [0.03, 0.33]
0.11 [0.02, 0.66]
0.17 [0.05, 0.72]
0.24 [0.06, 0.90]
0.26 [0.05, 0.67]
0.11 [0.05, 0.34]
0.15 [0.02, 0.70]
0.15 [0.04, 0.50]
0.22 [0.08, 0.41]
0.23 [NE]
0.19 [0.04, 0.59]
3.31 [0.02, 49.96]
0.24 [0.07, 0.64]
0.09 [NE]
0.47 [0.02, 7801.31]
0.28 [0.08, 1.08]
0.51 [0.12, 3.86]
0.20 [0.09, 0.61]
0.14 [0.02, 0.63]
0.05 [0.01, 11.78]
0.0159
0.2000
0.0079
0.0159
0.0079
0.1508
0.0317
1.0000
0.0079
0.0286
0.0159
0.2000
0.0159
1.0000
1.0000
0.0159
0.0079
0.0952
0.0079
0.4000
0.0079
0.0079
0.0079
0.0079
0.0079
0.0079
0.0079
0.0159
0.0079
0.0317
0.0079
0.0079
0.0159
0.0079
0.0079
0.5000
0.0079
0.5476
0.0079
0.1000
0.4206
0.0952
0.4206
0.0079
0.0159
0.1429
12
Adjusted
p-value
0.0283
0.2607
0.0192
0.0283
0.0192
0.2039
0.0492
1.0000
0.0192
0.0492
0.0283
0.2607
0.0283
1.0000
1.0000
0.0283
0.0192
0.1390
0.0192
0.4710
0.0192
0.0192
0.0192
0.0192
0.0192
0.0192
0.0192
0.0283
0.0192
0.0492
0.0192
0.0192
0.0283
0.0192
0.0192
0.5530
0.0192
0.5966
0.0192
0.1431
0.4724
0.1390
0.4724
0.0192
0.0283
0.1968
miR-7-5p
miR-92a-3p
miR-93-5p
miR-98-5p
miR-99a-5p
DddCt [95%CI]
2-ΔddCt [95%CI]
p-value
1.37 [-0.14, 3.58]
2.27 [0.64, 4.44]
2.49 [1.08, 4.06]
3.96 [NE]
1.06 [-4.08, 7.43]
0.39 [0.08, 1.10]
0.21 [0.05, 0.64]
0.18 [0.06, 0.47]
0.06 [NE]
0.48 [0.01, 16.95]
0.2286
0.0079
0.0079
0.3333
0.6857
Adjusted
p-value
0.2828
0.0192
0.0192
0.3989
0.7305
Comparison of ddCt (dCt Post CPAP– dCt Pre CPAP) in responders and non-responders defined as (ΔddCt =
ddCt[responders] – ddCt[non-responders]) (Mann-Whitney U test). The ΔddCt column shows the median of the
differences between the change in the miRNA dCt value in the responders minus the change in the miRNA dCt
value in the non-responders. Positive values of ΔddCt (or 2^-ΔddCt < 1) are indicative of a significantly higher
decrease in miRNA expression in responders vs. non-responders. A negative ΔddCt (or 2-ΔddCt > 1) indicates a
significantly higher increase in miRNA expression in responders vs. non-responders. NE indicates that the
nonparametric 95% confidence interval was not achievable. False discovery rate adjusted p-values are shown in the
last column.
Table 8: Pathways identified as significantly enriched for miRNAs differentially expressed
at baseline between patients with OSA and resistant hypertension with favorable and
unfavorable blood pressure response to adherent use of continuous positive airway
pressure treatment.
KEGG pathway
KEGG Category
p-value
mTOR signaling pathway
Wnt signaling pathway
Neurotrophin signaling pathway
Focal adhesion
ErbB signaling pathway
Glioma
PI3K-Akt signaling pathway
Prostate cancer
Melanoma
Glycosaminoglycan biosynthesis - heparan
sulfate / heparin
Long-term potentiation
Endometrial cancer
Regulation of actin cytoskeleton
Dopaminergic synapse
Phosphatidylinositol signaling system
Transcriptional misregulation in cancer
Pathways in cancer
Ubiquitin mediated proteolysis
Insulin signaling pathway
Endocrine and other factor-regulated
calcium reabsorption
Valine. leucine and isoleucine biosynthesis
Fatty acid metabolism
Type II diabetes mellitus
Signal transduction
Signal transduction
Nervous system
Cellular community
Signal transduction
Cancers
Signal transduction
Cancers
Cancers
Glycan biosynthesis and metabolism
1.1*10-10
2.64*10-8
3.27*10-8
3.65*10-8
3.43*10-7
6.08*10-7
2.60*10-6
2.76*10-6
3.29*10-5
Nervous system
Cancers
Cell motility
Nervous system
Signal transduction
Cancers
Cancers
Signal transduction
Endocrine system
Excretory system
Amino acid metabolism
Metabolism
Endocrine and metabolic diseases
13
6.28*10-5
0.0001
0.0001
0.0002
0.0002
0.0004
0.0004
0.0005
0.0008
0.0012
0.0012
0.0029
0.0033
0.0036
(continuation of Table 8)
KEGG pathway
Melanogenesis
Colorectal cancer
Basal cell carcinoma
Non-small cell lung cancer
Small cell lung cancer
GnRH signaling pathway
HIF-1 signaling pathway
Acute myeloid leukemia
Pancreatic cancer
Pancreatic secretion
Cholinergic synapse
Glutamatergic synapse
RNA transport
Inositol phosphate metabolism
Gap junction
MAPK signaling pathway
Endocytosis
Amoebiasis
Aldosterone-regulated sodium reabsorption
KEGG Category
p-value
Endocrine system
Cancers
Cancers
Cancers
Cancers
Endocrine system
Signal transduction
Cancers
Cancers
Digestive system
Nervous system
Nervous system
Translation
Carbohydrate metabolism
Gap junction
Signal transduction
Transport and catabolism
Infectious diseases: Parasitic
Excretory system
0.0043
0.0045
0.0046
0.0052
0.0057
0.0074
0.0094
0.0108
0.0115
0.0153
0.0155
0.0196
0.0212
0.0247
0.0271
0.0311
0.043
0.0441
0.0481
DIANA-miRPath v2.1 settings: MicroT threshold: 0.8. p-value threshold: 0.05. Significantly enriched pathways
sorted by p-value.
14
Table 9. Pathways identified as significantly enriched for the miRNAs that changed
significantly after adherent use of continuous positive airway pressure treatment (CPAP)
in favorable blood pressure responders vs. non-responders to CPAP.
KEGG pathway
KEGG Category
p-value
Fatty acid biosynthesis
Protein digestion and absorption
Glycosaminoglycan biosynthesis chondroitin sulfate
ECM-receptor interaction
Amoebiasis
Axon guidance
Melanoma
Glioma
ErbB signaling pathway
Ubiquitin mediated proteolysis
TGF-beta signaling pathway
Insulin signaling pathway
Prostate cancer
Transcriptional misregulation in cancer
Small cell lung cancer
MAPK signaling pathway
Hepatitis B
mTOR signaling pathway
Pathways in cancer
p53 signaling pathway
Wnt signaling pathway
Neurotrophin signaling pathway
Focal adhesion
PI3K-Akt signaling pathway
Long-term potentiation
Chronic myeloid leukemia
Non-small cell lung cancer
Hypertrophic cardiomyopathy (HCM)
Endometrial cancer
B cell receptor signaling pathway
Endocytosis
Colorectal cancer
Acute myeloid leukemia
HTLV-I infection
Regulation of actin cytoskeleton
Glycosaminoglycan biosynthesis - heparan
sulfate / heparin
Dilated cardiomyopathy
T cell receptor signaling pathway
Metabolism
Digestive system
Glycan biosynthesis and metabolism
<10-16
<10-16
Signaling molecules and interaction
Infectious diseases: Parasitic
Development
Cancers
Cancers
Signal transduction
Folding, sorting and degradation
Signal transduction
Endocrine system
Cancers
Cancers
Cancers
Signal transduction
Infectious diseases: Virus
Signal transduction
Cancers
Cell growth and death
Signal transduction
Nervous system
Cellular community
Signal transduction
Nervous system
Cancers
Cancers
Cardiovascular diseases
Cancers
Immune system
Transport and catabolism
Cancers
Cancers
Infectious diseases: Viral
Cell motility
Glycan biosynthesis and metabolism
Cardiovascular diseases
Immune system
15
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
<10-16
3*10-15
1.88*10-13
3.24*10-12
8.53*10-11
1.95*10-11
3.26*10-10
1.1*10-9
4.85*10-9
7.73*10-9
1.86*10-8
3.12*10-7
3.65*10-7
4.13*10-7
1.6*10-7
(continuation of Table 9)
KEGG pathway
KEGG Category
p-value
Pancreatic cancer
Type II diabetes mellitus
Lysine degradation
Amyotrophic lateral sclerosis (ALS)
Dopaminergic synapse
Arrhythmogenic right ventricular
cardiomyopathy (ARVC)
Valine. leucine and isoleucine biosynthesis
GnRH signaling pathway
Long-term depression
Cancers
Endocrine and metabolic diseases
Amino acid metabolism
Neurodegenerative diseases
Nervous system
Cardiovascular diseases
3.23*10-7
4.14*10-7
4.29*10-7
1.14*10-6
1.11*10-5
Cell cycle
Gap junction
Protein processing in endoplasmic
reticulum
Mucin type O-Glycan biosynthesis
HIF-1 signaling pathway
Fc epsilon RI signaling pathway
Renal cell carcinoma
Prion diseases
Cytokine-cytokine receptor interaction
Basal cell carcinoma
Phosphatidylinositol signaling system
Adipocytokine signaling pathway
Progesterone-mediated oocyte maturation
VEGF signaling pathway
Viral myocarditis
Viral carcinogenesis
Aldosterone-regulated sodium reabsorption
Melanogenesis
Adherens junction
Osteoclast differentiation
Cell growth and death
Cellular community
Folding. sorting and degradation
Amino acid metabolism
Endocrine system
Nervous system
Glycan biosynthesis and metabolism
Signal transduction
Immune system
Cancers
Neurodegenerative diseases
Signaling molecules and interaction
Cancers
Signal transduction
Endocrine system
Endocrine system
Signal transduction
Cardiovascular diseases
Cancers
Excretory system
Endocrine system
Cellular community
Development
1.8*10-5
1.83*10-5
2.8*10-5
0.0001
0.0002
0.0002
0.0003
0.0003
0.0004
0.0017
0.0019
0.0029
0.0086
0.0114
0.019
0.0198
0.0207
0.0208
0.0225
0.0278
0.0318
0.0333
0.0351
0.0422
DIANA-miRPath v2.1 settings: MicroT threshold: 0.8. p-value threshold: 0.05. Significantly enriched pathways
sorted by p-value.
16
Table 10. Plasma levels of peptides and hormones related to cardiovascular function before
and after adherent CPAP use.
Non-responders
N=18
Adropin at baseline, mcg/ml
0.70 [0.53;0.97]
MRP8/14 at baseline, mcg/ml
56.1 [33.5;113]
Aldosterone at baseline, ng/ml
12.9 [10.3;16.5]
Renin at baseline, uU/ml
18.9 [15.8;27.6]
Aldosterone-to-renin ratio at baseline 0.59 [0.26;1.2]
Aldosterone-to-renin ratio >1.2 at
baseline
No
11 (73.3%)
Yes
4 (26.7%)
Adropin after CPAP, mcg/ml
0.75 [0.64;0.91]
MRP8/14 after CPAP, mcg/ml
60 [37.7;85.9]
Aldosterone after CPAP, ng/ml
10.9 [6.10;22.8]
Renin after CPAP, uU/ml
10.7 [6.75;14.4]
Aldosterone-to-renin ratio after
1.06 [0.44;1.93]
CPAP
Aldosterone-to-renin ratio >1.2 after
CPAP
No
10 (66.7%)
Yes
5 (33.3%)
Change in adropin, mcg/ml
-0.02 [-0.07;0.06]
Change in MRP8/14, mcg/ml
-2.2 [-5.70;14.4]
Change in aldosterone, ng/ml
1.5 [-0.40;4.8]
Change in renin, uU/ml
5.4 [0.30;7.6]
Change in aldosterone-to-renin ratio -0.2 [-0.59;-0.05]
Change in classification
“aldosterone-to-renin ratio >1.2”:
Change to aldosterone-to-renin ratio
>1.2
1 (7.7%)
No change
11 (84.6%)
Change to aldosterone-to-renin ratio
≤1.2
1 (7.7%)
Responders
N=19
0.71 [0.48;0.8]
69.9 [44.5;85.9]
12.1 [8.90;16]
14.2 [8.75;40.8]
0.63 [0.26;1.47]
12 (66.7%)
6 (33.3%)
0.68 [0.57;0.73]
59.5 [38.3;97.6]
10.4 [5.9;14]
16.9 [10.3;26.9]
0.72 [0.32;0.98]
0.76
0.51
0.48
0.42
0.91
0.72
0.29
0.9
0.97
0.15
0.29
0.42
14 (82.4%)
3 (17.6%)
0.08 [-0.09;0.13]
11.4 [-6.40;27.1]
1.15 [-0.20;4.18]
0.65 [-3.82;8.82]
0.07 [-0.08;0.73]
0 (0%)
13 (81.2%)
3 (18.8%)
Aldosterone-to-renin ratio values higher than the cutoff of 1.2 indicate hyperaldosteronism.
17
p-value
0.38
0.57
0.84
0.29
0.016
0.44
Table 11. Correlation between plasma levels of peptides and hormones related to
cardiovascular function and change in mean blood pressure after adherent use of
continuous positive airway pressure.
r
p-value
s
p-value
Adropin at baseline
-0.03
0.85
-0.11
0.53
MRP8/14 at baseline
-0.10
0.55
-0.14
0.41
Aldosterone at baseline
0.08
0.64
0.07
0.7
Renin at baseline
0.02
0.92
-0.03
0.87
Aldosterone/renin at baseline
-0.21
0.23
-0.22
0.21
Adropin after CPAP
-0.05
0.8
-0.04
0.84
MRP8/14 after CPAP
-0.11
0.55
-0.21
0.23
Aldosterone after CPAP
-0.02
0.9
0.22
0.23
Renin after CPAP
0.19
0.27
0.02
0.92
Aldosterone/renin after CPAP
-0.14
0.46
-0.14
0.44
Change in adropin
0.08
0.65
0.07
0.69
Change in MRP8/14
0.13
0.46
0.14
0.44
Change in aldosterone
-0.11
0.57
-0.04
0.85
Change in renin
-0.14
0.45
-0.28
0.13
Change in aldosterone/renin
0.46
0.011
0.47
0.0099
Pearson’s (r) and Spearman’s (s) correlation coefficients and their associated p-values.
Table 12. Non-linear relationship analysis to identify cutoff points for plasma levels of
peptides and hormones related to cardiovascular function most significantly related with
favorable blood pressure response to adherent use of continuous positive airway pressure.
Renin post-CPAP
≤14.7 uU/ml
>14.7 uU/ml
Change in aldosterone-to-renin ratio
≤-0.13
>-0.13
Non-responders
Responders
12 (66.7%)
3 (21.4%)
6 (33.3%)
11 (78.6%)
9 (75%)
4(23.5%)
Paired
p-value
0.0155
Estimated
OR for R
7.33
0.0095
9.8
3 (25%)
13 (76.5%)
OR, odds ratio. Favorable blood pressure response to continuous positive airway pressure is characterized
as mean blood pressure changes greater than 4.5 mmHg.
18
Table 13. Non-linear relationship analysis to identify cutoff points for the change in mean
blood pressure most significantly related with the plasma levels of peptides and hormones
related to cardiovascular function.
Low change in MBP
High change in MBP
Aldosterone at baseline, ng/mla
13.50[10.20,16.50]
7.35[ 5.35, 9.05]
Renin post-CPAP, uU/mlb
10.65[ 7.27,15.23]
24.90[16.30,48.00]
Change in MRP8/14, mcg/ml c
12.25[ -3.63,31.75]
-4.40[ -7.28, -2.40]
d
Change in aldosterone, ng/ml
3.15[ -0.13, 5.08]
-0.50[-12.30, 0.10]
Change in Aldosterone/Renine
-0.26[ -0.85, -0.16]
0.11[ -0.05, 0.52]
a
b
Mean blood pressure (MBP) change >12.5 mmHg; MBP change>10.0 mmHg; c MBP
change>0.5 mmHg; d MBP change>12.5 mmHg; e MBP change>3 mmHg.
19
Paired pvalue
0.0422
0.0121
0.0252
0.0282
0.0009
Figure 1.
Title: Post-hoc analysis of the statistical power of the study.
Legend: At a significance level of 0.05 and a statistical power of 80%, with 24 subjects,
there is sufficient statistical power to estimate odds ratios of 15.2 or higher. When the
training and test sets are joined for a total of 38 subjects, there is sufficient power to
estimate odds ratios of 8.1 or higher.
20
Figure 2
Title: Analysis of unsupervised hierarchical clustering of miRNA microarray results for
samples from OSA patients with resistant hypertension with favorable (responders) and
unfavorable (non-responders) blood pressure responses to adherent use of continuous
positive airway pressure (CPAP).
Legend: The heat map shows the individual results for differential miRNA expression
post-CPAP compared to pre-CPAP. The color scale at the top ranges from red (the
highest registered increase in expression) to blue (the highest registered decrease in
expression). Values from -1 to 1 express the ddCt values computed as the post-CPAP
change from pre-CPAP relative to the trimmed 95% maximum in absolute value. Thus,
the heat map colors range from red (or negative ddCt, denoting increased expression after
CPAP) to blue (or positive ddCt, denoting decreased expression after CPAP) to white (no
changes in ddCt after CPAP), without scaling by row or column. The bottom of the image
shows the mean blood pressure change for each patient after three months of adherent use
of CPAP. The dendrograms show hierarchical clustering representing the similarities and
dissimilarities in expression profiles among individuals and among miRNAs. Missing
expression is presented in grey. The miRNAs presented are those missing less than 50%
of the values.
21
Figure 3.
Title: Unsupervised hierarchical clustering of miRNAs versus pathways (clustering based
on significance levels). The miRNAs included in this heat map were those that were
differentially expressed at baseline between the favorable blood pressure responders and
non-responders to adherent use of continuous positive airway pressure treatment among
patients with OSA and resistant hypertension.
Legend: Darker colors represent lower significance values. The dendrograms on the x
and y axes depict hierarchical clustering results for miRNAs and pathways, respectively.
22
Figure 4.
Title: Unsupervised hierarchical clustering of miRNAs versus pathways (clustering based
on significance levels). The miRNAs included in this heat map were those that
significantly changed after adherent use of continuous positive airway pressure (CPAP)
treatment in favorable blood pressure responders vs. non responders to CPAP.
Legend: Darker colors represent lower significance values. The dendrograms on the x
and y axes depict hierarchical clustering results for miRNAs and pathways, respectively.
23
Figure 5.
Title: Resistant Hypertension, Sleep Apnea, and Prediction of Favorable Response to
Treatment.
Legend: A singular cluster of cardiovascular system-related functional miRNAs was
identified, and specifically differentiates between patients with RH and OSA with
favorable BP reductions to adherent CPAP treatment from those with unfavorable
responses. The HIPARCO-Score was generated based on such discriminative miRNA
cluster, and is an easy-to-use and highly predictive clinical practice tool for identifying
favorable BP responders to CPAP treatment among patients with RH and OSA. Adherent
CPAP treatment is associated with significant and potentially functionally-relevant
changes in circulating cardiovascular system--related miRNAs. CPAP treatment
significantly decreased aldosterone-to-renin ratios among favorable BP responders to
CPAP but not among those whose BP did not significantly change in response to CPAP
treatment. RH; Resistant hypertension. OSA; Obstructive sleep apnea. CPAP; Continuous
positive airway pressure. BP; Blood pressure.
24
References
1.
Livak KJ, Schmittgen TD. Analysis of relative gene expression data using realtime quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods
2001;25:402–408.
2.
Liu Z, Liu Y, Li L, Xu Z, Bi B, Wang Y, Li JY. MiR-7-5p is frequently
downregulated in glioblastoma microvasculature and inhibits vascular endothelial
cell proliferation by targeting RAF1. Tumour Biol 2014;35:10177–10184.
3.
Sánchez-de-la-Torre M, Campos-Rodriguez F, Barbé F. Obstructive sleep apnoea
and cardiovascular disease. The Lancet Respiratory Medicine 2013;1:61–72.
4.
Dhandapany PS, Razzaque MA, Muthusami U, Kunnoth S, Edwards JJ, MuleroNavarro S, Riess I, Pardo S, Sheng J, Rani DS, Rani B, Govindaraj P, Flex E,
Yokota T, Furutani M, Nishizawa T, Nakanishi T, Robbins J, Limongelli G, Hajjar
RJ, Lebeche D, Bahl A, Khullar M, Rathinavel A, Sadler KC, Tartaglia M,
Matsuoka R, Thangaraj K, Gelb BD. RAF1 mutations in childhood-onset dilated
cardiomyopathy. Nature genetics 2014;46:635–639.
5.
Loyer X, Potteaux S, Vion A-C, Guérin CL, Boulkroun S, Rautou P-E,
Ramkhelawon B, Esposito B, Dalloz M, Paul J-L, Julia P, Maccario J, Boulanger
CM, Mallat Z, Tedgui A. Inhibition of microRNA-92a prevents endothelial
dysfunction and atherosclerosis in mice. Circulation Research 2014;114:434–443.
6.
Wu X, Sagave J, Rutkovskiy A, Haugen F, Baysa A, Nygård S, Czibik G, Dahl
CP, Gullestad L, Vaage J, Valen G. Expression of bone morphogenetic protein 4
and its receptors in the remodeling heart. Life Sci 2014;97:145–154.
7.
Brock M, Trenkmann M, Gay RE, Michel BA, Gay S, Fischler M, Ulrich S,
Speich R, Huber LC. Interleukin-6 modulates the expression of the bone
morphogenic protein receptor type II through a novel STAT3-microRNA cluster
17/92 pathway. Circulation Research 2009;104:1184–1191.
8.
Hu Y-W, Hu Y-R, Zhao J-Y, Li S-F, Ma X, Wu S-G, Lu J-B, Qiu Y-R, Sha Y-H,
Wang Y-C, Gao J-J, Zheng L, Wang Q. An agomir of miR-144-3p accelerates
plaque formation through impairing reverse cholesterol transport and promoting
pro-inflammatory cytokine production. In: Kocher O, editor. PLoS ONE
2014;9:e94997.
9.
Huan T, Rong J, Tanriverdi K, Meng Q, Bhattacharya A, McManus DD, Joehanes
R, Assimes TL, McPherson R, Samani NJ, Erdmann J, Schunkert H, Courchesne
P, Munson PJ, Johnson AD, O'Donnell CJ, Zhang B, Larson MG, Freedman JE,
Levy D, Yang X. Dissecting the Roles of MicroRNAs in Coronary Heart Disease
via Integrative Genomic Analyses. Arterioscler Thromb Vasc Biol
2015;ATVBAHA.114.305176.doi:10.1161/ATVBAHA.114.305176.
10. Bostjancic E, Zidar N, Glavac D. MicroRNA microarray expression profiling in
human myocardial infarction. Disease markers 2009;27:255–268.
11. Greco S, Perfetti A, Fasanaro P, Cardani R, Capogrossi MC, Meola G, Martelli F.
Deregulated microRNAs in myotonic dystrophy type 2. In: Musaro A, editor.
PLoS ONE 2012;7:e39732.
12. Huang N, Wang J, Xie W, Lyu Q, Wu J, He J, Qiu W, Xu N, Zhang Y. MiR-378a3p enhances adipogenesis by targeting mitogen-activated protein kinase 1.
Biochem Biophys Res Commun 2015;457:37–42.
13. Wang L-S, Li L, Li L, Chu S, Shiang K-D, Li M, Sun H-Y, Xu J, Xiao F-J, Sun G,
Rossi JJ, Ho Y, Bhatia R. MicroRNA-486 regulates normal erythropoiesis and
enhances growth and modulates drug response in CML progenitors. Blood
2014;doi:10.1182/blood-2014-06-581926.
25
14.
Lai CTM, Ng EKO, Chow P-C, Kwong A, Cheung Y-F. Circulating microRNA
expression profile and systemic right ventricular function in adults after atrial
switch operation for complete transposition of the great arteries. BMC
cardiovascular disorders 2013;13:73.
26