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Epigenetic changes related to glucose metabolism in type 1 diabetes
after BCG vaccinations: A vital role for KDM2B
Hans F. Dias, Willem M. Kühtreiber, Kacie J. Nelson, Nathan C. Ng, Hui Zheng 1, Denise L. Faustman ⇑a r t i c l e

i n f oArticle history:
Available online xxxx
Keywords:
Diabetes
BCG vaccine
Adaptive immunity
KDM2B
DDIT4
Histone lysine demethylase
Oxidative phosphorylationa b s t r a c t
Background: A recent epigenome-wide association study of genes associated with type 2 diabetics (T2D),
used integrative cross-omics analysis to identify 22 abnormally methylated CpG sites associated withinsulin and glucose metabolism. Here, in this epigenetic analysis we preliminarily determine whether
the same CpG sites identified in T2D also apply to type 1 diabetes (T1D). We then determine whether
BCG vaccination could correct the abnormal methylation patterns, considering that the two diseases
share metabolic derangements.
Methods: T1D (n = 13) and control (n = 8) subjects were studied at baseline and then T1D subjects studied
yearly for 3 years after receiving BCG vaccinations in a clinical trial. In this biomarker analysis, methylation patterns were evaluated on CD4+ T-lymphocytes from baseline and yearly blood samples using thehuman Illumina Methylation EPIC Bead Chip. Methylation analysis combined with mRNA analysis using
RNAseq.
Results: Broad but not complete overlap was observed between T1D and T2D in CpG sites with abnormal
methylation. And in the three-year observation period after BCG vaccinations, the majority of the abnormal methylation sites were corrected in vivo. Genes of particular interest were related to oxidative phosphorylation (CPT1A, LETM1, ABCG1), to the histone lysine demethylase gene (KDM2B), and mTOR signaling
through the DDIT4 gene. The highlighted CpG sites for both KDM2B and DDIT4 genes were hypomethylated at baseline compared to controls; BCG vaccination corrected the defect by hypermethylation.
Conclusions: Glycolysis is regulated by methylation of genes. This study unexpectedly identified both
KDM2B and DDIT4 as genes controlling BCG-driven re-methylation of histones, and the activation of
the mTOR pathway for facilitated glucose transport respectively. The BCG effect at the gene level was
confirmed by reciprocal mRNA changes. The DDIT4 gene with known inhibitory role of mTOR was remethylated after BCG, a step likely to allow improved glucose transport. BCGs driven methylation of
KDM2B’s site should halt augmented histone activity, a step known to allow cytokine activation andincreased glycolysis.
Ó 2021 Elsevier Ltd. All rights reserved.

1. Introduction
Abbreviations: BCG, Bacillus Calmette-Guérin; EWAS, Epigenome-wide association study; DDIT4, DNA-damage-inducible transcript 4 protein; KDM2B, Lysine
demethylase 2B; T1D, Type 1 Diabetes; T2D, Type 2 Diabetes; CpG, Regions of DNA
where a cytosine nucleotide is immediately followed by a guanine nucleotide on
the same strand in a 50 to 30 direction; OXPHOS, Oxidative Phosphorylation; FAO,
Fatty Acid Oxidation.
⇑ Corresponding author at: Harvard Medical School and Massachusetts General
Hospital, Immunobiology Laboratory, 13th Street, Building 149, Rm 3602, Boston,
MA 02129, United States.
E-mail addresses: HDIAS@mgh.harvard.edu (H.F. Dias), WKUHTREIBER@mgh.
harvard.edu (W.M. Kühtreiber), KNELSON15@mgh.harvard.edu (K.J. Nelson),
NNG1@mgh.harvard.edu (N.C. Ng), hzheng1@mgh.harvard.edu (H. Zheng), dfaustman@mgh.harvard.edu (D.L. Faustman).
1
Statistics Department, Massachusetts General Hospital 50 Saniford Street, Boston
Massachusetts, United States.

First used in 1921, the Bacillus Calmette-Guerin (BCG) vaccine
is primarily used prophylactically for tuberculosis. It is a live attenuated strain of Mycobacterium bovis and is one of the safest vaccines in production, with over 4 billion people vaccinated globallyand 100 million newborn children vaccinated each year [1,2]. Since
the 1970s, the vaccine was proven to be efficacious for intravesicaltreatment of bladder cancer [3–5], and more recently, has shown
surprising off-target human benefits, including protection against
diverse infections, protection from allergies, and significant protection against autoimmune diseases such as multiple sclerosis andtype 1 diabetes (T1D) [6–23].

https://doi.org/10.1016/j.vaccine.2021.04.011
0264-410X/Ó 2021 Elsevier Ltd. All rights reserved.

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cinations: A vital role forMay
KDM2B,
Vaccine,https://doi.org/10.1016/j.vaccine.2021.04.011
14, 2021.
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in ABCG1, and the 4p15.33 region were associated with fasting
insulin only.
Here we study methylation alterations in gene regions associated with T1D DNA samples compared to control samples. We target the above mentioned CpG associated regions and genes that are
differentially methylated and impact fasting insulin, fasting glucose, and glucose metabolism. Next, we study those same insulin,
glucose associated CpG regions and genes after multi-dose BCG
vaccine therapy in a 3-year clinical trial with adults with longstanding T1D. We also study the downstream effects on mRNA
expression. These studies especially ask whether BCG therapy
can correct abnormal methylation patterns associated with insulin
secretion, fasting glucose and glucose metabolism. In the course ofanswering these questions, we uncovered an upstream gene that
controls BCG-driven histone methylation and demethylation. This
likely results in increased levels of histone 3 lysine 4 trimethylation (H3K4me3). We also confirm an undermethylated CpG sitein T1D that is related to overlapping mTOR signaling defects inboth T1D and T2D and is re-methylated by BCG in vivo therapy.

The mechanisms behind these off-target or heterologous
immune benefits appear to be diverse and may partly be derived
from the ability of this microorganism to reset host immune andmetabolic functions, even at the DNA level. This concept of modulated methylation of host DNA in monocytes by microorganisms
originated in plants but also applies to humans in the conceptreferred to as ‘‘trained immunity” a refinement of innate immunity[24–28]. The epigenetic DNA changes in human host DNA havelikely evolved to result in long term commensalism by select andoften ancient organisms including their close relative tuberculosis
i.e. Mycobacterium tuberculosis. BCG vaccination or tuberculosis
infection, also result in changes to adaptive immunity and thiscan be measured by the upregulation of host Regulatory T Cells(Treg) genes to prevent host immune detection [9,12]. Additionally, infected host myeloid cells are modified into greater utilization of aerobic glycolysis for preferential sugar metabolism
through epigenetic changes. A step believed by some to relate to
BCG replication and therapeutic effect on blood sugars in T1D[29,30]. In human clinical trials with adult vaccinations of BCG
with underlying T1D, this gradually reestablishes commensalism(over a number of years) and results in predictable epigenetic
changes in DNA obtained from various subpopulations of lymphocytes [12,30]. This concept goes hand-in-hand with the hygiene
hypothesis. It is only in the modern era that the sustained exposures to these ancient microbes disappeared, such as in the soil
or water [31]. Recent human data shows a reset of T cells andmonocytes after BCG vaccinations, thus an influence of BCG on
innate and adaptive immunity. Furthermore, BCG vaccinations
may exert an affect at the level of the hematopoietic progenitor
stem cell compartment [32], suggesting a mechanism for the longterm and durable effects from BCG.
It is now well-established that human disease can be driven byaltered methylation patterns, often triggered by environmental
exposures affecting gene expression. Although T1D and type 2
diabetes (T2D) are different diseases, both are modulated by theenvironment affecting disease incidence and both have glucose
and insulin dysregulation and a strong role for epigenetics inthe control of disease expression [33–35]. These environment
exposures can be in the context of changed methylation patterns.
For T2D, the environmental influences are often contributing toworsening disease, such as smoking and obesity [36]. In T1D,
the environmental influences are often described as preventative,
the basis for the Hygiene Hypothesis and protection after certain
beneficial microbiologic exposures [34,35]. Abundant T2D datafrom cross-omics and pure DNA analysis approaches have identified altered methylation sites of glucose and insulin homeostasisby these massive EWAS studies and this has allowed strong confirmation of the identified methylation errors with very large
sample numbers [33]. In T1D reproducibility of epigenetic differences between control and T1D DNA sample have been less confirmed but a study has identified a CpG site in DDIT4 as apotential candidate by comparing DNA samples from discordant
identical twins [37].
A recent publication identified a list of 22 differentially methylated CpGs that were associated with early phases of glucose intolerance in an Epigenome-Wide Association Study (EWAS) of 4808
non-diabetic individuals [38]. These CpGs were associated witheither fasting glucose, fasting insulin, or both, and 13 of the 22
had been found in previous EWAS. Out of the novel associations,
CpGs in LETM1, RBM20, IRS2, MAN2A2, and the 1q25.3 region wereassociated with fasting insulin, and CpGs in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region were associated with fasting glucose [38]. Of those previous associations with Type 2 Diabetic(T2D) traits, CpGs in SLC7A11, CPT1A and SREBF1 had been associated with both fasting glucose and insulin, and the CpGs in
DHCR24, CPT1A, RNF145, ASAM, KDM2B, MYO5C, TMEM49, two

2. Materials and methods
2.1. Research subjects and human consent
All human studies had full institutional approvals through Massachusetts General Hospital and Partners Health Care, and composed of open and closed label subjects consented throughvarious protocols (Study# 2007P001347, 2012P002243 and2013P002633). The BCG interventional studies were also formallyapproved by the FDA (IND#2007P001347 and IND#2013P16434).
All blood donors, both T1D and non-diabetic control (NDC) subjects
consented through Study #2001P001379. Informed consent was
obtained from all subjects and the experiments conformed to theprinciples set out in the WMA Declaration of Helsinki and theDepartment of Health and Human Services Belmont Report. This
study included 13 T1D subjects, where the timing of BCG vaccinations and serial blood sampling times for visits were baseline (preBCG vaccine), year 01, year 02 and year 03. All patients were given
two initial intradermal BCG vaccinations, the first at baseline and asecond vaccine four weeks later. Non-diabetic control subjects(n = 8) were also studied and compare against T1D patients. The
T1D have a mean age of 46 years, average age of disease onset of
25 years, and an average of 20 years of disease duration. All individuals were derived from a random sample of subjects and areunrelated to each other.

2.2. Isolation of lymphocytes from whole blood
Lymphocytes of CD4 subset were isolated from blood that wascollected in purple tops (K2-EDTA anticoagulant) using magnetic
Easysep Direct Human CD4+ T Cell Isolation Kits from Stem Cell
Technologies (Vancouver, BC, Canada), following the instructionsof the manufacturer. Briefly, 1200 lL of Isolation Cocktail and1200 lL of Rapid Spheres were mixed with 24 mL of whole bloodin a 50 mL centrifuge tube and incubated for 5 min at room temperature. Twenty-four milliliters of Ca- and Mg-free PBS was thenadded, and the tube placed into an ‘‘Easy 50” magnet (Stem Cell
Technologies). This immobilized the unwanted cells at the side of
the tube. After 10 min, the CD4 enriched cell suspension was transferred into a new tube and the magnetic separation processrepeated for 5 min with fresh Rapid Spheres. The resulting highly
CD4 enriched cell suspension was transferred into a new tube
and purified for a third time using the magnet. The resulting final
CD4 T cell preparations had purities of >95%.
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2.3. Methylation analysis

3. Results

Genomic DNA (gDNA) from lymphocytes of the CD4 T cell subset was isolated in the laboratory, and methylation patterns wereanalyzed as described by the Partners Personalized Medicine
Translational Genomics Core using the Human Infinium Methylation EPIC Bead Chip Kit (Illumina, San Diego, CA). This chip targets
over 850,000 known and potential human DNA methylation sites.
DNA methylation levels for particular CpGs (Illumina CpG Database Identifier), were expressed as beta values (b = intensity ofthe methylated allele (M) / (intensity of the unmethylated allele(U) + intensity of the methylated allele (M) + 100)). A beta valueof 0 defined the CpG to be fully demethylated, and a value of 1
being fully methylated. The data for the relevant genes and thebeta values for the CpGs were extracted using fgrep through theUnix command line. Data processing, heatmap creation, and statistical analyses was carried out on Microsoft Excel Version 16.38(20061401) for Mac, Graph pad Prism Version 8.4.3 (471), the R
program and the G* Power 3.1 software.

3.1. Baseline evaluation of T1D CpG sites to control DNA methylationsites; relationship to fasting glucose and insulin metabolism
Some DNA methylation alterations in T2D lymphocytes, both
hyper and hypo-methylation are associated with dysfunctional
fasting insulin, fasting glucose and glucose homeostasis [38]. We
first studied T1D DNA compared to control DNA for similar methylation alterations at these strategic CpG sites similarly using DNA
samples derived from lymphocytes. Of the 22 T2D identified CpG
or genes associated with altered glucose or insulin control, 20 CpGs
were represented on our Illumina EPIC Bead Chips, and so werestudied in T1D DNA samples compared to control samples. The
methylation levels of 13 of the 20 T2D high-risk CpGs were alteredin the same direction for T1D as for T2D, either with hypermethylation or with hypomethylation compared to control DNA (Fig. 1,
circled values). In three cases these cgs were statistically significant (ABCG cg06500161, CPT1A cg00574958 and CPT1A
cg17058475). The CpG within the SLAMF1 gene showed no difference between T1D and control, and was excluded from Fig. 1. The
remaining six CpGs were in the opposite direction, of which the
CpG for KDM2B cg13708645 was significant (Fig. 1). Of the four
significant CpGs (p-value cut off of < 0.05) three met a false discovery rate q-value cut off of < 0.1 (CPT1A cg00574958 (0.002), CPT1A
cg17058475 (0.077) and KDM2B cg13708645 (0.086). The results
suggest that for 13 out of 20 studied CpG sites in T1D a possible
similar directional methylation error was occurring at strategic
DNA methylation sites as previously found in the T2D crossomics study and associated with glucose and insulin control. Of
the CpG sites that were not in the same direction in T1Ds, 5 outof 6 of them were associated with high fasting insulin levels, with
SLC7A11 cg06690548 also being associated with high fasting glucose. This is an expected outcome due to T1Ds inability to produce
insulin.
Table 1 provides a summary of the CpGs identified in T2D andtheir relevant gene functions (data pulled from GeneCard, [39]),
including their association with fasting glucose or fasting insulin.
Of particular interest is the observation that three CpGs within
two genes (CPT1A and LETM1) were associated with mitochondrial
processes. This is of interest since in T1D there is overactive
OXPHOS in the mitochondrial organelles of lymphoid cells; cells
that are deprived of balanced energy metabolism due to deficientaerobic glycolysis, a state of greater glucose utilization [29,30].
Typically, T2D studies analyze whole blood, this was also the casefor the cross-omics paper. In comparison, we specifically used CD4lymphocytes, which may have resulted in missed trends.

2.4. mRNA isolations and analysis
Total RNA was extracted from isolated CD4 T cells using the
RNeasy Plus Mini Kit of Qiagen (Qiagen Sciences, MD, Cat#74104) and the RNA quality determined using an Agilent 2100
Bioanalyzer. RNAseq was performed at the Center for Cancer Computational Biology (CCCB) of the Dana-Farber Cancer Institute(DFCI) as well as at the BioMicro Center (BMC) of the Massachusetts Institute of Technology. mRNA was isolated from total
RNA using NEBNextÒ Poly(A) mRNA Magnetic Isolation Modules.
For library preparation, the CCCB used NEBNextÒ UltraTM Directional RNA Library Prep Kits for IlluminaÒ, whereas the BMC used
NEBNextÒ Ultra IITM Kits instead. Sequencing at the CCCB was performed on the Illumina NextSeq 500, whereas the BMC used a
NovaSeq 6000 with S4 flowcell as well as a NextSeq 500. Reads
were aligned to the GRCh38.95 reference genome using STAR
Aligner, primary aligned reads were filtered using Samtools, andsubsequent quality control software included FastQC, RSeQC, andMultiQC. The reads were then normalized using DESeq2, and thedata analyzed in Microsoft Excel Version 16.38 (20061401) for
Mac, Graph pad Prism Version 8.4.3 (471) and the R program.

2.5. Statistical analyses
Normality testing for the CpGs was performed in Prism using
Anderson-Darling, D’Agostino & Pearson, Shapiro-Wilk andKolmogorov-Smirnov tests. The beta-values of individual CpGs
from 13 T1Ds were averaged, a repeated measure one-way ANOVA,
followed with a Holm-Šídák’s multiple comparisons test was conducted to compare baseline values to subsequent years (year 1, 2or 3) for parametric CpGs. Sphericity was not assumed, and theGeisser-Greenhouse correction was applied. For CpGs that wereobserved as non-parametric in at least three of the four normality
tests for a given year, a Friedman’s test with a Dunn’s test for multiple comparison was instead performed when comparing baseline
values to subsequent years (years 1, 2 or 3). When comparing T1D
baseline to control methylation levels, a Mann-Whitney’s u test
was conducted. Whole gene summary figures for LETM1 and FCRL6
were created by averaging the mean beta values for CpGs acrossthe genes for each year, baseline or control. For the mRNA data, a
two tailed Student’s t-test was conducted to compare baseline values to subsequent years (year 1, 2 or 3).

3.2. Clinical impact on altered CpG methylation sites in BCG vaccinatedT1D subjects
The BCG vaccine, derived from Mycobacterium bovis, is an example of an environmental influence that changes the DNA methylation patterns. T1D with established and long-term disease received
at least 2 BCG vaccinations and then were followed for 3 years at
yearly intervals. DNA methylation patterns were tracked over the
3-year time course using the Infinium Methylation EPIC Bead Chip
Kit. This Illumina methodology identified 20 of 22 CpG DNA sites
associated with insulin and glucose homeostasis. The data shows
CpG gene regions responding to BCG vaccines in T1D that over
the observation period either hypermethylated (Fig. 2 top) or
demethylated. (Fig. 2 bottom). Overall, 13 of 20 CpGs showed that
BCG treatment could indeed induce significant methylation
changes in T1D CD4 lymphocytes at gene sites of interest for insulin and glucose regulation (Fig. 2). All statistics were baseline value
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Fig. 1. T1D Baseline methylation changes in genes associated with T2D, either hyper (top) or hypomethylated (bottom), as compared to non-diabetic controls. Altered
DNA methylation patterns at gene sites of glucose and insulin homeostasis were studied in the context of hypermethylation (top) or hypomethylation (bottom) in T1D
compared to non-diabetic controls. If the T1D differential shift in methylation of select gene regions in T1D compared to controls was in the same abnormal direction as T2D,
the paired samples were circled i.e. circled sets are those that were in the same direction as for abnormal T2D traits. Red circles are T1D; black squares are controls. Of the CpG
sites listed, the two in CPT1A, the KDM2B CpG and the ABCG1 CpG showed significant differences in T1D compared to controls; the rest of circled data showed directional
trends. n = 13 for T1D and n = 8 for controls, a Mann-Whitney’s u-test was used to determine significance. * = p < 0.05, ** = p < 0.01, *** p < 0.001. P-values were 0.0368 (ABCG1
cg0650016), <0.0001(CPT1A cg00574958), 0.0077 (CPT1A cg17058475) and 0.0129 (KDM2B cg13708645). Testing for the false discovery rate yielded Q values with a cut-off
as 0.1 for CPT1A cg00574958 (0.002), CPT1A cg17058475 (0.077) and KDM2B cg13708645 (0.086). (For interpretation of the references to colour in this figure legend, thereader is referred to the web version of this article.)

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H.F. Dias, W.M. Kühtreiber, K.J. Nelson et al.
Table 1CpG sites studied, and the functions for the genes.
Gene/
RegionCpG

Associated with Fasting Glucose(FG) / Fasting Insulin (FI):

4p15.33
ABCG1

cg10438589
cg06500161

FI
FI

ABCG1
APOBEC3H

cg27243685
cg06229674

FI
FG

DHCR24

cg17901584

FI

IRS2

cg25924746

FI

MAN2A2

cg20507228

FI

RBM20

cg15880704

FI

SLC7A11

cg06690548

FI, FGSREBF1cg11024682

FI, FG

1q25.315q26.1
ASAM

cg13222915
cg18247172
cg26894079

FI
FG
FI

CPT1A

cg00574958

FI, FG

CPT1A
KDM2B

cg17058475
cg13708645

FI
FI

MYO5C

cg06192883

FI

RNF145

cg26403843

FI

TMEM49cg24174557

FI

SLAMF1

cg18881723

FG

FCRL6

cg00936728

FG

LETM1

cg13729116

FI

FunctionATP-binding cassette, sub-family G (WHITE), member 1.Encodes a protein belonging to thesuperfamily of ATP-binding cassette (ABC) transporters which transport different molecules acrossextra- and intra-cellular membranes. ABCG1 is involved in cholesterol and phospholipids transport
and is assumed to regulate cellular lipid homeostasis.
Above
Apolipoprotein B mRNA-editing enzyme catalytic polypeptide-like 3H. A cytidine deaminase with
anti-retroviral activity by generating hypermutations in viral genomes, inhibiting replication andretrotransposon mobility. Is enriched in immune effector processes and innate immune response
24-Dehydrocholesterol Reductase. Contains a Flavin Adenine Dinucleotide (FAD)-dependentoxidoreductase which catalyzes the reduction of the delta-24 double bond of sterol intermediates
during cholesterol biosynthesis.
Insulin Receptor Substrate 2. Cytoplasmic signaling molecule mediating the effects of insulin,
insulin-like growth factor 1 and other cytokines by acting as a molecular adaptor between diverse
receptor tyrosine kinases and downstream effectors. This molecule is phosphorylated by the insulin
receptor tyrosine kinase upon stimulation
Mannosidase Alpha Class 2A Member 2. (Glycosylase enzyme). Catalyzes the first committed step inthe biosynthesis of complex N-glycans. Regulates conversion of high mannose to complex N-glycans
at the final hydrolytic step. Also related to pathways involving metabolism of proteins and IntraGolgi traffic.
RNA Binding Motif Protein 20. Protein that binds mRNA and regulates splicing. Including those of asubset of genes involved in cardiac development. Regulates the splicing of TNN (Titin).
Solute Carrier Family 7 Member 11. Protein coding gene for a member of a heteromeric, sodiumindependent, anionic amino acid transport system that is highly specific for cysteine and glutamate.
Glutamate is one pathway for sugar regulation.
Sterol regulatory element binding transcription factor 1. Encodes a transcription factor binding to
the sterol regulatory element-1, which is a decamer flanking the low-density lipoprotein receptor
gene and some genes involved in sterol biosynthesis.

(ASAM) CLMP: Coxsackie- And Adenovirus Receptor-Like Membrane Protein. This gene encodes atype I transmembrane protein that is localized to junctional complexes between endothelial andepithelial cells and may have a role in cell–cell adhesion. Expression of this gene in white adipose
tissue is implicated in adipocyte maturation and development of obesity.
Carnitine palmitoyltransferase 1a. CPT1A is an isoform of carnitine palmitoyltransferase (CPT) I. By
the sequential action of CPT and carnitine palmitoyltransferase II, together with a carnitineacylcarnitine translocase, the mitochondrial oxidation of long-chain fatty acids is initiated.
Deficiency of CPT I leads to a reduced rate of fatty acid beta-oxidation. Rate limiting for
mitochondrial fatty acid oxidation.
Above
Lysine Demethylase 2B. Involved in phosphorylation-dependent ubiquitination. Histone
demethylase that preferentially demethylates trimethylated H3 ’Lys-40 and dimethylated H3 ’Lys360 . Preferentially binds the transcribed region of ribosomal RNA and represses the transcription ofribosomal RNA genes which inhibits cell growth and proliferation.
Myosin VC. May be involved in transferrin trafficking. Likely to power actin-based membranetrafficking in many physiologically crucial tissues.
Ring Finger Protein 145. E3 ubiquitin ligase. In response to bacterial infection, negatively regulates
the phagocyte oxidative burst by controlling the turnover of the NADPH oxidase complex subunits.
Involved in the maintenance of cholesterol homeostasis. In response to high sterol concentrations
ubiquitinates HMGCR, a rate-limiting enzyme in cholesterol biosynthesis, and targets it for
degradation. In addition, triggers ubiquitination of SCAP, likely inhibiting its transport to the Golgi
apparatus and the subsequent processing/maturation of SREBPF2, ultimately downregulating
cholesterol biosynthesis.
(TMEM49) VMP1: Vacuole Membrane Protein 1. Transmembrane protein playing a key regulatoryrole in autophagy. Plays a role in the initial stages of the autophagic process through its interaction
with BECN1.
Signaling Lymphocytic Activation Molecule 1. Self-ligand receptor involved in modulating theactivation and differentiation of a variety of immune cells, and hence involved in the regulation andinterconnection of both innate and adaptive immune responses.
Fc Receptor Like 6. A Protein Coding gene. Acts as an MHC class II receptor. When stimulated on its
own, does not play a role in cytokine production or the release of cytotoxic granules by NK cells andT cells.
Leucine Zipper And EF-Hand Containing Transmembrane Protein 1. This gene encodes a protein thatis localized to the inner mitochondrial membrane. The protein functions to maintain the
mitochondrial tubular shapes and is required for normal mitochondrial morphology and cellularviability. Crucial for the maintenance of mitochondrial tubular networks and for the assembly of thesupercomplexes of the respiratory chain.

correct at reversing the abnormal patterning. These CpGs, except
the one for 15q26.1, all showed significant changes in methylation
status by year 3. In 15q26.1 this change was evident by year 1
instead. This data is additionally reflected in the heatmaps as allof a T1D compared to year 01, year 02 and year 03 of monitoring.
Of these 13 CpGs, 8 were in the same altered starting direction forT2D traits; 4p15.33, both ABCG1 CpGs, IRS2, MAN2A2, 15q26.1,
and both CPT1A CpGs. Thus, BCG treatment in vivo was directional
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Fig. 2. BCG vaccinations of T1D subjects induce shifts in methylation in restored direction towards normal over a 3-year monitoring time period. Significant yearly andlongitudinally followed changes in methylation status of select CpG regions related to glucose and insulin regulation. Homeostasis occurred either in year 01 (region 15q26.1
cg18247172) or by year 3 with the desired hypermethylation (top) of sites or hypomethylation (bottom) of select CpG sites (Red: T1D samples from Baseline – Year 3). Heatmaps (right) showed the same methylation data over Year 01–03 for each of the studied CpG sites but for simplicity represented as the gene name for the CpG sites. n = 13 forT1D; Significance was calculated using a repeated measure one-way ANOVA test followed with a Holm-Šídák’s multiple comparisons test comparing baseline to eachsequential year. For IRS2 cg25924746 a Friedman’s test followed with Dunn’s test for multiple comparisons was used instead. P-values * = p < 0.05, ** = p < 0.01, *** p < 0.001
are shown for the RM-ANOVA’s, and error bars represent standard error of the mean. Significant adjusted P-values for Holm-Šídák’s testing are: 15q26.1 cg18247172 (Y1:
0.0004, Y2: 0.0007, Y3: 0.0010), CPT1A cg00574958 (Y3: 0.0002), CPT1A cg17058475 (Y3: 0.0046), KDM2B cg13708645 (Y3: 0.0161), 4p15.33 cg10438589 (Y3: 0.0002),
ABCG1 cg06500161 (Y3: 0.0021), ABCG1 cg27243685 (Y3: <0.0001), APOBEC3H cg06229674 (Y1: 0.0226, Y2: 0.0044, Y3: 0.0045), DHCR24 cg17901584 (Y3: <0.0001), IRS2
cg25924746 (Y3: 0.0294), MAN2A2 cg20507228 (Y3: 0.0343), SLC7A11 cg06690548 (Y3: <0.0001). (For interpretation of the references to colour in this figure legend, thereader is referred to the web version of this article.)

the CpGs, except the one for 15q26.1, show the boldest colors by
year 3. As from the past data, this suggested that the beneficial
effects on glucose regulation as now showed, by following HbA1clevels, is a slow gradual process that occurs over multiple years[9,12]. Our data shows a similar slow gradual time course occurredat methylation sites as well as a few CpG sites were observed to
6

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for this gene showed increased methylation compared to controls;
but this difference statistically decreased for the pooled sites over
the three years of monitoring (Fig. 3A). The BCG treatment in vivo
appeared to overall work on the gene’s methylation sites with nosingle site driving the changes. Most LETM1 CpG sites graduallyde-methylated towards normal and showed significant net
demethylation across available CpGs by year 3 for LETM1.
In contrast, 7 of the T1D CpG sites with abnormal methylation
did not show a favorable change after BCG treatment (Supplemental Fig. 1, 2). The CpGs in region 1q25.3 and RBM20 shifted in an
unfavorable direction away from control levels, and no change
occurred for the CpGs in TMEM49 and SREBF1. The CpGs in ASAM
and RNF145 only got back to baseline levels by year 3, and further
longitudinal data would be required to confirm if their methylationlevels reach the same as controls. Additionally, the CpG in SLAMF1
did not show a difference between baseline and control levels; asignificant decrease in methylation was observed by year 1, how-methylate in an unfavorable direction (in relation to that for controls) for the first 2 years before correcting in year 3; an effect thatwas significant for the CpG in APOBEC3H in years 1 and 2. The CpG
for MYO5C decreased significantly in beta value by year 2 in an
unfavorable direction, however by year 3 the significant differencecompared to baseline was diminished and the methylation level
was closer to that of the control. The full effects of BCG on blood
sugar control can take up to 3 years to be induced [12]. For the
CpGs that corrected, heatmaps of the all the available CpGs fromthe genes showed that the most dramatic changes in beta values
occurred in year 3.
LETM1 is an identified gene from the T2D EWAS but the specificCpG for this gene identified in T2D studies associated with alteredinsulin was not represented in our Infinium Methylation EPIC Bead
Chip for this study. Therefore, we studied the entire methylation
patterning after BCG treatment in vivo in T1D for all CpG sites in
LETM1 (Fig. 3). The average beta value across all the CpG sites

Fig. 3. BCG induces demethylation in the LETM1 gene, an entire gene associated with fasting insulin, towards a favorable direction in T1D. A. Net demethylation in year
3 for the LETM1 gene occurs with BCG vaccinations in T1D (red) towards restored levels like controls (black). These results are mirrored in the individual CpG breakdown,when comparing the difference from each year to baseline (B), as significant demethylation is evident for multiple CpGs by year 3. N = 43 for net CpG changes studies. n = 13
for T1Ds; n = 8 for Controls. For Fig. 3B significance for each individual CpG was calculated using a Mann-Whitney’s u-test when comparing baseline to controls, and a
repeated measure one-way ANOVA test followed with a Holm-Šídák’s multiple comparisons test comparing baseline to each sequential year. For non-parametric CpGs a
Friedman’s test with Dunn’s test multiple comparisons was used instead when comparing baseline to each sequential year (Red asterisks). P-values * = p < 0.05, ** = p < 0.01,*** p < 0.001 are shown for the Holm-Šídák’s/Dunn’s multiple comparison testing in Fig. 3B, and error bars represent standard error of the mean. (For interpretation of thereferences to colour in this figure legend, the reader is referred to the web version of this article.)
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hypermethylation of the select CpG site but the gene overall
showed dominant hypomethylation although the mRNA corresponded to the CpG site methylation patterns in response to
BCG. The CpG site for SLAMF1 does not appear to be abnormal in
T1D, and after BCG treatment, a significant decrease in methylation
is evident for year 1 and year 2, reflecting the changes in the mRNA
profiles for the gene. Contrastingly, only 54% of the CpG sites in the
SLAMF1 gene were observed to have the strongest changes by year
3.
Taken together the results indicate that BCG treatment in T1D
induces significant changes of the methylation status of the majority of CpGs associated with T2D, although this is a gradual yearslong process after vaccine administration.

ever, the levels did not fully shift back up towards baseline/controls. Similarly, a heatmap of these CpGs (Supplemental Fig. 1, 2)
do not show any particular trends.
3.3. The methylation patterns resulting from BCG treatment of T1D
correlate with mRNA expression of the genes
We performed a more detailed characterization of genes of particular interest. CPT1A has two CpG regions associated with T2D
risk and is associated with glucose regulation pathways associatedwith OXPHOS, a topic of interest in T1D. In T1D both of these sites
are hypermethylated at baseline compared to control samples(Fig. 4). Importantly, both sites acquired methylation over the 3year observation period after BCG vaccinations in very statisticallysignificant ways (Fig. 4A). To confirm that this gene site andmethylation changes might be functionally important, mRNA wasprepared from the lymphocytes of treated T1D and analyzed byRNAseq. In a corresponding manner, mRNA levels diminished as
methylation increased suggesting the CPT1A CpG sites were associated tightly with the regulation in mRNA production. As mentioned earlier CPT1A has a function related to mitochondrial
oxidation and this metabolic process is overzealous in T1D. We
should point out here that the benefit of BCG on turning off
overzealous OXPHOS could involve this gene, a step that then promoted aerobic glycolysis and accelerated lymphoid ambient sugar
usage.
The KDM2B gene, also known as lysine demethylase 2B, wasalso studied in detail due to its known role in histone methylationand known role in glucose regulation in type 2 diabetes (Fig. 4B).
This gene is a mechanism for BCG to modify DNA histones andimpact gene expression. T1Ds at baseline were hypomethylated
at the cg13708645 site compared to controls samples and BCG triggered a gradual 3-year correction by hypermethylation. This shift
was reflected in the corresponding CD4 mRNA samples thatshowed decreased KDM2B expression. After BCG vaccinations, it
is already known that in monocytes, an increase in H3K4me3 histone modifications occurs and is associated with the promoters of
TNF, IL6 and TLR4. Thus our in vivo BCG methylation studies confirm this intricate control of gene expression.
The KDM family of lysine demethylase genes has many gene
members, so we also explored the other mRNA changes in theother KDM family members, not just the KDM2B gene associatedwith glucose metabolism. Nine different KDM-related genes
showed decreasing mRNA expression over the 3-year monitoringcourse (Fig. 5). It should be noted that none of these other KDM
related genes have a single CpG site that has been associated with
T2D. For the KDM genes with suppressed mRNA from BCG we do
not know the epigenetic sites for control. Not all members of the
KDM family of genes showed decreased mRNA; non-responding
mRNA levels were also identified (Supplemental Fig. 3).
A summary of KDM family members, their mRNA response after
BCG, and their known associations with select lysines on histones 3
and 4 is shown in Table 2. Many experiments in trained immunity,
typically on monocytes with various bacterial and yeast ligand
showed that H3K4s are modulated by BCG responsive cytokine
or glycolytic genes. This analysis showed a similar but not identical
overlap to KDM and known H3K4 histones in T1D.
To further buttress the functional link between T1D CpG sitemethylation changes due to BCG and mRNA changes, three additional CpG sites associated with insulin and glucose control wereanalyzed (Fig. 6). For MAN2A2 at baseline T1D lymphocytes were
hypermethylated (similar to T2D) but demethylated by year 3. This
was associated with a corresponding upward trend in mRNA also
isolated from lymphocytes. A heat map of all CpG sites in MAN2A2
showed BCG by year 03 was in general hypomethylating the geneas well as the specific CpG site under study. MYO5C corrects with

3.4. Baseline under-methylation of the DDIT4 gene is confirmed; BCG
vaccine treatment re-methylates this mTOR inhibitory gene
Epigenome wide association studies are difficult and demonstrate why large integrative cross omics of many T2D patientsare needed to show reproducibility [38]. Primary DNA methylation
variability in T1D, has been tackled most successfully using epigenome wide association studies in monozygotic twin pairs discordant
for T1D and isolated CD4 T cells [37]. A single observation thatreaches statistical significance is cg01674036 in CD4 T cells. Thisis a controlling region for the DDIT4 gene, an inhibitor of mTOR.
Although many prior CpG sites were not found especially in discordant identical T1D, we were able to show and confirm at baselinesimilar methylation of this gene (Fig. 7). With BCG vaccine therapy
and observations for 3 years, BCG re-methylated this inhibitory
gene. Based on the known signaling pathways of mTOR this would
be predicted to increase cellular glucose utilization in CD4 T cells[30].

4. Discussion
This study is a secondary analysis of a clinical trial evaluating
the benefits of BCG for the treatment of T1D. Patients with longterm T1D were dosed with at least 2 BCG vaccinations and then followed yearly for 3 years to look for the systemic methylation
changes in lymphocytes at CpG sites related to glucose and insulin
homeostasis taken from a cross-omics study of T2D. Five CpG sites
demonstrated over the 3-year time period re-methylation to control levels. Eight CpG sites demonstrated de-methylation to levels
close to control samples (Supplemental Table 1). We unexpectedly
identified KDMB2 as a key upstream regulator for BCG’s effect onhistone activity such as H3K4me3, a finding that is discussed further below.
The protective effect of the BCG vaccine from unrelated infections and in autoimmunity are now well documented from clinical
trial experiences [6–23]. Infections as well as hyperglycemia itself
can change the patterns of epigenetics through histone modifications. Hyperglycemia is associated with increased H3K4 andreduced H3H9 histone methylation patterns in the NFkB gene sets
[40]. Bacterial ligands such as Lipopolysaccharide and b-glucan(bacterial cell wall component) can also change the methylation
patterns on histone genes [41,42]. It is appreciated that each extracellular ligand, whether Lipopolysaccharide or b-glucan, utilizes
different functional programs and uses different cellular pathways
to achieve epigenetic programming of monocyte-to-macrophage
differentiation and trained innate immunity [43,44]. BCG itself also
alters histone methylation patterns, thus increasing expression ofcytokine genes and glycolytic pathways [41,42]. Each ligand or
microorganism is expected to have shared as well as unique setsof histone modifications specific to select gene regulation.
8

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Fig. 4. Impact of BCG vaccines in T1D on the methylation and mRNA patterns for the CpG CPT1A sites and CpG KDM2B site; yearly patterns after in vivo BCG treatment.
In T1Ds at baseline, both CPT1A (A) and KDM2B (B) CpG regions are hypomethylated compared to controls. The KDM2B gene is known as Lysine Demethylase 2B. With BCG
treatment and monitoring for 3 years after BCG vaccinations of T1D, the CpG sites of these genes become hypermethylated to adopt patterns that more closely align with
control DNA patterns. Hypermethylation for both the CPT1A gene sites and the KDM2B sites are associated with decreasing levels of mRNA over a 3-year period in the T1D(percent change in expression compared to T1D baseline). The mRNA expression profiles nominally match their methylation longitudinal changes after BCG vaccinations,suggesting functional significance. (C). Increased DNA methylation from BCG treatment at the KDM2B region may silence the gene. This likely results in increased levels of
methylation at Histone 3 Lysine 4 (H3K4me3) and Histone 3 Lysine 36me2 (H3K36me3) (red dots), allowing downstream activation of cytokines associated with BCG therapy
e.g TNF, IL6, TLR4 and genes involved in glycolysis. For the methylation n = 13 for T1Ds; n = 8 for controls regarding the methylation data. Significance presented is from a
repeated measure one-way ANOVA test followed with a Holm-Šídák’s multiple comparisons test comparing baseline and sequential years, and a Mann-Whitney’s u test whencomparing T1D baseline to control. mRNA expression percent change was calculated comparing baseline to each sequential year; A paired Student’s t-test was performed
between T1Ds baseline and sequential years, N = 10 for T1Ds. * = p < 0.05, ** = p < 0.01, *** p < 0.001, and error bars represent standard error of the mean. (For interpretation of
the references to colour in this figure legend, the reader is referred to the web version of this article.)
9

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Fig. 5. Impact of BCG vaccinations in vivo on the mRNA patterns of KDM-related gene members in T1D after BCG vaccinations. Similar to KDM2B, KDM gene family
members were studied for mRNA expression over the 3-year BCG clinical trial. This figure shows the related members that similarly showed less mRNA expression in
lymphocytes over the 3-year monitoring time period. mRNA expression percent change was calculated comparing baseline to each sequential year; A paired student’s t-test
was performed between baseline and sequential years, n = 10 for T1Ds. * = p < 0.05, ** = p < 0.01, *** p < 0.001, and error bars represent standard error of the mean.

related to glucose control in T2D. It is known that methylation of
select genes are associated with glycolysis; over-methylation ofthese genes is an underlying defect in diabetes [12,29,30].
With repeat BCG vaccinations in T1D, the critical glucose regulating CpG site of the KDM2B gene becomes re-methylated. This isconfirmed in parallel lymphocyte samples where BCG functionally

Here we extend these findings to human studies, to the adaptive immune response within T cells and add to the cascade of controlling proteins to this histone control of critical BCG activation. At
baseline compared to control subjects, T1D lymphocytes have
reduced methylation of the KDM2B gene, monitored in this study
on the cg13708645 methylation site previously identified and10

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stages of disease. However, some patients fail BCG therapy andthereby progress to invasive bladder cancer. In this BCG resistant
bladder cancer, constitutive activation of KDM2 family members
can occur with mutations resulting in overexpression of the
KDM2B proteins. This then transforms the bladder tumors to invasive carcinomas [46]. KDM2B likely is the upstream regulatory for
the BCG effect on histone modifications for subsequent gene control, especially since it targets the identified BCG histone modulator, H3K4me3. KDM2B dysregulation in T1D may be a primary stepin the therapeutic action of BCG in diabetes for the epigenetic
changes in cytokines but more importantly the clinically relevantchanges in glycolysis thus restoring lymphoid sugar utilization.
Some other KDM family members also showed decreasing mRNAlevels after BCG therapy in T1D (Fig. 5) although the fit with known
BCG driven histones was not as tight (Fig. 5, Table 2). Also, for theseother KDM family members, still with decreased levels with BCG
therapy, the exact CpG site driving the downregulation of mRNAby epigenetics is not known and genome wide studies have notbeen associated with glycolysis control.
Traditionally BCG or other microorganisms have been thought
to interact with only the innate immune system of human hosts
and this has focused studies on monocyte changes in vivo andin vitro, the term trained immunity. The data in this study uses
CD4 lymphocyte DNA and the referenced data set was using cells
from whole blood. Lymphocytes are part of the adaptive immune
system, not the innate immune system. This present data therefore
speaks to the broader role of BCG vaccines in both innate and adaptive immunity. To further add to the heterologous benefits of BCG,
our phase I trial showed that BCG reduced glycated hemoglobin(HbA1c) levels after 3 years in advanced T1D, increased the numbers of beneficial suppressive T-regs through methylation changes
in the promoters of over six central genes for optimal Treg function[12]. In the same publication, BCG treatment was shown to induce
DNA demethylation to signature Treg genes, which correlated totheir increased expression [12]. The reduction in HbA1c levels from
BCG treatment can be explained also by the upregulation of thetranscription factor Myc, a signature regulator of aerobic glycolysis,
glutaminolysis, polyamine synthesis and the mTOR/Hif-a pathways. This resulted in a shift from overactive OXPHOS (a state of
low glucose utilization) to aerobic glycolysis (a state of high glucose utilization) [30]. These shifts in glucose utilization wereobserved both in T cells (adaptive immunity) and in monocytes(innate immunity). BCG therefore in vivo appears to include boththe innate and adaptive immune systems through altered methylation patterns.
The CpGs identified in the cross-omics paper were involved in arange of functions, including, metabolism, immune responses,
sterol/lipid regulation, sugar regulation and as transporters(Table 1). Of these 20+ CpGs, 13 visually displayed the same differential methylation in T1D as for T2D traits in our study, indicatinga strong similarity in the progression of the diseases, at least as it
relates to methylation defects associated with insulin and glucose
control. The 13 CpGs included: 4p15.33, both ABCG1 CpGs, IRS2,
MAN2A2, RBM20, SERBF1, 1q25.3, 15q26.1, ASAM, both CpGs in
CPT1A, and TMEM49. In particular, the CpGs for CPT1A, a very
well-studied gene related to methylation defects in T2D, were statistically significant for this difference in this study. The CpG in
KDM2B was hypomethylated abnormally as compared to controls
at baseline, and also corrected with BCG therapy in a statisticallysignificant manner.
Complementary to our work in T1D, the cross-omics analysis of
DNA methylation sites related to fasting glucose and insulin identified 3 CpGs genes related to defects in OXPHOS, two of whichwere localized to the mitochondria. The sites CPT1A cg00574958
and ABCG1 cg06500161 were found to be expression quantitative
trait methylations (eQTMs), meaning that there is a correlation

Table 2
Members of the KDM family, RIOX1 was associated to KDM2B through an Ingenuity
Pathway Analysis, of which RIO2 was a strong paralog. Information retrieved fromgenecards.com.
Gene
KDM1A
KDM1B
KDM2A
KDM2B
KDM3A
KDM3B
JMJD1C
KDM4A
KDM4B
KDM4C
KDM4D
KDM4E
KDM5A
KDM5B
KDM5C
KDM5D
KDM6A
KDM6B
UTY
KDM7A

Expression
trend:
Decreases
Decreases

Decreases
Decreases

Decreases
Decreases

Decreases
Decreases

PHF8
KDM8
RIOX1
RIOX2

Decreases
Decreases

Histone Lysine Demethylase Function
Demethylates H3K4me1/me2 and H3K9.
Demethylates H3K4me1/me2
Demethylates H3K36me2, weakly H3K36me1
Demethylates H3K4me3, H3K36me2
Demethylates H3K9me1/me2
Demethylates H3K9
Demethylates H3K9
Demethylates H3K9me3, H3K36me3
Demethylates H3K9me3
Demethylates H3K9me3, H3K36me3
Demethylates H3K9me2/me3
Demethylates H3K9me2/me3
Demethylates H3K4me2/me3
Demethylates H3K4me1/me2/me3
Demethylates H3K4me2/me3
Demethylates H3K4me2/me3
Demethylates H3K27me2/me3
Demethylates H3K27me2/me3
Demethylates H3K27me3
Demethylates H3K9me2, H3K27me2,
H4K20me1
Demethylates H3K9me1/me2, H3K27me2,
H4K20me1
Can induce demethylation at H3K36me2/me3
Demethylates H3K4me1/me3, H3K36me2
Demethylates H3K9me3

Methylation at H3K4, H3K36 and H3K79 is often association with transcriptional
activation; methylation at H3K9, H3K27 and H4K20 is usually associated withtranscriptional silencing. H3K27 demethylation appears to be concomitant with
H3K4 methylation.

decreases mRNA levels in KDM2B. KDM2B could be the upstream
gene for BCG training to the already well-documented histonechanges for various ligand experiments studying trained immunity, especially for cytokine and glucose regulating genes. Human
monocytes in culture exposed to either C. albicans (yeast) or bglucan show genome-wide changes in epigenetic marks, including
histones H3K4me1 and H3K4me3 [45]. For b-glucan exposures tomonocytes in culture, the cell surface binding involves dectin 1(b-glucan receptor), AKT, mTOR and HIFl and cellular metabolism
switches from oxidative phosphorylation to glycolysis with epigenetic reprogramming by inhibiting KDM5 histone demethylases[45]. BCG in vitro and in vivo does not bind to the b-glucan receptor but these pathways overlap downstream to similarly change
glycolysis [29,30] and now a different central KDM histone lysine
demethylase is identified. For cultured human monocytes, H3K4
type histones have been shown to have increased methylation thatin return increases cytokines and glycolysis after BCG exposures inculture [27].
In this study we identify the known glucose regulating gene
KDM2B as defective in T1D and responsive to BCG, but we also
identify close family members are also function by changing mRNAlevels over the 3-years of monitoring, including KDM1B, JMJD1C,
KDM4A, KDM4D, KDM5A, UTY, KDM7A, RIOX1 and RIOX2. Fromprior studies we know which KDM family members are associatedwith histone lysine demethylase targets (Table 2). There is excellent pairing of these histone methylation sites with past data on
the patterning of these histones on cytokine genes and glycolysis
genes. The current study suggests the central role of KDM2B andsome closely related family members in the correction of blood
sugars.
The role of KDM family, and KDMB2 specifically, in the BCG
mechanism of action is buttressed by another clinical example,
BCG for cancer. BCG is an approved drug for bladder cancer at early11

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Fig. 6. Impact of BCG vaccinations in vivo on the methylation and mRNA patterns compared to untreated controls for MAN2A2, MYO5C and SLAMF1 CpG sites; yearlypatterns after in vivo BCG treatment. For the MAN2A2 CpG site, the MYO5C CpG site, and the SLAMF1 CpG site, BCG treatment of T1D over the 3-year studied time course
nearly restores the methylation patters to control levels. MAN2A2 is demethylated, MYO5C is methylated and no difference is seen for SLAMF1. A study of the overall
methylation pattern of all CpG sites for the three genes only shows a mild correlation for MAN2A2 but not for MYO5C. For SLAMF1, only just over 50% of the CpG sites show
the biggest changes by year 3 (the studied CpGs are highlighted in yellow); for some genes a single CpG site can confer dominant function. In a reciprocal manner themeasurement of mRNA in peripheral T cells over the same time course shows the impact of the changing methylation patterns for these genes is reflected by a similar
reciprocal change in mRNA expression. For the methylation analysis: n = 13 for T1Ds; n = 8 for controls. Significance shown was calculated using a Mann-Whitney’s u testwhen comparing baseline to controls, a repeated measure one-way ANOVA test for MAN2A2 cg20507228 and MYO5C cg06192883, and a Friedman’s test for SLAMF1
cg18881723 comparing baseline to each sequential year. mRNA expression percent change was calculated comparing baseline to each sequential year; A paired Student’s ttest was performed between baseline and sequential years, n = 10 for T1Ds. * = p < 0.05, ** = p < 0.01, *** p < 0.001, and error bars represent standard error of the mean. (Forinterpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
12

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Fig. 7. Baseline undermethylation of a critical CpG site of DDIT4 Gene; Impact of BCG vaccinations in vivo on re-methylation of the gene. (A) At baseline the cg site of
the DDIT4 gene (cg01674036), a site associated with T1D progression, is undermethylated. After repeat BCG vaccinations in vivo, the CpG site of the DDIT4 gene is gradually
re-methylated, almost to control levels. (B) The DDIT4 gene is a known inhibitor of mTOR. mTOR is an activator of HIF-1a and thus facilitates glucose transport. The observed
under-methylation of the CCIT4 gene would be predicted to hamper glucose transport. After BCG therapy in vivo, the CD4 lymphoid cells have restored glucose transport fromthe re-methylation of DDIT4. Significance was calculated using a repeated measure one-way ANOVA test followed with a Holm-Šídák’s multiple comparisons test comparing
T1D baseline to sequential years, and a Mann-Whitney’s u-test when comparing T1D baseline to control. * = p < 0.05, ** = p < 0.01, *** p < 0.001, and error bars represent
standard error of the mean. ANOVA P-value = <0.0001, Holm-Šídák’s P-value comparing T1D Baseline to Year 3 = <0.0001.

an increase in CPT1A expression (and other fatty acid oxidation(FAO) genes) in the liver of T1D mice models [47], a possible cause
for the increased ketogenesis in T1D patients; this increase could
be to compensate for the lack of glucose uptake in T1D patients.
Three years after BCG treatment, the methylation levels for both
the CPT1A CpGs corrected, suggesting a lowered reliance on fatty
acid oxidation for energy. Likewise, the relevant CpGs in ABCG1

between their methylation status and the gene’s expression level.
CPT1A is a rate-limiting enzyme for fatty acid oxidation, the protein converts acyl-coenzyme A into acyl-carnitines, allowing for
migration across membranes into the mitochondria. The beta values for both CPT1A CpGs at baseline were lower than controls
implying an increased level of expression for the gene, and thus
potentially increasing the rate of fatty acid oxidation. There is also
13

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DNA data sets. Additional consideration of this study involves thetime frame of observations and comparison of past in vitro data
to this in vivo study. Commonly histone modifications of monocytes come from in vitro BCG exposures. This study looks at thehistone modifications from humans treated with BCG vaccinations
and the common lymphocyte under study are T cells analyzed overyears of time post systemic exposures.
In conclusion, many of the CpGs identified in the Cross-omics
paper had similar defects in T1D and following BCG treatment(Supplemental Table 3), 13 of the CpGs showed corrections inmethylation levels back towards those of controls. The results fromthis study beg the question whether BCG treatment would be beneficial in T2D. What amount of information would suffice to further
pursue studies of BCG treatment in T2D? In a mouse model, BCG
reduces plasma High Density Lipoproteins and cholesterol levels
and also delays atherosclerotic lesions formed in hyperlipidemic
mice, showing the dramatic ability of BCG to change the predominantly mitochondrial driven fatty acid synthesis pathways [51].
Also, BCG ameliorates metabolic syndrome in nonalcoholic fatty
liver disease in obese, diabetic ob/ob mice [52]. Finally, it is not
yet known in T2D whether like T1D, the starting set point of theimmune system similarly shares the marked defects of overabundant OXPHOS and deficient aerobic glycolysis [12,29,30].

were in the same direction for T1D and T2D traits and also corrected by year 3. ABCG1 is a cholesterol and phospholipid transporter in macrophages and prevents cell death by transporting
cytotoxic 7-beta-hydroxycholesterol, but its role may also extend
to other cell types. Moreover, streptozotocin-induced diabetic mice
have shown reduced levels of ABCG1 [48], supporting the data that
the CpG may be an eQTM. Conjointly with CPT1A, the CpGs in bothgenes also showed a correction by year 3, suggesting that these
epigenetic changes do impact the biology and may contributetowards the reversal of diabetic traits.
LETM1 displayed significant net demethylation towards controls by year 3. The gene encodes a proton/calcium antiporter protein also located in the inner mitochondrial membrane and is
crucial for maintaining the tubular mitochondrial structures. If
the methylation difference translated to the gene’s expression,
T1D at baseline would have reduced levels of this protein available,
which suggests dysregulated OXPHOS. A publication from Lin et al2018 [47] provided data that FAO can promote reprogramming ofsomatic cells to induced pluripotent stem cells by enhancing
OXPHOS (and inhibiting protein kinase C); it was found that in
the early stages CPT1B (an isoform of CPT1A) was significantly
upregulated. The methylation data regarding CPT1A, ABCG1 andLETM1 could contribute towards why T1Ds overuse OXPHOS compared to controls.
Although this paper was centered on the massive integrative
cross-omics analysis of DNA methylation sites, now applied to
T1D, we also investigated the single CpG site statistically identified
in T1D twin samples with strong methylation differences related todisease expression [37]. In only T1D twins that progress to diseases, the cg01674036 of the DDIT4 gene is under-methylated. This
gene is an inhibitory protein of mTOR, a protein that facilitates glucose transport. We confirm at baseline the gene is undermethylated in our data set. (Fig. 7A). With BCG therapy the gene
becomes more methylated at this T1D linked CpG disease risk site
(Fig. 7A). The role of the mTOR pathway both in BCG biology andalso the use of this pathway to facilitate enhanced glucose uptake
has been established [30] (Fig. 7B). This confirms the mTOR
derangements are present at baseline in T1D and BCG appears
through modulations of methylation impact well known pathway
important for cellular glucose transport.
There are limitations of this study. Epigenetic studies comparing T1D to controls populations are difficult to do and often requiremassive numbers of individuals in the replication. For our data forthis comparison (Fig. 1), the power was low for the majority of the
CpGs except CPT1A cg00574958 (0.9815793), CPT1A cg17058475(0.866527)
and
KDM2B
cg13708645(0.7715659):(ABCG1cg06500161 was 0.4618398). Power calculations for thedata in Fig. 2, comparing baseline to each subsequent year, attained
acceptable values of over 0.77 for all CpGs bar MYO5C cg06192883,
where the highest power was 0.53 comparing baseline to year 2.
For DITT4 cg01674036 the power was 0.8281764 comparing T1D
baseline to controls, and 0.9999994 comparing T1D baseline to
T1D year 3 (Fig. 7). In the past, methylation studies of T1D DNA
compared to control populations have been conducted. Probably
some of the best controlled studies in T1D and epigenetics are
the classic studies comparing discordant twin pair methylation
patterns [37,49,50]. We present this early data in this paper (T1D
versus controls) as an introduction of epigenetic changes thatmight directly match similar alterations found in fasting glucose
and insulin derangements [38] (Fig. 1). Using this limited dataset, 65% overlap was observed; it is not known if our patient sample numbers were larger if this overlap would be higher. The
strength of this investigation is the multi-year longitudinal studyof T1D compared to self with BCG treatment which affords a morerobust power analysis (Figs. 2-7). These comparisons to self eliminate the careful and painstaking matching of control and patient

Declaration of Competing Interest
The authors declare that they have no known competing financial interests or personal relationships that could have appeared
to influence the work reported in this paper.
Appendix A. Supplementary material
Supplementary data to this article can be found online athttps://doi.org/10.1016/j.vaccine.2021.04.011.
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