The adaptive immune repertoire of type 1 diabetes

Stephanie Rothweiler1, Howard Seay1, Lin Zhang1, Jeff Bluestone2, Marissa Vignali, PhD3, Ryan Emerson3, Harlan Robins3, Todd Brusko1 1Department of Pathology, Immunology and Laboratory Medicine, University of Florida, Gainesville, Florida

2Diabetes Center, University of California San Francisco, San Francisco, California 3Adaptive Biotechnologies, Inc, Seattle, WA

Introduction The adaptive immune system plays an essential role in the pathogenesis of type 1 diabetes (T1D)

through the expansion of T cell receptors (TCR) expressed by autoreactive CD4+ and CD8+ T

cells. Moreover, B cells are thought to play an essential role in the disease process by serving as

antigen presenting cells upon autoantigen uptake through the B cell receptor (BCR). To date, the

majority of studies assessing TCR and BCR diversity in subjects with T1D have been limited to

sampling from peripheral blood. We hypothesized that there would be an enrichment of

autoreactive TCR and BCR signatures within the pancreatic draining lymph nodes of T1D

subjects. In an effort to assess TCR and BCR usage in T1D, we FACS-sorted high-purity

lymphocyte subpopulations from the tissues available from 32 nPOD donors, including the

pancreatic-draining lymph node (pancLN), non-pancreatic-draining lymph node (non-pancLN),

spleen, and PBMC. From these, we isolated Treg (CD4+CD25+CD127-/lo), T conventional

(Tconv; CD4+CD127+), CD8+ T cells, and CD19+ B cells. The 232 resultant samples were deep

sequenced (targeted output of 800,000 sequences) by Adaptive Technologies (Seattle, WA) at the

TCR Vbeta and IgH genes.

Materials and Methods

Demographics

Conclusions & Future Directions

• From all tissues analyzed, we observed an enrichment of some TCRs

in T1D subjects within CD8+ T cells (TCRBV07-07; 2.7-fold), CD4

Tconv (TCRBV26-01, 2.2-fold). More specifically in the pancLN, we

observed a selective enrichment of CD8+ TCRs in T1D (TCRBV05-

02, 13.07 fold) and Tconv (TCRBV03-01, 3.93 fold)

• In terms of the B cell repertoire, we observed BCR V genes IGHV03-

29 and IGHV03-06 were abundant in T1D-associated pancLN, while

these genes were absent from control donor samples

• A large degree of diversity was observed in terms of receptor usage

for both T and B cells. Future efforts will further stratify patient

cohorts by defined characteristics (e.g., insulitis, HLA)

• These studies should provide a valuable resource of sequences for

investigators to query with their defined TCRs or BCRs of interest to

determine if they are also present in this nPOD cohort through nPOD

DataShare

• We expect this broad receptor sequencing data, when paired with

high-resolution HLA and additional histological and clinical metadata,

will provide a powerful dataset to aid in the discovery and validation

of adaptive immune signatures in T1D.

• Future efforts will extend these studies into the isolation and analysis

of islet resident T cells (single cell) and defined populations of

memory and effector T cell lineages where enrichments of

autoreactive receptors would be expected

Figure 1. Workflow of sample processing. Fresh donor tissues is received from the nPOD

(jdrfnpod.org) Organ Processing and Pathology Core (based on availability), and homogenized,

filtered, and put into single-cells suspensions. Cells are labeled with an antibody cocktail

containing anti-CD19, CD8, CD4, CD25, and CD127. The cells are then FAC-sorted on a BD

FACSAriaIII for B cells, cytotoxic T cells (CTL), conventional CD4+ T cells, and regulatory

CD4+ T cells. Based on recovery , 100K-400K cells are combined with DNA/RNA Lysis Buffer

(Guanidine Thiocyanate-based; Zymo Research, Orange, CA) to preserve nucleic acids for

experimentation and frozen at -80oC. DNA is extracted and 0.145μg-7.5µg is shipped to Adaptive

Biotechnologies (Seattle, WA) for TCR and BCR sequencing. Sequences are analyzed in

Adaptive’s ImmunoSEQ software (Adaptive Biotechnologies).

Acknowledgements

Results

Top Variable-region β-chain Clones in nPOD Samples

Figure 3. TCR and BCR Variable-region β -chain (V-beta) distribution in pancreatic lymph nodes (pancLN) and

spleen. Graphs indicate TCR and BCR usage and tissue distribution among T1D subjects with residual C-peptide

preservation (>0.5 ng/ml), subjects with long-term disease with no residual C-peptide (<0.5 ng/ml), or control

donors.

Case ID AGE(y) GENDER ETHNICITY BMI

C-

peptide

(ng/mL)

Disease (y) AAB + HLA-A HLA-B HLA-DQA1 HLA-DQB1 HLA-DRB1PBMC

CTL

PBMC

Tconv

PBMC

Treg

PBMC

B cells

pancL

N CTL

pancLN

Tconv

pancLN

Treg

pancLN

B cells

Spleen

CTL

Spleen

Tconv

Spleen

Treg

Spleen

B cells

non-

pancL

N CTL

non-

pancLN

Tconv

non-

pancL

N Treg

non-

pancLN

B cells

6161 19.2 Female Caucasian 36.1 <0.05 T1D (7) IA-2A+, mIAA+ 02:01, 02:05 50,62 02:01, 03:01 02:02, 03:02 04:01, 07:01 X X X X X X X X

6174 20.8 Male Caucasian 19.5 3.00 Control Negative 02:05, 26:01 08, 50 02:01, 05:01 02:01, 02:02 03:01, 07:01 X X

6193 26 Male Caucasian 24 <0.05 T1D (20) mIAA+ 02:01, 03:01 62, 35 01:01, 03:01 03:02, 05:01 01:01, 04:01 X X X

6195 19.2 Male Caucasian 23.7 <0.05 T1D (5) GADA+, IA-2A+, ZnT8A+, mIAA+ 03:01, 03:01 07, 62 01:02, 03:01 03:02, 06:02 04:01, 15:01 X

6196 26 Female African American 26.6 0.48 T1D (15) GADA+, mIAA+ 03:01, 30:02 35, 58 01:01, 05:01 02:01, 05:01 12:01, 13:03 X X

6197 22 Male African American 28.2 17.48 Control GADA+, IA-2A+ 02:02, 24:02 42, 45 02:01, 04:01 02:02, 04:02 03:02, 07:01 X

6207 16 Female African American 24.2 <0.05 T1D (10) IA-2A+, ZnT8A+, mIAA+ 23:01, 24:02 07, 55 01:02, 03:01 02:02, 06:04 09:01, 13:02 X X X X X X X X X

6208 32 Female Caucasian 23.4 <0.05 T1D (16) Negative 01:01, 68:01 08, 44 03:01, 05:01 02:01, 03:02 03:01, 04:01 X X X X X

6211 24 Female African American 24.4 <0.05 T1D (4) GADA+, IA-2A+, ZnT8A+, mIAA+ 02:01, 03:01 08, 45 03:01, 05:01 03:01, 03:02 04:05, 12:01 X X X X X

6212 20 Male Caucasian 29.1 <0.05 T1D (5) mIAA+ 01:01, 02:01 02:01, 02:01 02:02, 02:02 07:01, 07:01 X X X X X X X X

6220 35 Female Caucasian 27.4 <0.05 T1D (11) GADA+, mIAA+ 01:01, 02:01 08, 39 02:01, 05:01 02:01, 03:03 03:01, 07:01 X X X X X

6242 39 Male Caucasian 19.5 <0.05 T1D (19) IA-2A+, mIAA+ 02:01, 02:01 27, 44 01:01, 03:01 03:02, 05:01 01:01, 04:01 X X X X X X

6243 13 Male Caucasian 21.3 0.42 T1D (5) mIAA+ 01:01, 02:01 08, 08 05:01, 05:01 02:01, 02:01 03:01, 03:01 X X X X X X X X

6249 45 Female Asian 32.2 4.17 T2D (15) mIAA+ 02:01, 24:01 62, 62 03:01, 03:01 04:02, 04:02 04:05, 04:05 X X X X X X X

6254 38 Male Caucasian 30.5 6.43 Control Negative 02:01, 29:02 07, 62 02:01, 05:01 02:01, 02:02 03:01, 07:01 X X X X X X

6262 44 Male African American 21.5 <0.05 T1D (8) GADA+, IA-2A+, mIAA+ 01:02, 11:01 49, 62 03:01, 03:01 03:02, 03:02 04:01, 04:05 X X X X X X X X

6263 34 Male Hispanic 23.5 3.18 T1D (21) Negative 02:06, 24:02 39, 39 03:01, 05:01 03:01, 03:02 04:07, 14:06 X X X X X X X X

6264 12 Female Caucasian 22 <0.05 T1D (9) Negative 23:01, 32:01 03:01, 05:01 02:01, 03:02 03:01, 04:04 X X X X X X X

6265 11 Male Caucasian 12.9 0.06 T1D (8) GADA+, mIAA+ 03:01, 32:01 07, 62 03:01, 05:01 02:01, 03:02 03:01, 04:01 X X X X X X X X

6266 30 Male Caucasian 27.1 <0.05 T1D (23) GADA+, IA-2A+, mIAA+, ZnT8A+ 01:01, 03:01 08, 61 03:01, 05:01 02:01, 03:02 03:01, 04:04 X X X X X X X X X X X X

6271 17 Male Caucasian 24.2 11.47 Control Negative 02:01, 02:06 27, 44 01:01, 02:01 02:02, 05:01 07:01, 15:02 X X X X X X X X X X X X

6273 45 Female African American 39.1 3.17 T2D (2) Negative 02:02, 03:01 07, 49 01:02, 01:02 06:02, 06:02 15:01, 15:03 X X X X X X X X X X X X

6274 36 Female Caucasian 28.6 12.64 Control Negative 01:01, 31:01 08, 35 05:01, 05:01 02:01, 03:01 03:01, 11:01 X X X X X X X

6275 48 Male Hispanic 41 3.46 T2D (2) Negative 02:01, 25:01 07, 51 01:02, 03:01 03:03, 06:02 09:01, 15:01 X X X X X X X X X X

6278 10 Female African American 21.3 4.54 Control Negative 23:01, 68:02 45, 71 23:01, 68:02 03:01, 05:01 11:04, 12:01 X X X X X X X X X X X

6279 19 Male Caucasian 34 8.01 Control Negative 01:01, 29:01 07, 51 01:02, 02:01 02:02, 06:02 07:01, 15:01 X X X X X X X X X X X X

6282 14 Male Caucasian 41.9 6.83 Control Negative 03:01, 29:02 44, 51 01:02, 01:03 06:02, 06:03 13:01, 15:01 X

6284 24 Female African American 27.3 1.70 Pending Negative 36:01, 68:02 53, 53 01:02, 03:01 02:02, 06:02 15:03, 15:03 X X X X X X X X X X X

6285 22 Female Hispanic 21.8 <0.05 T1D (15) GADA+, IA-2A+, mIAA+ 01:01, 24:02 07,45 02:01, 03:01 02:02, 03:02 04:05, 07:01 X X X X X X X X

6287 57 Female Caucasian 21.8 4.75 Control (NET) Negative 02:01, 03:01 27, 44 01:01, 03:01 03:03, 05:01 01:01, 09:01 X X X X X X X X

6288 55 Male Caucasian 37.7 12.96 Control Negative 02:01, 24:02 39, 44 01:02, 05:01 03:01, 06:02 11:01, 15:01 X X X X X X X X

6289 19 Male African American 38.3 8.05 Control Negative 02:01, 02:11 44, 52 02:01, 03:01 02:02, 03:02 04:11, 07:01 X X X X X X X X X X X X

FACSAriaIII

Spleen

PBMC

pLN

Figure 2. Cell recovery and yield from nPOD donors. Graph depicts yields from nPOD donor

spleen, pancreatic-draining lymph node (pancLN), non-pancreatic-draining lymph node (non-

pancLN), and periperial blood mononuclear cells (PBMC) in the Brusko laboratory. These

numbers are event counts recorded in the FACSDiva software, with spleen, pancLN, non-

pancLN, and PBMC counts representing the input into the machine and the population counts

being the average number of output cells FAC-sorted into collection tubes.

These studies were supported by a research sequencing grant (provided in kind) from

Adaptive Biotechnologies. Additional project support was provided by grants from the

NIH-NIAID P01 (AI42288), JDRF (CDA 2-2012-280), and the Helmsley Charitable

Trust George Eisenbarth Award for team science.

• Analysis of nPOD tissues provides the unique ability to make comparisons of TCR and BCR usage in cross-sectional patient cohorts from

various tissue sources relevant to the disease pathogenesis. Using Adaptive’s ImmunoSEQ software, we have identified both global and

tissue-specific alterations in TCR-Vbeta sequences in T1D subjects as compared to relevant controls

Spleen

pancLN

PBMC

Repertoire Overlap in T cells

5.92% 5.91±%

3.82% 3.93±%

31.46 18.98±%

5.70% ±4.95%

13.14 ±10.32%

27.48 ±22.81%

CD8+ T cells

CD4+ Tconv

Figure 6. TCR V-gene Overlap Analysis Heat Map of FAC-

sorted T cell populations. The overlap metric for each possible

pair-wise percent sharing between all pairs of samples. Due to

the nature of the program, many nPOD donor samples do not

contain all tissues types requested. Cases 6212, 6249, 6262,

6266, and 6284 contained enough material from the spleen,

pancreatic-draining lymph node (pancLN), and PBMC for

repertoire overlap analysis using the Adaptive ImmunoSEQ

Analyzer bioinformatics software. While there are currently not

enough samples in our dataset to compare cases with diabetes

against those without, it is not hypothesized that there is a

significant difference between the two, and therefore, sample

overlap was averaged to show V-gene overlap between immune

tissues as a basic finding. Interestingly, there seems to be

massive overlap between CD8+ T cell TCR implicating them as

a primary target for biomarker discovery.

Figure 5 (above). Enrichment of TCR Variable-region β-chain (V-beta) TCRBV05-01 in the pancreatic-draining lymph node (pancLN)

Tconv in GADA+ mIAA+ case 6265. Frequencies of TCRV-beta in nPOD non-T1D-control donor pancLN do not exceed 6% and there are

no TCRV-beta significantly enriched in pancLN over spleen. The above figure shows that TCRVB05-01 was enriched in the pancLN over

spleen within case 6265 by 359.4%.

pancLN Tconv Spleen Tconv

TCR Enrichment in Case 6265 Figure 4 (left). Enrichment of a

45 amino acid TCR Variable-

region β-chain (V-beta) in the

pancreatic-draining lymph node

(pancLN) conventional T cells in

GADA+ mIAA+ case 6205.

Complementarity determining

region 3 (CDR3) length from 28

nPOD pancLN Tconv samples.

All CDR3 include some of a V

region, all of a diversity (D,

heavy chains only) and joining (J)

regions. CDR3 is the most

variable of the CDR and CDR3

length distribution analysis

explores the diversity of the TCR

repertoire at the transcriptome

level. Studies of the CDR3 have

been frequently used to identify

recruitment of T cell clones

involved in immunological

responses. This figure shows that

there is a clonal response of a 45

amino acid TCR in case 6265.