Copenhagen DIRECT Copenhagen Diabetes Research Center

The Autoimmune Pathogenesis of Type 1 Diabetes

Flemming Pociot Professor, MD, DMSc

Why trying to understand narcolepsy genetics and pathogenesis by contrasting it to type 1 diabetes?

The major players in autoimmune disease development

Environmental triggers Genetic susceptibility

Immune system and b-cell

Autoimmunity module

T1D

CeD

RA

IBD

MS

NAR

Genetic and immunology studies have demonstrated considerable overlap between autoimmune diseases

Won et al (2004) J Clin Sleep Med Pundziute-Lyckå et al (2002) Diabetologia https://www.23andme.com

Narcolepsy

T1D

Thannickal et al (2000) Neuron

NORMAL TYPE 1 DIABETIC

Hypocretin staining

Insulin staining

NORMAL NARCOLEPSY

Target cells are dispersed and limited in number

Mundinger et al (2016) Diabetes

Thannickal et al (2000) Neuron

Cell-specific destruction

T1D vs Narcolepsy (genetics)

T1D NAR Autoimmune YES YES Prevalence 0.4% 0.02-0.2% HLA major genetic risk component >50% >85% HLA major risk genotype: DQ2/DQ8 DQ6 Non-HLA risk ~ 50 loci ~ 3 -10* loci OR non-HLA loci 1.05-1.8 1.05-1.5 Explained heritability ~ 80-85% ~50% **

*: GWAS p-value <10E-6) **: Model-dependent

Pociot and Lernmark (2016) Lancet

Interception

Natural history of type 1 diabetes

Studies of pathogenesis

Pociot and Lernmark (2016) Lancet

Autoantibodies are strong predictors of T1D risk but not causal factors

Pociot and Lernmark (2016) Lancet

DR3-DQ2/DR4-DQ8

DR3-DQ2/DR3-DQ2 DR4-DQ8/DR8-DQ4

DR4-DQ8/DR4-DQ8

Størling et al (2013) Diabetologia Mignot (2014) Immunol Res

Type 1 diabetes

Narcolepsy

Pathogenetic model – A dialogue between the target cell and the immune system

Eizirik et al. Nat Rev Endocrinol 2009

Cytokine-induced β-cell apoptosis

Faraco et al (2013) Plos Genet

Immunochip data - Narcolepsy

GWAS data NAR and T1D

The HLA association

Narcolepsy: > 90% DQB1*0602 positive (20-25% of the background population T1D: > 90% positive for DR3 and/or DR4 (45% of the background population)

Immune genes

Insulin production and metabolism

Beta-cell apoptosis Unknown function

Futher insight into the pathogenesis from genetics

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KEGG/GO

Bergholdt et al (2012) Diabetes, Eizirik et al (2012) Plos Genet

Faraco et al (2013) Plos Genet

Immunochip data - Narcolepsy

GWAS data NAR and T1D (Manhattan plots)

Guo et al (2015) Hum Genet Mol

CTSH region on 15q25.1

Lysosomal cysteine cathepsins:

Proteases known for their presence in the lysosomes - protein degradation.

Cathepsins Involvement in diabetes

Cathepsin G, D, S, and V Involved in proinsulin processing Zou et al. PLoS ONE 2011

Cathepsin G Important for generation of proinsulin-reactive T cells Zou et al. PLos ONE 2011

Cathepsin S, B, and L Important for onset of autoimmune diabetes in NOD mice

Maehr et al. J Clin Invest 2005, Hsing et al. J Autoimmun 2010

Cathepsin S, W, H and C Immune cell penetration of the peri-islet basement membrane leading to insulitis Korpos et al. Diabetes 2013

Involved in cellular processes such as apoptosis, antigen presentation, and prohormone

processing.

Cysteine cathepsins

Associated with diseases e.g. cancer, osteoporosis, rheumatoid arthritis,

osteoarthritis, and type 1 diabetes

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Slide 20

T1D-associated single nucleotide polymorphisms (SNPs)

affect the mRNA and protein expression of CTSH

CTSH is expressed in human β-cells

CTSH is downregulated by pro-inflammatory cytokines in

human islets and rat β-cells

Overexpression of CTSH decreases cytokine-

induced apoptosis and increases insulin

expression in INS-1 cells

Children with T1D who carries the SNP genotype causing

low CTSH expression have less residual β-cell function

Floyel et al. PNAS 2014

CTSH affects β-cell function

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CTSH

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Islets from Ctsh knockout mice contain less

insulin compared to wild-type mice

WT

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STAT1

CELL DEATH

gene transcription e.g.

iNOS, DP5, c-Myc, Bim

Nucleus

IRAK1

TRAF6

JNK

NFkB

Plasma membrane IL-1RI IL-1AcP

MAPKK

IL-1 IFNγ IFNγ

IFNγR1 IFNγR2

IKK ERK p38

Transcription factors

e.g. c-Jun, JunD

Non-transcription factors

e.g. Bcl-2 family members

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CTSH decreases cytokine signalling

CTSH overexpression changes a limited number of β-cell genes

Fløyel et al, In preparation

Genes affecting beta-cell function in type 1 diabetes

Fløyel et al (2016) Curr Diabetes Rep

‘Classical’ immune genes are important in β-cell function

Challenges Define ‘true’ risk (study the pre-diabetic phase) Disease classification (e.g. based on biomarkers) Uncover novel mechanisms (in vitro and in vivo studies) Guiding therapeutic options

How will we address these issues? 1. The identification and understanding of type 1

diabetes biomarkers 2. Prediabetes biomarker discovery 3. Gene regulation, non-coding RNAs and

epigenetics 4. New cohorts – e.g. TrialNet, TEDDY; 5. Collaboration (Local, national, and international)

An IMI2 EU Project 26 ACADEMIC INSTITUTIONS AND CLINICS 4 EFPIA PARTNERS 2 PATIENT ORGANIZATION 1 SME SMALL AND MEDIUM SIZED ENTERPRISE ECONOMY: TOTAL FUNDING 35 MIO EUR/7 YEARS START 2016

Some INNODIA objectives 1. Develop a European infrastructure for the recruitment,

detailed clinical phenotyping and bio‐sampling of a large cohort of newly diagnosed subjects with T1D and at risk family members

2. Establish a tight collaborative network of basic and clinical researchers working in a coordinated and focused way to address key knowledge gaps in relation to β-cell autoimmunity, leading to a better understanding of the pathogenesis of T1D and a cure for this disease

3. Conceive innovative clinical trial designs that exploit novel validated biomarkers allowing better subject stratification and functioning as surrogate endpoints, thus yielding shorter and more focused intervention studies of single or combined therapies

"You've got to be very

careful if you don't

know where you're

going, because you

might not get there." Yogi Berra

Thank you!