page 1 of 50 diabetes...1 baseline assessment of circulating micrornas near diagnosis of type 1...
TRANSCRIPT
1
Baseline assessment of circulating microRNAs near diagnosis of type 1 diabetes
predicts future stimulated insulin secretion
Isaac Snowhite1, Ricardo Pastori1,2, Jay Sosenko2, Shari Messinger Cayetano3, and
Alberto Pugliese1,2,4
1Diabetes Research Institute
2Department of Medicine, Division of Endocrinology and Metabolism,
3Department of Public Health Sciences,
4Department of Microbiology and Immunology,
Leonard Miller School of Medicine,
University of Miami,
Miami, Florida
Corresponding AuthorAlberto Pugliese, MDDiabetes Research InstituteLeonard Miller School of Medicine, University of Miami1450 NW 10th Avenue, Miami, FL 33136 USATel. 305-243-5348; Fax 305-243-4404;E-mail: [email protected]
Words: 4,204
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Diabetes Publish Ahead of Print, published online December 4, 2020
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Abstract
Type 1 diabetes is an autoimmune disease resulting in severely impaired insulin
secretion. We investigated whether circulating microRNAs (miRNAs) are associated with
residual insulin secretion at diagnosis and predict the severity of its future decline. We
studied 53 newly diagnosed subjects enrolled in placebo groups of TrialNet clinical trials.
We measured serum levels of 2,083 miRNAs using RNAseq technology, in fasting
samples from the baseline visit (<100 days from diagnosis), during which residual insulin
secretion was measured with a mixed meal tolerance test (MMTT). Area under the curve
(AUC) C-peptide and peak C-peptide were stratified by quartiles of expression of 31
miRNAs. After adjustment for baseline C-peptide, age, BMI and sex, baseline levels of
miR-3187-3p, miR-4302, and the miRNA combination of miR-3187-3p/miR-103a-3p
predicted differences in MMTT C-peptide AUC/peak levels at the 12-month visit; the
combination miR-3187-3p/miR-4723-5p predicted proportions of subjects above/below
the 200 pmol/L clinical trial eligibility threshold at the 12-month visit. Thus, miRNA
assessment at baseline identifies associations with C-peptide and stratifies subjects for
future severity of C-peptide loss after 1 year. We suggest that miRNAs may be useful in
predicting future C-peptide decline for improved subject stratification in clinical trials.
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Type 1 diabetes is a chronic autoimmune disease leading to progressive (yet
heterogeneous) loss and dysfunction of pancreatic -cells (1). The TrialNet organization
has completed clinical trials in participants with newly diagnosed type 1 diabetes (<100
days) and stimulated peak C-peptide >200 pmol/L. A 2-year follow-up of 191 participants
in placebo groups demonstrated greater C-peptide loss during the first year post-
diagnosis (2); yet 88% and 66% had stimulated peak C-peptide >200 pmol/L 1 year and
2 years after diagnosis, respectively. Several agents preserve insulin secretion in
individuals with newly diagnosed type 1 diabetes, in some cases for up to 2-7 years after
treatment (3). Novel biomarkers to stratify trial participants at baseline and predict decline
of their insulin secretion would afford gains in trial design and efficiency, facilitating the
identification of effective therapies.
miRNAs are small, non-coding RNAs that regulate gene expression (4) and are
emerging as disease biomarkers. Circulating miRNAs are stable and measurable in
serum and plasma with similar results (5). Twenty-nine circulating miRNAs were
associated with type 1 diabetes by 2-8 studies (supplemental Table S1) (6-24),
suggesting reproducible associations despite heterogeneity in study design, cohorts,
assays, and analysis methods. Cellular miRNAs were also linked to both human and
experimental diabetes (23; 25-30).
An outstanding question is whether circulating miRNAs predict C-peptide decline
after diagnosis. Samandari et al. (12) assessed plasma levels using Exiqon RT-PCR
assays for 179 miRNAs; 3-month visit plasma levels of several miRNAs (miR-24-3p, miR-
146a-5p, miR-194-5p, miR-197-3p, miR-301a-3p and miR-375) correlated with residual
-cell function at the 6- and 12-month visits; miR-197-3p levels at the 3-month visit
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predicted -cell function 12 months after diagnosis. Garavelli et al. (24) reported that miR-
23a-3p, miR-23b-3p, miR-24-3p, miR-27a-3p and miR-27b-3p predicted fasting C-
peptide loss <10% or >90% 12 months after diagnosis. In other studies, Let-7g was
associated with C-peptide levels during the first year post-diagnosis (19), levels of the -
cell enriched miR-204 correlated with C-peptide AUC at diagnosis (31), and levels of miR-
142-5p, miR-29c-3p, and miR320 differed in children with recent onset type 1 diabetes
according to residual fasting C-peptide (23).
We assessed levels of 2,083 miRNAs in baseline serum samples from 53
participants with newly diagnosed type 1 diabetes randomized to placebo groups in
TrialNet clinical trials. We report miRNA associations with stimulated C-peptide which are
maintained at the 12-month visit and stratify participants for future severity of C-peptide
loss.
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MATERIAL AND METHODS
Subjects. We examined baseline serum samples from 53 individuals with newly
diagnosed type 1 diabetes who were enrolled in TrialNet clinical trials as placebos, <100
days from diagnosis and with stimulated peak C-peptide >200 pmol/L. Table 1 shows
their baseline characteristics. Subjects were included in this study based on availability
of a fasting serum sample that could be used for miRNA assessment, obtained on the
day of the baseline MMTT. Supplemental Fig. S1 illustrates C-peptide AUC and peak
levels during the 2-hour MMTTs performed at the baseline, 6-month, and 12-month visits
(2). The baseline MMTT was performed within an average of 1.9 + SD 0.1 months from
diagnosis or 58 days.
MMTT. The MMTT was described previously (32); serum C-peptide levels were
measured using a TOSOH 900 AIA analyzer. The trapezoidal rule was used to calculate
the C-peptide AUC in nmol/L; peak levels are reported in pmol/L (2).
miRNA Assay. We tested 15 l serum aliquots. Samples were collected and
processed according to TrialNet protocols (supplemental methods). miRNAs were
assayed using the HTG Molecular Diagnostics EdgeSeq miRNA assay (33), which
combines a quantitative nuclease protection assay with Next Generation Sequencing. It
does not require miRNA isolation, reverse transcription, adenylation or ligation, which
could introduce bias. The assay has a broad dynamic range with high reproducibility,
sensitivity and specificity (33). Testing of blind replicate samples from 4 individuals with
type 1 diabetes provided by the JDRF Biomarker Working Group Core for Assay
Validation confirmed excellent reproducibility (r=0.94-0.96, CV%=1.06%). Undiluted RNA
is bound to corresponding target-specific nuclease protection probes, after treatment with
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lysis buffer. The probe set contains complementary sequences for 2,083 specific miRNAs
or ~78% of the published mature transcripts in miRbase V22 (34). Probes hybridized to
cognate miRNAs are protected from S1 nuclease digestion, amplified with the addition of
barcodes, and sequenced. After amplification the library was quantified according to the
HTG EdgeSeq KAPA Library Quantification protocol for Illumina Sequencing.
Sample Processing and Batch Control. Processing controls include 4 negative and
1 positive control, and a human brain RNA standard. All samples were run as singletons
except the standard was run in triplicate. Samples were randomized before placement
to reduce inter-plate and intra-plate biases, which were assessed using both Pearson and
Spearman correlation coefficients.
Post Sequencing Quality Control. Each well in HTG EdgeSeq assays includes 4
negative and 1 positive control probes with unique sequences. All samples and controls
were quantified in triplicate with the inclusion of no template control (NTC) reactions
during the qPCR process. A PhiX control adaptor-ligated library was spiked into the
pooled library to confirm labeling efficiency and each well was spiked with four unique
plant sequences that are digested by the S1 nuclease during the protection assay.
miRNA Data Management and Analysis. The output is a read count, as in small
RNA-seq, but unlike small RNA-seq, the read count reflects the quantity of probes bound
by miRNAs and protected from digestion. The HTG EdgeSeq Parser aligned the FASTQ
files to the probe list to collate the data. Data tables included raw, QC raw, log2 CPM
(counts per million), and median normalized.
CPM Standardization and Normalization. CPM standardization was used for
evaluation between samples, replicate comparisons, batch effects, and quality control
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metrics. The Log2 transformation was used for standardizing, or scaling, gene-level data
within a sample. CPM standardization allows the evaluation of probe-level expression as
a proportion of total counts on a sample level and between samples, as described in the
𝑙𝑖𝑚𝑚𝑎 package (35; 36). Inter-sample normalization was achieved by scaling raw read
counts in each lane by a single lane-specific factor reflecting its library size (37). Gene
counts were divided by the median of mapped reads (or library size) associated with their
lane and multiplied by the median total count across all samples. Normalization was
performed using the 𝐷𝐸𝑆𝑒𝑞2 package from Bioconductor and the 𝑅 statistical program
(www.r- project.org).
Statistical analysis. We investigated whether C-peptide levels (fasting, AUC and
peak) were associated with miRNA levels at the baseline MMTT; then, we examined
whether baseline associations were maintained at the 12-month MMTT.
Baseline analysis. We estimated associations between baseline MMTT outcomes
(fasting C-peptide, AUC and peak levels) and miRNA levels. For each miRNA we fit a
linear model to MMTT outcomes, including a nominal indicator of quartile of expression,
with adjustments for age, BMI, and sex. Global F tests of significance determined a list of
miRNAs where variability in baseline MMTT outcome was significantly explained by
miRNA quartile. Bootstrapped resampling with 1,000 replications provided correction for
multiple comparisons, and estimated comparisons among quartiles for differences in
MMTT outcomes. For those miRNAs having significant bootstrapped associations
between expression quartiles and MMTT outcomes, we evaluated specific comparisons
between quartiles for significant differences in MMTT outcomes.
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Longitudinal analysis. Those miRNAs with baseline associations with MMTT
outcomes were investigated to evaluate maintained associations with 12-month C-
peptide AUC and peak. This was accomplished by fitting a linear model to each MMTT,
considering quartile of miRNA expression with identified association with baseline MMTT,
adjusting for corresponding baseline C-peptide, age at draw, sex, and BMI. Results
illustrating evidence of longitudinal associations with specific miRNAs were then
considered in stepwise regression to identify those miRNAs which, in combination, have
significant association and best predict 12-month MMTT after adjustment for baseline C-
peptide AUC, age, sex and BMI.
Receiving Operator Curves (ROC). ROC were constructed from predicted values
from logistic regression models fit to binary outcome defined by percentage decline from
baseline (<25% vs >25%). These models were fit with/without miRNA information in
addition to baseline C-peptide AUC and were adjusted for BMI and gender. ROC were
compared to determine whether miRNAs improve prediction of C-peptide decline above
baseline C-peptide AUC using the DeLong’s test for correlated ROC (38).
Longitudinal assessment of MMTT C-peptide/Glucose Response (CGR) curves
after stratification for baseline miRNA levels. We plotted glucose against C-peptide values
(30 to 120 minutes) from baseline, 6-month and 12-month MMTTs for the two groups of
subjects defined by baseline miRNA levels. Changes/differences in the curves position
(shifts to the left, lower C-peptide; upwards, higher glucose), directionality and shape (a
narrower horizontal spread and upward straightening of the curve, or monotonic shape)
illustrates progressive worsening over time and differences between miRNA-stratified
groups. We used the T-test to assess statistical significance in comparisons of baseline
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mean AUC C-peptide/AUC glucose ratios of the two miRNA expression groups (curves)
to 6- and 12-month ratios, and in comparisons of miRNA-stratified groups (curves) within
each MMTT.
Other analyses. For statistical comparisons involving binary outcomes, groups
were compared using the 2-tailed Fisher’s exact test.
Bioinformatic prediction of putative gene targets and pathways. We
interrogated the reference database KEGG (Kyoto Encyclopedia of Genes and Genomes,
https://www.genome.jp/kegg/) and used miRWalk 2.0 (39) (http://zmf.umm.uni-
heidelberg.de/apps/zmf/mirwalk2/) to identify gene pathways predicted to be targeted by
miRNAs of interest (accessed April-May 2020). miRWalk 2.0 hosts predicted and
experimentally validated miRNA-target interaction pairs, documents miRNA-binding sites
within the complete sequence of a gene and combines this information with a comparison
of binding sites resulting from use of miRanda-rel2010, Targetscan 6.2, miRWalk 2.0 and
RNA22 v2. Statistical significance of these predictions is reported after the Benjamini–
Hochberg correction for multiple comparisons.
Data resource sharing and availability. The datasets generated during and/or
analyzed during the current study were deposited in the Gene Expression Omnibus
(GEO) repository https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE157177). No
applicable resources were generated or analyzed during the current study.
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RESULTS
Detection of miRNAs. The EdgeSeq assay collectively detected all 2,083
miRNAs. Detection rates were >95% for all but 4 miRNAs (miR-128-2-5p, 2%; miR-1282,
27%; miR-4525, 6%; miR-6752-3p, 38%). The average detection rate was 2,077 ± 12 SD
miRNAs, which accounts for 99.7% ± SD 0.5% of the panel. The mean normalized log2
CPM values were 7.92 ± SD 0.33 (range:0.5-22.4) for all miRNAs. We observed very
robust raw counts (mean 3.2 ± SD 1.05, range 1.4-7.7 million reads) in 15 L of serum.
Baseline associations. We estimated associations of baseline MMTT outcomes
(fasting C-peptide, AUC, and peak levels) with miRNA expression quartiles. Bootstrapped
resampling with 1,000 replications provided adjusted p values for associated miRNAs, to
correct for multiple comparisons, and estimated comparisons among quartiles for
differences in MMTT outcomes. Among statistically significant associations of C-peptide
with mRNAs after bootstrapping, lowest or highest quartiles vs. the other 3 quartiles were
generally best at discriminating C-peptide differences. Table 2 lists miRNAs and quartile
comparisons that identified significant differences in baseline C-peptide AUC and/or peak:
differences in C-peptide AUC or peak were identified by 25 and 22 miRNAs, respectively,
among which 16 miRNAs had associations with both outcomes, which are naturally
correlated (Table 2A). There were 9 and 6 miRNAs associated with either C-peptide AUC
or peak levels (Table 2B). There were no significant miRNA associations with fasting C-
peptide. miRNA expression quartiles identified baseline C-peptide AUC differences
ranging from 25.92 to 42.3 nmol/L, and peak C-peptide differences ranging from 276 to
442 pmol/L, after bootstrapping. The miRNA that identified the largest C-peptide AUC
and peak differences was miR-3187-3p (42.3 nmol/L and 442 pmol/L, respectively); the
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previously reported miR-197-3p (6) identified C-peptide AUC and peak differences of
33.58 nmol/L and 351 pmol/L, respectively. All values are reported in Table 2; Fig. 1
shows C-peptide AUC and peak levels according to miRNA expression quartiles for 6
representative miRNAs. Supplemental Table S5 reports total raw counts, raw CPM and
normalized CPM (log2) for the 31 miRNAs associated with C-peptide.
Longitudinal associations. We investigated whether baseline miRNAs predicted
C-peptide at the 12-month MMTT. Specifically, we examined whether any miRNA
associated with baseline C-peptide AUC and/or peak (Table 2) remained associated and
predicted C-peptide AUC and/or peak at the 12-month MMTT, after adjusting for baseline
C-peptide, age, sex, and BMI. Two miRNAs remained associated with both C-peptide
AUC (miR-3187-3p, p=0.037; miR-4302, p=0.047) and peak (miR-3187-3p, p=0.038;
miR-4302, p=0.039) at the 12-month MMTT (Table 3). Baseline expression quartiles of
miR-3187-3p and miR-4302 defined groups of participants with a mean difference in the
12-month C-peptide AUC of 22.49 and 21.05 nmol/L, respectively; mean differences for
12-month peak C-peptide were 236 and 229 pmol/L, respectively. miR-1292-5p was
associated with peak C-peptide only (mean difference=212 pmol/L). Fig. 2 illustrates
longitudinal associations and C-peptide decline for representative miRNAs: miR-3187-3p
and miR-4302 (which stratified participants with significantly different 12-month C-peptide
AUC and peak) and miR-103a-3p and miR-197-3p (which stratified participants only at
baseline).
Stepwise regression modeling to identify combinations of predictive
miRNAs. miRNAs associated with baseline C-peptide AUC were evaluated in a stepwise
regression to identify miRNA combinations with improved prediction of 12-month C-
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peptide AUC, after adjustment for baseline C-peptide AUC, age, sex and BMI: 12/25
miRNAs with baseline associations were included in the model. The combination of miR-
3187-3p and miR-103a-3p discriminated C-peptide AUC (Fig. 3A) and peak (Fig. 3B)
levels at 12 months. Stratification according to baseline miRNA expression quartiles for
this combination demonstrated differences in the baseline to 12-month AUC and peak C-
peptide levels of 37.95 nmol/L (p=0.001) and 39 pmol/L (p=0.001) between groups
(supplemental Table S2). Eleven participants with low expression (1st quartile) of miR-
3187-3p combined with high expression (2nd-4th quartile) of miR-103a-3p had higher 12-
month C-peptide AUC compared to the other 42 participants. This combination was
superior to miR-3187-3p alone as 2 more subjects were stratified to the lower C-peptide
group. The miR-3187-3p/miR-4302 combination identified differences in AUC C-peptide
decline of 44.86 nmol/L (p=0.001) (Table S2, Fig. 3C) and assigned two additional
individuals to the lower C-peptide group than miR-3187-3p alone.
We also investigated whether any single miRNA or combination could stratify
participants at the 12-month visit by peak C-peptide levels above/below the clinical trial
eligibility threshold. No individual miRNA from Table 2 was predictive. However, the
combination of miR-3187-3p and miR-4723-5p predicted that 94% (17/18) of the
participants with baseline expression levels in the lower quartile for both miRNAs would
have peak C-peptide >200 pmol/L at the 12-month visit compared to 64% (22/34) of those
with miRNA expression levels in the second to fourth quartiles (p=0.021, Fisher’s exact
test, 2-tailed; relative risk=1.4, 95% C.I.=1.086-1.993; sensitivity=0.4359, 95%
C.I.=0.2930-0.5902; specificity=0.9231, 95% C.I.=0.6669-0.9961).
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We examined whether miRNAs improved prediction of C-peptide decline
compared to baseline C-peptide AUC. ROC in Fig. 3D illustrates improved ability to
separate between groups with decline greater/lower than 25% when the miR-3187-3p/
miR-103a-3p combination is considered in the model; ROC AUC with/without miRNAs
were 0.82 and 0.70, respectively (p=0.04).
Longitudinal assessment of MMTT CGR curves after stratification for
baseline miRNA levels. CGR curves for baseline, 6-month and 12-month MMTTs
stratified participants into two groups (curves) by their baseline levels of associated
miRNAs (Fig. 4). Curves evolved at 6 months and 12 months, demonstrating progressive
worsening of insulin secretion (shift to the left) and higher glucose levels (shift upwards),
with greater separation of the curves for the miRNA combinations. Overall, subject
stratification by baseline miRNA expression quartiles demonstrated differences in
disease severity at diagnosis which persisted during further progression and involved
both C-peptide and glucose responses.
Longitudinally, we compared baseline mean AUC C-peptide/AUC Glucose ratios
of the two miRNA expression groups (curves) to the ratios of the corresponding curves at
later time points; for example, the ratio from the Q1 curve at baseline was compared to
the ratio of the Q1 curves at 6 month and the same comparison was made between 6
and 12 months. These were all significantly different from each other, demonstrating
worsening in both groups (range p<0.0001-p=0.02, 2-tailed paired T-test, supplemental
Table S3). However, 6-month and 12-month curves of miR-3187-3p/miR-4302 were
statistically different from each other for participants in combination group 0, but not for
those in combination group 1, suggesting that the latter did not experience significant
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worsening in this time interval. Cross-sectionally, we compared AUC C-peptide/AUC
Glucose ratios of the two groups (curves) in each panel; these were significantly different
at all time points for all miRNAs or combinations analyzed (range p<0.0001-p=0.0397; T-
test, unpaired, 2-tailed; supplemental Table S4); the only exception were the miR-103a-
3p 12-month curves (p=0.05). The findings suggest significant differences in disease
progression identified by stratification in groups defined by baseline miRNA levels.
Bioinformatic prediction of target gene pathways. We used miRWalk 2.0 (39)
to examine whether any of the 31 miRNAs associated with C-peptide AUC and/or peak
at baseline are predicted to modulate gene pathways relevant to type 1 diabetes. Results
are reported in Table 4, in which we list four major gene pathways relevant to type 1
diabetes and/or type 2 diabetes, specifically the insulin signaling, SNARE interactions in
vesicular transport, type II diabetes mellitus, and the T-cell receptor (TCR) signaling
pathways. Nineteen miRNAs were predicted to target either the insulin or TCR signaling
pathways, and remarkably 9 miRNAs were predicted to target both (miR-103a-3p, miR-
193b-5p, miR-197-3p, miR-3187-3p, miR-4302, miR-622, miR-6748-3p, miR-1208, and
miR-1292-5p). Among the 5 miRNAs which alone or in combination predicted 12-month
C-peptide outcomes (miR-3187-3p, miR-4302, miR-1292-5p, miR-103a-3p, and miR-
4723-5p), 4 targeted both insulin and TCR signaling pathways and potentially may
modulate a large number of genes (71 to 104/139 genes and 65-80/110 genes,
respectively). For miR-3187-3p, the TCR signaling pathway was predicted as the first of
16 pathways.
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DISCUSSION
Despite the emergence of reproducible associations of circulating miRNAs with
type 1 diabetes, there are limited data about miRNA prediction of C-peptide decline after
diagnosis. Moreover, virtually all published studies of circulating miRNAs in islet
autoimmunity and type 1 diabetes used RT-PCR assays investigating a fraction of the
known miRNAs (supplemental Table S1); Nielsen et al. (6) sequenced pooled samples
to identify differentially expressed miRNAs between individuals with type 1 diabetes and
controls, then assessed levels of 24 miRNAs by RT-PCR. With 2,656 transcripts in
miRbase V22 (34), there is much potential for discovery. Thus, we profiled 2,083 miRNAs
using RNAseq technology. To date, our study has examined the largest number of
miRNAs concerning residual C-peptide at diagnosis.
To investigate whether circulating miRNAs are associated with and predict loss of
insulin secretion after diagnosis, we examined fasting serum samples obtained on the
same day of the baseline MMTT from 53 individuals. Several miRNAs were associated
with C-peptide AUC and/or peak at the baseline MMTT (Table 2, Fig. 1); miRNA
expression quartiles identified participants with better or worse residual insulin secretion,
after adjustment for age, sex, and BMI. The observed differences were not explained by
variation in time from diagnosis to baseline MMTT (not shown). These associations
survived correction for multiple comparisons by bootstrapping.
In longitudinal analyses, baseline levels of 5 of these miRNAs, alone or in
combination, predicted MMTT C-peptide outcomes at the 12-month visit: miR-3187-3p
and miR-4302 predicted C-peptide AUC, miR-3187-3p/miR-103a-3p predicted AUC and
peak, and miR-1292-5p predicted peak C-peptide; . In addition, miR-3187-3p/miR-4723-
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5p predicted participants being above or below the peak C-peptide trial eligibility threshold
at the 12-month visit. The miR-3187-3p/miR-103a-3p combination improved prediction of
C-peptide decline compared to baseline C-peptide AUC alone (Fig. 3D). Baseline
differences in C-peptide AUC or peak were maintained on follow-up, after correction for
baseline C-peptide, age, sex and BMI, and decline occurred with similar slopes (Figs. 2
and 3). We cannot discern whether this reflects differences in physical/functional -cell
mass at baseline, in the severity of the autoimmune process, or both.
A prior study of relatives at-risk for type 1 diabetes showed that plotting C-peptide
AUC against glucose AUC values at the time points of the oral glucose tolerance test
(OGTT) helps assessing metabolic impairment during progression to clinical diagnosis
(40). Changes in the curves position, shape and direction demonstrated progressive
worsening during the progression. For the first time, we applied this approach to visualize
these relationships during the MMTT and analyze differences in metabolic responses at
baseline and on follow-up in groups stratified by baseline miRNA levels (Fig. 4).
Participants having higher baseline C-peptide AUC after miRNA stratification had
less pathological curves: their position on the grid indicated higher C-peptide and lower
glucose levels, and their shape indicated more C-peptide secretion relative to glucose
levels. On follow-up, their curves remained distinct from those of the other participants.
The comparisons of the C-peptide AUC/Glucose AUC ratios from baseline ratios
quantified the significant worsening and the differences among the groups stratified by
the baseline miRNA levels persisted over time.
For most of the 31 miRNAs associated with C-peptide at baseline there is no prior
involvement in disease-relevant pathways. This is not surprising given that we identified
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many miRNAs never before examined in this setting. However, miR-Walk 2.0 predicted
that 19/31 miRNAs may target disease-relevant gene pathways; 7/19 had previous
disease-relevant literature associations (4 with type 1 and type 2 diabetes, 2 with type 2
diabetes only, and 1 with -cell differentiation): remarkably, 19 miRNAs could target either
the insulin or TCR signaling pathways; 9 miRNAs may target both. These included 4/5
miRNAs associated with C-peptide at the 12-month MMTT, alone or in combination (miR-
3187-3p, miR-4302, miR-103a-3p, miR-1292-5p and miR-4723-5p). There were no
previous associations, except for miR-589-5p, for 13 miRNAs with no relevant predictions.
miR-3187-3p had the strongest association with C-peptide. The TCR signaling
pathway ranked first of 16 predicted pathways. It could target genes involved in AKT
(Serine/Threonine Kinase)/PI3K (Phosphatidylinositol 3-kinase) signaling, which is critical
for the development, differentiation and function of effector (41) and regulatory T-cells
(42). Other predicted targets include the CD3 -chain, the MAPK13 and MAPK14 genes
in the mitogen-activated protein kinase signaling pathway, LAT (linker for the activation
of T-cells, SOS1 (son of sevenless factor 1, an exchange factor recruited by LAT), NFAT
(transcription factor nuclear factor of activated T-cells), and the tyrosine phosphatase
CD45 (43).
Plasma levels of miR-103a-3p were increased in individuals with type 1 diabetes
(<5 years duration compared to healthy subjects) (18). We show that higher miR-103a-
3p levels are associated with higher residual insulin secretion near diagnosis, and that
baseline miR-103a-3p levels can aid in predicting C-peptide AUC at 12 months; the
combination miR-3187-3p/miR-103a-3p was the stronger predictor of C-peptide AUC.
This miRNA was linked to type 2 diabetes, obesity, and HFN1A-MODY (44-46). In the
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Coronary Diet Intervention with Olive Oil and Cardiovascular Prevention study, low
circulating levels of miR-103a-3p were associated with increased likelihood of type 2
diabetes (47). miR-107 and miR-103a-3p are negative regulators of insulin sensitivity
(48). Validated gene targets of miR-103a-3p include SFRP4 (the secreted frizzled-related
protein 4), which suppresses insulin exocytosis (49), and Cav1 (caveolin-1), which inhibits
insulin signaling by decreasing insulin receptors in caveolae-enriched plasma membrane
domains (48). miR-103a-3p regulates the autophagy gene ATG5 (50), and autophagy
regulates transport-competent secretory peptide precursors, including proinsulin (51). In
our analysis, this miRNA may target both the TCR and insulin signaling pathways.
Other miRNAs were associated with C-peptide at baseline but not on follow-up.
These included miR-197-3p, which in a previous report predicted future C-peptide AUC
(12); the different outcomes may reflect assay type, sample size (most likely), or sample
type (serum vs plasma). miR-197-3p is predicted to target several genes in both the
insulin and TCR signaling pathways. Its plasma levels were reduced in subjects with type
2 diabetes (52).
The gene coding for miR-342-3p on 14q32 contains a cluster of glucose-
responsive miRNAs expressed in pancreatic islet cells (53); miR-342-3p also regulates
the expression of the autoantigen IA-2β (54). We previously reported that miR-342-3p
levels were associated with increased risk of progression to type 1 diabetes among
autoantibody-positive relatives and levels correlated with OGTT outcomes (13); in other
studies, miR-342-3p was differentially expressed in individuals with type 1 diabetes
compared to healthy subjects and at-risk relatives (14); its levels were reduced in
regulatory T-cells in affected individuals compared to healthy subjects (25).
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miR-127-3p is enriched in human -cells (55) and involved in endocrine
differentiation (56); miR-99a-5p, exhibited increased levels during the first 12 months
post-diagnosis in children with recent onset type 1 diabetes (20) and targets the mTOR
pathway (57). miR-589-5p (58) and miR-193b-5p were associated with type 2 diabetes
and prediabetes, respectively; miR-193b-5p was linked to islet autoimmunity as it was
differentially expressed in autoantibody-positive vs -negative individuals (10).
In closing, trial participants with higher or lower MMTT C-peptide AUC and peak
were stratified by baseline miRNA levels. Selected miRNAs/miRNA combinations
predicted future decline of C-peptide AUC and peak. Predicting future C-peptide at
baseline is critical for subject stratification early after diagnosis when impactful decisions
about trial participation or treatment need to be made. A miRNA combination predicted
12-month C-peptide peak above/below the clinical trial eligibility threshold, which is of
particular importance given increased consideration for trial enrollment up to 2 years from
diagnosis if meeting the peak C-peptide threshold. Many associated miRNAs were
examined for the first time, but some were previously linked to type 1 diabetes; several
are predicted to impact gene pathways relevant to -cell function and T-cells, both critical
to disease pathogenesis. Future studies may explore possible links of miRNAs with
disease endotypes. Limitations of this study are the limited sample size and the lack of a
validation cohort, which require future investigations. These miRNAs are excellent
candidates for validation studies and may become useful biomarkers for advancing
therapeutic discoveries for type 1 diabetes.
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ACKNOWLEDGEMENTS
Author contributions. Authors generated (I.S.), analyzed and interpreted data (I.S., J.S.
R.L.P., S.M.C., A.P.) participated in the preparation of the manuscript and approved its
final version (all authors). S.M.C. was responsible for statistical design and analysis plan.
J.S. R.L.P., S.M.C., and A.P conceived the study or parts of the study.
Guarantor statement. A.P. and S.M.C. are the guarantors of this work and, as such, had
full access to all the data in the study and take responsibility for the integrity of the data
and the accuracy of the data analysis.
Conflict of interest. Authors declare no conflict of interest relevant to this study.
Funding. The study supported by JDRF (2-SRA-2015-122-Q-R) and the Diabetes
Research Institute Foundation, Hollywood, Florida, USA. We acknowledge the support of
the Type 1 Diabetes TrialNet Study Group, which identified study participants and
provided samples and follow-up data for this study. The Type 1 Diabetes TrialNet Study
Group is a clinical trials network funded by the National Institutes of Health (NIH) through
the National Institute of Diabetes and Digestive and Kidney Diseases, the National
Institute of Allergy and Infectious Diseases, and The Eunice Kennedy Shriver National
Institute of Child Health and Human Development, through the cooperative agreements
U01 DK061010, U01 DK061034, U01 DK061042, U01 DK061058, U01 DK085453, U01
DK085461, U01 DK085465, U01 DK085466, U01 DK085476, U01 DK085499, U01
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DK085504, U01 DK085509, U01 DK103180, U01 DK103153, U01 DK103266, U01
DK103282, U01 DK106984, U01 DK106994, U01 DK107013, U01 DK107014, UC4
DK106993, UC4 DK11700901, U01 DK 106693-02, and the JDRF. We acknowledge Dr.
Simi Ahmed (JDRF) for programmatic support. The contents of this article are solely the
responsibility of the authors and do not necessarily represent the official views of the NIH
or the JDRF.
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Table 1. Baseline characteristics of 53 Participants with new-onset type 1 diabetes.
______________________________________________________________________
N (M/F) 53 (34/19)
TrialNet Trials N (M/F)
TN02 MMF/DZB 16 (11/5)
TN08 GAD 19 (12/7)
TN09 CTLA-4Ig 8 (6/2)
TN14 Anti-IL-1 Beta 10 (5/5)
Mean ± SD
Age of Diagnosis (Years) 16.8 ± 10.0
Type 1 diabetes duration at MMTT (Months) 1.9 ± 0.1
BMI (kg/m2) 20.8 ± 4.2
HbA1c [mmol/mol (%)] 60 ± 26 (7.6% ± 1.7)
2-Hours MMTT Mean ± SD
Fasting C-Peptide (pmol/L) 364.1 ± 216.3
AUC C-Peptide (nmol/L) 82.2 ± 35.3
Peak C-Peptide (pmol/L) 886.2 ± 385.1
Fasting Glucose (mmol/L) 112.8 ± 29.6
Peak Glucose (mmol/L) 2.7 ± 1.2
______________________________________________________________________
Essential baseline characteristics of the study cohort and baseline MMTT C-peptide
outcomes.
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Table 2. miRNAs associated with baseline MMTT AUC and/or peak C-peptide.
miRNA Quartiles Comparison
C-peptide AUC Estimated Difference
(nmol/L)P
ValueC-peptide Peak
Estimated Difference (pmol/L)
P Value
miRNAs associated with AUC and peak C-peptidemiR-3187-3p Q2-4 vs Q1 42.30 0.0018 442 0.0070miR-4302 Q2-4 vs Q1 35.19 0.0218 344 0.0065miR-8079 Q2-4 vs Q1 34.46 0.0156 387 0.0258miR-197-3p Q1 vs Q2-4 33.58 0.0150 351 0.0086miR-193b-5p Q2-4 vs Q1 32.58 0.0272 366 0.0178miR-4669 Q2-4 vs Q1 31.75 0.0279 351 0.0419miR-494-5p Q1-3 vs Q4 31.72 0.0233 325 0.0377miR-103a-3p Q1 vs Q2-4 31.44 0.0231 332 0.0560miR-4304 Q1-3 vs Q4 29.83 0.0257 324 0.0360miR-4701-3p Q1-3 vs Q4 29.75 0.0269 272 0.0501miR-98-3p Q2-4 vs Q1 29.23 0.0387 337 0.0480miR-99a-5p Q4 vs Q1-3 28.42 0.0367 312 0.0492miR-3678-3p Q1-3 vs Q4 27.77 0.0292 290 0.0487miR-5682 Q1-3 vs Q4 26.91 0.0436 288 0.0343miR-7154-3p Q1-3 vs Q4 26.55 0.0457 294 0.0194miR-3191-3p Q1-3 vs Q4 26.14 0.0455 276 0.0106
miRNAs associated with C-peptide AUCmiR-8058 Q2-4 vs Q1 32.30 0.0216 - nsmiR-2355-3p Q1-3 vs Q4 32.13 0.0162 - nsmiR-934 Q2-4 vs Q1 28.77 0.0443 - nsmiR-6748-3p Q1 vs Q2-4 28.71 0.0275 - nsmiR-6073 Q1-3 vs Q4 28.33 0.0416 - nsmiR-342-3p Q4 vs Q1-3 26.96 0.0572 - nsmiR-622 Q2-4 vs Q1 26.92 0.0369 - nsmiR-215-5p Q2-4 vs Q1 26.89 0.0563 - nsmiR-568 Q1-3 vs Q4 25.92 0.0456 - ns
miRNAs associated with peak C-peptidemiR-1208 Q2-4 vs Q1 - ns 361 0.0406miR-1292-5p Q2-4 vs Q1 - ns 311 0.0326miR-589-5p Q1-3 vs Q4 - ns 297 0.0159miR-4723-5p Q2-4 vs Q1 - ns 283 0.0260miR-127-3p Q1 vs Q2-4 - ns 282 0.0321miR-6506-5p Q1-3 vs Q4 - ns 281 0.0559
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The Table reports estimated differences in C-peptide levels between patient groups
defined by quartiles of miRNA expression. Estimated differences and p values are
corrected for multiple comparisons by bootstrapping analysis. The estimated differences
are those between the quartile comparisons; the quartiles on the left side of the
comparison are those associated with higher C-peptide AUC or peak levels. Either the
highest or lowest quartile of miRNA expression was associated with higher or lower C-
peptide levels compared to the remaining quartiles, which did not differ amongst
themselves. C-peptide AUC and peak levels showed associations with 16 miRNAs, and
miRNAs are ranked by the estimated difference in C-peptide AUC (upper Table); 9
miRNAs were associated with AUC and 6 miRNAs with peak C-peptide, respectively, and
miRNAs are ranked by estimated difference in AUC or peak (middle and lower Table).
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Table 3. miRNAs assessed at baseline with association with C-peptide AUC
and/or peak at the 12-month MMTT.
miRNA Quartile Comparison
C-peptide AUC Estimated Difference (nmol/L)
P Value
C-peptide Peak Estimated Difference (pmol/L)
P Value
miR-3187-3p Q2-4 vs Q1 22.49 0.0371 236 0.0383
miR-4302 Q2-4 vs Q1 21.05 0.0479 229 0.0391
miR-1292-5p Q2-4 vs Q1 n/a n/a 212 0.0496
The Table reports estimated differences in the 12-month MMTT C-peptide levels between
participant groups defined by baseline quartiles of miRNA expression. The estimated
differences are those between the quartile comparisons, as described in the legend of
Table 2.
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Table 4. Prediction of targeted gene pathways by miRNAs associated with
baseline MMTT AUC and/or peak C-peptide.
miRNAPredicted Disease Relevant KEGG Pathways
Predicted Gene Targets/ Genes in
PathwayPathway Ranking P Value
miR-98-3p Insulin signaling 63/139 17 of 18 0.0320miR-99a-5p Insulin signaling 34/139 5 of 6 0.0569
Insulin signaling 104/139 2 of 20 8.33E-06miR-103a-3pTCR signaling 80/110 11 of 20 0.0018
miR-127-3p Insulin signaling 80/139 5 of 21 0.0002TCR signaling 94/110 13 of 27 0.0005miR-193b-5pInsulin signaling 115/139 16 of 27 0.0013TCR signaling 59/110 8 of 18 0.0046miR-197-3pInsulin signaling 71/139 10 of 18 0.0064
miR-2355-3p Insulin signaling 84/139 14 of 14 0.0469miR-342-3p Insulin signaling 90/139 1 of 23 5.00E-06
TCR signaling 82/110 15 of 33 0.0002Insulin signaling 100/139 16 of 33 0.0003miR-622Type II diabetes mellitus 38/49 31 of 33 0.0381
miR-934 Insulin signaling 76/139 5 of 17 0.0017Insulin signaling 91/139 4 of 27 5.14E-05TCR signaling 72/110 14 of 27 0.0008miR-1208Type II diabetes mellitus 36/49 17 of 27 0.0049Insulin signaling 91/139 10 of 22 0.0008miR-1292-5pTCR signaling 71/110 17 of 22 0.0171Insulin signaling 101/139 1 of 16 4.76E-06miR-3187-3pTCR signaling 74/110 12 of 16 0.0230Insulin signaling 85/139 6 of 19 0.0001miR-4302TCR signaling 65/110 12 of 19 0.0094
miR-4304 Insulin signaling 57/139 3 of 15 0.0001Insulin signaling 71/139 2 of 20 3.40E-06miR-4723-5pType II diabetes mellitus 28/49 16 of 20 4.72E-03TCR signaling 49/110 9 of 21 0.0005miR-6748-3pInsulin signaling 57/139 12 of 21 0.0021Insulin signaling 76/139 3 of 12 0.0008
miR-7154-3p SNARE interactions in vesicular transport 26/29 8 of 12 0.0160
miR-8058 Insulin signaling 60/139 5 of 12 0.0002
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Disease-relevant gene pathways predicted to be targeted by miRNAs associated with C-
peptide in the primary analysis. Number of predicted genes, ranking of the reported
pathways and corrected p values are also shown.
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FIGURE LEGENDS
Fig. 1. Baseline miRNA quartile levels association with baseline C-peptide AUC and
peak levels. The figure illustrates individual C-peptide AUC and peak levels according to
miRNA expression quartiles. Data shown are mean + SD. Data are shown for 6
representative miRNAs. Differences between groups and p values after bootstrapping are
reported from Table 2.
Fig. 2. Baseline miRNA levels association with 12-month C-peptide AUC and peak
levels. The dot plots illustrate C-peptide AUC and peak levels at the 12-month visit, for
participants stratified by baseline miRNA expression quartiles. Their C-peptide AUC and
peak values are shown from baseline to the 12-month visit, and slope values are reported.
Data shown are mean + SD. Data are shown for 4 representative miRNAs: the baseline
associations of miR-3187-3p and miR-4302 with C-peptide values remained significant at
the 12-month visit, for which differences between groups and p values are reported from
Table 3. The baseline levels of miR-103a-3p and miR-197-3p were not associated with
statistically significant C-peptide differences at the 12-month visit.
Fig. 3. Combined baseline levels of selected miRNAs predict C-peptide at the
12-month visit. 12-month AUC (A, C) and peak C-peptide (B) in participant groups
defined by baseline combined levels of miR-3187-3p and miR-103a-3p (A, B) or miR-
3187-3p and miR-4302 (C). The Whisker boxes show median, 1st and 4th quartiles, and
maximum/minim values. The dot plots show individual values, mean and SD. Black
circles in the dot plots mark subjects with lower C-peptide outcome uniquely identified by
the miRNA combinations. By multivariable analysis, the miR-3187-3p/miR-103a-3p
combination identified differences between groups in AUC and peak C-peptide decline
Page 34 of 50Diabetes
35
from baseline to 12 months of 37.95 nmol/L (p=0.001) and 39 pmol/L (p=0.001),
respectively. Likewise, the miR-3187-3p/miR-4302 combination identified differences
between groups in AUC C-peptide decline of 44.86 nmol/L (p=0.001). In panels A and B,
combination 0=Q1 miR-103a-3p + Q2-4 miR-3187-3p, combination 1=Q2-4 miR-103a-3p
+ Q1 miR-3187-3p; in panel C, combination 0=Q2-4 miR-3187-3p + Q2-4 miR-4302,
combination 1=Q1 miR-3187-3p + Q1 miR-4302. Results of these analyses are reported
in supplemental Table S2. Panel D illustrates the improved ability to separate between
groups with C-peptide decline lesser or greater than 25% when the miR-3187-3p/miR-
103a combination is considered in the model. ROC AUC in the model with and without
miRNAs were 0.82 and 0.70, respectively (p=0.04).
Fig. 4. MMTT CGR curves after stratification for baseline miRNA expression
quartiles. The curves plot the mean values at 30, 60, 90, and 120 minutes (left to right)
for the baseline, 6-month and 12-month MMTTs. CGR curves are shown for miR-3187-
3p, miR-103a-3p, miR-4302, and the combination of miR-3187-3p with miR-103a-3p
(combination 0=Q1 miR-103a-3p + Q2-4 miR-3187-3p, combination 1=Q2-4 miR-103a-
3p + Q1 miR-3187-3p) and the combination of miR-3187-3p with miR-4302 (combination
0=Q2-4 miR-3187-3p + Q2-4 miR-4302, combination 1=Q1 miR-3187-3p + Q1 miR-
4302). Participants were stratified for baseline expression levels of associated miRNAs;
those in the Q1 group had a more monotonic shape of the CGR curves, which is located
upward and to the left of participants in the Q2-Q4 groups. The 6- and 12-month panels
shows the metabolic deterioration over time in both groups as is evident by the increasing
monotonicity in both and by the upward and leftward movement of the CGR curves.
Page 35 of 50 Diabetes
p=0.0018 p=0.0070 p=0.0218 p=0.0065
p=0.0156 p=0.0258 p=0.0150 p=0.0086
p=0.0272 p=0.0178 p=0.0231 p=0.0560
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C-peptide AUC C-peptide Peak
p=0.0371 p=0.0383
p=0.0479 p=0.0391
p=ns p=ns
p=ns p=ns
Page 37 of 50 Diabetes
C
A
B
Sensitivity
Specificity
- - with miRNA (AUC=0.82)… without miRNA (AUC=0.72)
p=0.04
p=0.001 p=0.001
p=0.001 p=0.001
p=0.001 p=0.001
D
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1
Supplementary Information
Supplementary Table S1
Supplementary Table S2
Supplementary Table S3
Supplementary Table S4
Supplementary Table S5
Supplementary Fig. S1
Supplementary Material
Supplementary Fig. S2
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2
Table S1. Circulating miRNAs associated with type 1 diabetes by at least 2 independent studies.
Table S1. Circulating miRNAs associated with T1D by at least 2 independent studies published (2012-2020).
Control At-risk Associated miRNAs (n=30)T1D
First author Year Study DesignNew
Onset(Y/N)
n(meanage)
n(meanage)
n(meanage)
Sample type Assay type
Numberof
miRNAsstudied
miR
-24-
3pm
iR-3
75m
iR-2
5-3p
miR
-146
a-5p
miR
-21-
5ple
t-7g-
5pm
iR-1
48a-
3pm
iR-1
81a-
5pm
iR-2
6b-5
pm
iR-2
9a-3
pm
iR-3
0e-5
pm
iR-1
03a-
3pm
iR-1
06a-
5pm
iR-1
39-5
pm
iR-1
40-5
pm
iR-1
44-5
pm
iR-1
52-3
pm
iR-1
6-5p
miR
-342
-3p
miR
-19a
-3p
miR
-20a
-5p
miR
-200
a-3p
miR
-21-
3pm
iR-2
10-3
pm
iR-2
22-3
pm
iR-2
7b-3
pm
iR-3
0c-5
pm
iR-3
4a-5
pm
iR-4
51a
miR
-93-
5p
Nielsen et al. 2012 Case-Control, C-peptide levels Y 275 (12) 151 n/a serum Sequencing/qPCR 240/47 X X X X X X X X X X X XLatreille et al. 2015 Case-Control N 38 (43.6) 51 (40.8) n/a plasma TLDA qPCR 1 XMarchand et al. 2016 Case-Control Y 22 (9.8) 10 (9.9) n/a serum TLDA qPCR 1 XSeyhan et al. 2016 Case-Control N 16 (25.9) 27 (25.3) n/a plasma TLDA qPCR 28 X X X X XYin et al. 2016 At-risk relatives n/a n/a n/a 35 (n/a) serum TLDA qPCR 754 X XErener et al. 2017 Case-Control Y 38 (8.9) 32 (8.8) n/a plasma Exiqon LNA qPCR 745 X X X X X X X XSamandari et al. 2017 C-peptide levels Y 40 (8.7) n/a n/a plasma Exiqon LNA qPCR 745 X X X XSnowhite et al. 2017 At-risk relatives n/a n/a n/a 150 (11) serum Exiqon LNA qPCR 93 X X X X X X X X XAkerman et al. 2018 Case-Control, At-risk relatives Y 8 (11.7) 17 (11.8) 21 (10.2) serum Exiqon LNA qPCR 179 X X X X X X X X X X X X X X X X X X X X X X XLakhter et al. 2018 Case-Control Y 19 (10.5) 16 (10.5) n/a serum/exosomes Digital droplet PCR 1 X X X XGrieco et al. 2018 Case-Control N 15 (32) 14 (28) n/a serum TLDA qPCR 6 X XLiu et al. 2018 Case-Control Y 73 (22) 85 (21) n/a serum TLDA qPCR 6 XAssmann et al. 2018 Case-Control N 33 (19.5) 26 (21.5) 0 plasma TLDA qPCR 45 X X X XMałachowska et al. 2018 Case-Control Y 9 (n/a) 10 (n/a) n/a serum Exiqon LNA qPCR 752 X XSamandari et al. 2018 C-peptide levels Y 40 (8.7) n/a n/a serum/plasma Exiqon LNA qPCR 179 XBertoccini et al. 2019 Case-Control, At-risk relatives Y 49 (16.1) 48 (41.2) 46 (26.8) serum TLDA qPCR 1 XLiu et al. 2019 Case-Control N 29 (24) 19 (30) n/a serum In house qPCR 4 X X X XGaravelli et al. 2020 Case-Control, C-peptide levels Y 88 (8.9) 47 (8.4) n/a plasma Exiqon LNA qPCR 60 XGaravelli et al. 2020 Case-Control, C-peptide levels Y 88 (8.9) 47 (8.4) n/a plasma Exiqon LNA qPCR 60 X
8 6 6 6 4 3 3 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2TOTAL STUDIES REPORTING
In a review of the published literature last updated on October 29, 2020 we find that circulating levels of 30 miRNAs were associated with type 1 diabetes by at least 2 published studies and 11 miRNAs were reported by at least 3 studies, as indicated in the last row of the table. These 11 miRNAs are: miR-24-3p, miR-375, mir-25-3p, miR-146-3p, miR-21-5p, let-7g-5p, miR-148a-3p, miR-181a-5p, miR-26b-5p, miR-29a-3p, and miR-30e-5p. This Table only includes 19 studies examining association of circulating miRNAs in autoantibody-positive at-risk relatives (4 studies), case-control studies (n=15), or investigations of miRNAs in relation to C-peptide levels after the onset of type 1 diabetes (n=5). Virtually all studies used RT-PCR assays and the number of miRNAs examined ranged between 1 and 754, with 13/19 studies examining fewer than 100 miRNAs, 7<10 miRNAs; Nielsen et al (2012) used sequencing of pooled samples and then RT-PCR to assess levels of 47 miRNAs. All papers listed in this table are referenced in the manuscript.
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Table S2. Combinations of miRNAs predict change in C-peptide AUC and Peak between
baseline and 12 months.
______________________________________________________________________
Estimate Std. Error t value Pr(>|t|)Intercept -39.5511 20.95 -1.888 0.06551BMI 2.6036 1.1169 2.331 0.02429 *Age at draw 0.3008 0.4802 0.626 0.53419Sex -3.8242 8.0189 -0.477 0.63574Baseline C-Peptide AUC -0.7337 0.1314 -5.583 1.3e-06 ***COMBINATION 103a-3p/3187-3p 37.9503 11.3019 3.358 0.0016 **
Multiple R-squared: 0.4418, Adjusted R-squared: 0.3798 F-statistic: 7.124 on 5 and 45 DF, p-value: 5.551e-05Baseline-12 months C-peptide AUC difference: 37.9 mmol/l
Estimate Std. Error t value Pr(>|t|)Intercept -0.404444 0.220724 -1.832 0.07352BMI 0.024643 0.011931 2.065 0.04467 *Age at draw 0.00538 0.005116 1.052 0.29854Sex -0.031963 0.084778 -0.377 0.70793Baseline C-Peptide Peak -0.73719 0.130452 -5.651 1.03e-06 ***COMBINATION 103a-3p/3187-3p 0.39958 0.120168 3.325 0.00176 *
Multiple R-squared: 0.4413, Adjusted R-squared: 0.3792F-statistic: 7.108 on 5 and 45 DF, p-value: 5.67e-05Baseline-12 months C-peptide Peak difference: 0.39 mmol/l
Estimate Std. Error t value Pr(>|t|)Intercept -38.1881 20.8928 -1.828 0.07421BMI 2.6424 1.1132 2.374 0.02194 *Age at draw 0.3338 0.4759 0.701 0.48666Sex -4.2175 7.9992 -0.527 0.60062Baseline C-Peptide AUC -0.7489 0.1326 -5.65 1.03e-06 ***COMBINATION 3187-3p/4302 44.8617 13.0642 3.434 0.00129 **
Multiple R-squared: 0.4469, Adjusted R-squared: 0.3855F-statistic: 7.272 on 5 and 45 DF, p-value: 4.59e-05Baseline-12 months C-peptide AUC difference: 44.86 mmol/L
______________________________________________________________________
The table reports the detailed results of the analysis for the data shown in Fig. 3.
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Table S3. Longitudinal comparisons of AUC C-peptide/Glucose ratios.
miR-3187-3p miR-3187-3p miR-3187-3pQ1: Baseline Q1: 6-Month Q1: Baseline Q1: 12-Month Q1: 6-Month Q1: 12-Month
N 13 13 13 13 13 13Mean + SD 1.06 + 0.30 0.09 + 0.05 1.06 + 0.30 0.07 + 0.05 0.09 + 0.06 0.07 + 0.05
Paired T-test p=0.0002 p=0.0002 p=0.0063Q2-4: Baseline Q2-4: 6-Month Q2-4: Baseline Q2-4: 12-Month Q2-4: 6-Month Q2-4: 12-Month
N 35 35 39 39 35 35Mean + SD 0.57 + 0.26 0.04 + 0.03 0.58 + 0.26 0.03 + 0.02 0.04 0.03 + 0.02
Paired T-test p<0.0001 p<0.0001 p<0.0001
miR-103a-3p miR-103a-3p miR-103a-3p Q1: Baseline Q1: 6-Month Q1: Baseline Q1: 12-Month Q1: 6-Month Q1: 12-Month
N 12 12 13 13 12 12Mean + SD 0.55 + 0.34 0.03 + 0.03 0.38 + 0.34 0.02 + 0.01 0.03 + 0.02 0.01 + 0.01
Paired T-test p=0.0005 p=0.0002 p=0.0256 Q2-4: Baseline Q2-4: 6-Month Q2-4: Baseline Q2-4: 12-Month Q2-4: 6-Month Q2-4: 12-Month
N 36 36 39 39 35 35Mean 0.76 + 0.33 0.06 + 0.05 0.75 + 0.32 0.04 + 0.03 0.06 + 0.06 0.04 + 0.04
Paired T-test p<0.0001 p<0.0001 p=0.0007
3187-3p/miR-103a-3p 3187-3p/miR-103a-3p 3187-3p/miR-103a-3p 1: Baseline 1: 6-Month 1: Baseline 1: 12-Month 1: 6-Month 1: 12-Month
N 11 11 11 11 11 11Mean + SD 1.05 + 0.29 0.09 + 0.06 1.05 + 0.05 0.10 + 0.05 0.09 + 0.06 0.10 + 0.06
Paired T-test p=0.0010 p=0.0010 p=0.0264 0: Baseline 0: 6-Month 0: Baseline 0: 12-Month 0: 6-Month 0: 12-Month
N 37 37 41 41 36 36Mean + SD 0.60 + 0.29 0.04 + 0.03 0.61 + 0.29 0.03 + 0.02 0.04 + 0.03 0.03 + 0.01
Paired T-test p<0.0001 p<0.0001 p=0.0052 miR-4302 miR-4302 miR-4302
Q1: Baseline Q1: 6-Month Q1: Baseline Q1: 12-Month Q1: 6-Month Q1: 12-MonthN 13 13 13 13 13 13
Mean + SD 0.90 + 0.37 0.08 + 0.06 0.90 + 0.37 0.06 + 0.04 0.08 + 0.06 0.06 + 0.04Paired T-test p=0.0002 p=0.0005 p=0.0017
Q2-4: Baseline Q2-4: 6-Month Q2-4: Baseline Q2-4: 12-Month Q2-4: 6-Month Q2-4: 12-MonthN 35 35 39 39 35 35
Mean + SD 0.63 + 0.30 0.04 + 0.04 0.63 + 0.30 0.03 + 0.03 0.04 + 0.04 0.03 + 0.03Paired T-test p<0.0001 p<0.0001 p<0.0001 miR-3187-3p/4302 miR-3187-3p/4302 miR-3187-3p/4302
1: Baseline 1: 6-Month 1: Baseline 1: 12-Month 1: 6-Month 1: 12-MonthN 8 8 8 8 8 8
Mean + SD 1.08 + 0.31 0.10 + 0.06 1.08 + 0.31 0.07 + 0.04 0.10 + 0.06 0.07 + 0.04Paired T-test p=0.0078 p=0.0078 p=0.5469
0: Baseline 0: 6-Month 0: Baseline 0: 12-Month 0: 6-Month 0: 12-MonthN 40 40 44 44 39 39
Mean + SD 0.63 0.04 0.64 0.03 0.04 0.03Std.
Deviation 0.30 0.04 0.29 0.03 0.04 0.03Paired T-test p<0.0001 p<0.0001 p=0.0122
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Table S3 reports full results of the longitudinal comparisons of the AUC C-peptide/Glucose ratios from the curves shown in Fig. 4, for the indicated quartiles of individual miRNAs, or for combinations of miRNAs, in which case the combined quartiles of expression are indicated as “0” or “1”. For miR-3187-3p/miR-103a-3p, combination 0= Q1 miR-103a-3p + Q2-4 miR-3187-3p, combination 1= Q2-4 miR-103a-3p + Q1 miR-3187-3p; for miR-3187-3p/miR-4302, 0= Q2-4 miR-3187-3p + Q2-4 miR-4302, combination 1= Q1 miR-3187-3p + Q1 miR-4302. Statistically significant changes occur for each of the two groups of patients defined by miRNA levels, consistent with the disease natural history. However, 6-month and 12-month curves of miR-3187-3p/miR-4302 were statistically different from each other for participants in the combination group 0, but not for those in combination group 1, suggesting that the latter did not experience significant worsening in this time interval.
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Table S4. Cross-sectional comparisons of AUC C-peptide/Glucose ratios.
miR-3187-3p miR-3187-3p miR-3187-3p Q1: Baseline Q2-4: Baseline Q1: 6-Month Q2-4: 6-Month Q1: 12-Month Q2-4: 12-Month
N 13 40 13 35 13 39Mean + SD 1.06 + 0.30 0.59 + 0.26 0.09 + 0.06 0.05 + 0.03 0.07 + 0.05 0.03 + 0.02
Paired T-test p<0.0001 p=0.0004 p=0.0007
miR-103a-3p miR-103a-3p miR-103a-3p Q1: Baseline Q2-4: Baseline Q1: 6-Month Q2-4: 6-Month Q1: 12-Month Q2-4: 12-Month
N 13 40 12 36 13 39Mean + SD 0.38 + 0.64 0.60 + 0.93 0.03 + 0.02 0.06 + 0.01 0.02 + 0.01 0.05 + 0.04
Paired T-test p=0.0140 p=0.0303 p=0.0557 3187-3p/miR-103a-3p 3187-3p/miR-103a-3p 3187-3p/miR-103a-3p
1: Baseline 0: Baseline 1: 6-Month 0: 6-Month 1: 12-Month 0: 12-MonthN 11 42 11 37 11 41
Mean + SD 1.05 + 0.29 0.61 + 0.28 0.09 + 0.06 0.04 + 0.03 0.07 + 0.05 0.03 + 0.02Paired T-test p=0.0001 p=0.0005 p=0.0004 miR-4302 miR-4302 miR-4302
Q1: Baseline Q2-4: Baseline Q1: 6-Month Q2-4: 6-Month Q1: 12-Month Q2-4: 12-MonthN 13 40 13 35 13 39
Mean + SD 0.90 + 0.37 0.64 + 0.30 0.08 + 0.06 0.04 + 0.04 0.06 + 0.04 0.03 + 0.03Paired T-test p=0.0268 p=0.0086 p=0.0397
miR-3187-3p/4302 miR-3187-3p/4302 miR-3187-3p/4302 1: Baseline 0: Baseline 1: 6-Month 0: 6-Month 1: 12-Month 0: 12-Month
N 8 45 8 40 8 44Mean + SD 1.08 + 0.31 0.63 + 0.29 0.10 + 0.06 0.04 + 0.04 0.07 + 0.04 0.03 + 0.03
Paired T-test p=0.0007 P<0.0001 p=0.0003
Table S4 reports full results of the cross-sectional comparison of the AUC C-peptide/Glucose ratios from the curves shown in Fig. 4, for the indicated quartiles of individual miRNAs, or for combinations of miRNAs, in which case the combined quartiles of expression are indicated as “0” or “1”. For miR-3187-3p/miR-103a-3p, combination 0= Q1 miR-103a-3p + Q2-4 miR-3187-3p, combination 1= Q2-4 miR-103a-3p + Q1 miR-3187-3p; for miR-3187-3p/miR-4302, 0= Q2-4 miR-3187-3p + Q2-4 miR-4302, combination 1= Q1 miR-3187-3p + Q1 miR-4302. The findings suggest significant differences in disease progression identified by stratification in groups defined by baseline miRNA levels.
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Table S5. Total raw counts, raw CPM, and normalized CPM (log2) observed for the 31 miRNAs associated with C-peptide AUC and or peak in the primary analysis.
Total Raw Counts Raw CPM Normalized CPM (log2)miRNA Average Median SD Average Median SD Average Median SDmiR-103a-3p 708.89 552 601.22 216.09 194.99 125.07 7.43 7.54 0.84miR-1208 455.15 235 649.40 129.18 80.12 119.64 6.17 6.31 1.65miR-127-3p 80.19 54 108.08 23.36 18.58 17.55 4.04 4.17 1.06miR-1292-5p 203.58 113 266.23 59.30 42.46 52.42 5.13 5.34 1.47miR-193b-5p 272.943 183 311.91 80.59 69.30 54.68 5.85 5.87 0.99miR-197-3p 563.91 477 386.48 174.93 163.45 72.95 7.23 7.29 0.65miR-215-5p 400.75 204 555.05 115.18 78.34 105.67 6.07 6.26 1.41miR-2355-3p 417.66 227 618.02 119.82 85.13 116.27 6.11 6.13 1.35miR-3187-3p 255.96 126 367.77 72.39 49.84 65.36 5.43 5.62 1.36miR-3191-3p 276.79 173 342.07 82.02 55.49 73.73 5.61 5.59 1.35miR-342-3p 484.98 414 497.72 144.52 126.64 93.03 6.69 6.89 1.09miR-3678-3p 362.25 199 525.68 102.85 66.30 96.02 5.92 6.00 1.36miR-4302 390.58 222 499.95 113.51 71.15 93.65 6.23 6.08 1.15miR-4304 443.13 272 503.33 131.40 92.54 97.79 6.51 6.38 1.09miR-4669 404.08 222 505.62 118.02 69.82 96.81 6.32 6.02 1.10miR-4701-3p 434.49 279 588.86 124.72 92.29 109.44 6.29 6.29 1.20miR-4723-5p 247.15 124 361.32 70.25 44.24 67.29 5.34 5.22 1.39miR-494-5p 323.17 173 480.73 91.69 59.38 86.41 5.74 5.84 1.42miR-568 435.66 181 653.15 125.12 74.24 127.33 5.92 5.99 1.69miR-5682 366.94 182 545.68 105.19 62.00 103.12 5.75 5.82 1.69miR-589-5p 423.66 238 557.65 123.11 83.55 107.92 6.24 6.16 1.30miR-6073 404.34 176 608.82 116.03 71.13 118.42 5.83 5.85 1.85miR-622 397.32 222 522.23 114.30 81.30 95.62 6.24 6.23 1.14miR-6506-5p 395.55 186 563.44 112.87 71.10 104.45 6.04 6.07 1.35miR-6748-3p 509.98 390 474.48 155.39 125.36 92.58 6.88 6.94 0.99miR-7154-3p 472.23 240 646.18 137.49 89.10 124.78 6.36 6.36 1.35miR-8058 342.83 154 499.62 98.79 63.17 96.36 5.70 5.84 1.58miR-8079 379.72 213 504.70 110.03 72.06 92.16 6.17 6.10 1.22miR-934 270.96 113 426.06 76.84 41.68 81.73 5.25 5.33 1.66miR-98-3p 191.42 94 267.90 56.39 35.23 54.12 4.95 4.95 1.51miR-99a-5p 535.47 383 530.25 159.66 131.07 94.54 6.96 7.00 0.89
Average 382.3 226.5 482.9 111.6 79.4 91.5 6.0 6.0 1.3Median 397.3 204.0 504.7 114.3 71.1 95.6 6.1 6.1 1.3SD 122.8 112.0 128.5 37.8 36.8 25.0 0.7 0.7 0.3Quartile 25% 300.0 173.0 406.3 86.9 60.7 77.7 5.7 5.8 1.1Quartile 75% 439.4 239.0 560.5 127.2 87.1 106.8 6.3 6.3 1.4
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Fig. S1. C-peptide AUC Decline in the Study Cohort
C-peptide AUC and peak levels for individual study participants (panel A) and as means+ SD (panel B) at the baseline, 6-month and 12-month MMTT. In panel B, statisticaldifferences among the time points demonstrate significant C-peptide decline (Mann-Whitney test). Panel C illustrates the statistically significant decline of C-peptide AUCand peak observed in the cohort from baseline to the 12-month MMTT; significance wasestimated using the Wilcoxon matched pairs signed rank test. Data are shown for 52/53participants since a single subject did not have 12-month MMTT data; at 6 months, 4subjects did not have MMTT data. Data are plotted on a Log2 scale.
Baseline 6 Month 12 Month1248
163264
128256
C-p
eptid
eA
UC
(nm
ol/L
)
N=52 N=49 N=52
Baseline 6 Month 12 Month1
4
16
64
256
1024
4096
Peak
C-p
eptid
e(p
mol
/L)
N=52 N=49 N=52
C-peptide AUC C-peptide PeakA
B
C
Baseline 12-Month0
50
100
150
200
C-p
eptid
eA
UC
(nm
ol/L
) p<0.0001
Baseline 12-Month8
163264
128256512
10242048
Peak
C-p
eptid
e(p
mol
/L)
p<0.0001
Baseline 6 Months 12 Months1248
163264
128256
C-p
eptid
eA
UC
(nm
ol/L
)
N=52 N=49 N=52
p=0.0028
p<0.0001
p<0.0001
Baseline 6 Months 12 Months1
4
16
64
256
1024
4096C
-pep
tide
AU
C(n
mol
/L)
N=52 N=49 N=52
p=0.0179
p<0.0001
p<0.0001
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Supplementary material
Blood Processing. Serum samples used in this study were provided by the Type 1
Diabetes TrialNet. Samples were obtained from participants at various TrialNet sites and were
uniformly collected and processed according to the TrialNet processing SOPs. Ot obtain
serum, blood was collected in 2.5 mL red top SST gel tube. The tube was gently inverted 5
times and placed upright in a tube rack. The blood was allowed to clot for 20-30 minutes at
room temperature, then it was centrifuged for 15 minutes. The serum was transferred into a
1.8 mL cryovial, placed upright in a 2” partitioned freezer storage box, then frozen at -70°C.
Assessment of Hemolysis. Only visually apparent hemolysis interferes with hybrid-
capture based assays and this was never observed at visual checks performed before sample
submission and before processing. In miRNA RT-PCR assays hemolysis is present when the
miR-23a-3p/miR-451a Cq ratio of is >7 (1) or >9 (2), as reported in different studies. In our
data, this translates to differential expression levels of miR-23a-3p/miR-451 greater than 128
or 512-fold, respectively, due to the binary logarithmic nature of Cq-values. The observed
difference was much lower (mean 13.6 ± SD 18.5) than 128-fold. Thus, hemolysis levels were
satisfactorily low in all samples.
Assessment of platelet contribution. Applicable to all studies of circulating miRNAs, the
study of serum or plasma samples has the limitation that circulating miRNAs reflect a variety
of cellular sources, including platelets. Serum typically contains fewer platelets than plasma
when processed by standard clinical collection protocols with normal CBC platelet counts of
~200,000/mL in whole blood, ~28,000/mL plasma, and <1000/mL serum. Thus, since we used
serum, the possible contribution from platelets would be much reduced compared to studies
that used plasma. We are not aware of reports of truly platelet-specific miRNAs. However,
several miRNAs have been linked to platelet activation or are expressed also by platelets.
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Figure S2 shows median and interquartile ranges of raw CPM values, in the Log2 scale, for
the 31 miRNAs associated with C-peptide in this study and 50 miRNAs that could be commonly
contributed by platelets (albeit not exclusively) (3). Overall, the miRNAs associated with C-
peptide had significantly lower expression levels than platelet miRNAs (p<0.0001). Moreover,
miRNAs associated with platelets were not a key contributor to the main associations reported
in this study because only 3 of the miRNAs associated with C-peptide overlapped with those
linked to platelets: these are miR-103a-3p, miR-342-3p, and miR-197-3p. As described in the
main text, these three miRNAs have been linked to type 1 diabetes by multiple studies.
References1. Blondal T, Jensby Nielsen S, Baker A, Andreasen D, Mouritzen P, Wrang Teilum M, Dahlsveen IK: Assessing sample and miRNA profile quality in serum and plasma or other biofluids. Methods (San Diego, Calif) 2013;59:S1-6
2. Zhelankin AV, Vasiliev SV, Stonogina DA, Babalyan KA, Sharova EI, Doludin YV, Shchekochikhin DY, Generozov EV, Akselrod AS: Elevated Plasma Levels of Circulating Extracellular miR-320a-3p in Patients with Paroxysmal Atrial Fibrillation. International journal of molecular sciences 2020;21
3. Sunderland N, Skroblin P, Barwari T, Huntley RP, Lu R, Joshi A, Lovering RC, Mayr M: MicroRNA Biomarkers and Platelet Reactivity: The Clot Thickens. Circ Res 2017;120:418-435
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Snowhite et al.
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Fig. S2. Median and interquartile ranges for 31 miRNAs associated with C-peptide in this study
compared to miRNAs associated with platelets in the literature.
31C-pep
tide Ass
ociated
miRNAs
Platele
t miRNAs
0.0009765625
0.03125
125
210
215
220
Raw
Cou
nts
perM
illio
nR
eads
(CPM
) miR-103a-3pmiR-197-3pmiR-342.-3p
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