The cation efflux transporter ZnT8 (Slc30A8) is a major autoantigen in human type 1 diabetes

doi:10.1073/pnas.0705894104

The cation efflux transporter ZnT8 (Slc30A8) is a major autoantigen in human type 1 diabetes

Barbara Davis Center for Childhood Diabetes, University of Colorado at Denver and Health Sciences Center, PO Box 6511, 1775 North Ursula Street, Aurora, CO 80045

Edited by Diane Mathis, Harvard Medical School, Boston, MA, and approved September 6, 2007 (received for review June 22, 2007)

Abstract

Type 1 diabetes (T1D) results from progressive loss of pancreatic islet mass through autoimmunity targeted at a diverse, yet limited, series of molecules that are expressed in the pancreatic β cell. Identification of these molecular targets provides insight into the pathogenic process, diagnostic assays, and potential therapeutic agents. Autoantigen candidates were identified from microarray expression profiling of human and rodent pancreas and islet cells and screened with radioimmunoprecipitation assays using new-onset T1D and prediabetic sera. A high-ranking candidate, the zinc transporter ZnT8 (Slc30A8), was targeted by autoantibodies in 60–80% of new-onset T1D compared with <2% of controls and <3% type 2 diabetic and in up to 30% of patients with other autoimmune disorders with a T1D association. ZnT8 antibodies (ZnTA) were found in 26% of T1D subjects classified as autoantibody-negative on the basis of existing markers [glutamate decarboxylase (GADA), protein tyrosine phosphatase IA2 (IA2A), antibodies to insulin (IAA), and islet cytoplasmic autoantibodies (ICA)]. Individuals followed from birth to T1D showed ZnT8A as early as 2 years of age and increasing levels and prevalence persisting to disease onset. ZnT8A generally emerged later than GADA and IAA in prediabetes, although not in a strict order. The combined measurement of ZnT8A, GADA, IA2A, and IAA raised autoimmunity detection rates to 98% at disease onset, a level that approaches that needed to detect prediabetes in a general pediatric population. The combination of bioinformatics and molecular engineering used here will potentially generate other diabetes autoimmunity markers and is also broadly applicable to other autoimmune disorders.

Footnotes

^†To whom correspondence should be addressed. E-mail: john.hutton{at}uchsc.edu
Author contributions: J.M.W., G.S.E., H.W.D., and J.C.H. designed research; J.M.W., K.J., L.Y., O.M., S.A.S., H.W.D., and J.H. performed research; J.M.W., K.J., S.A.S., P.G., M.R., G.S.E., J.J., H.W.D., and J.C.H. contributed new reagents/analytic tools; J.M.W., K.J., L.Y., S.A.S., P.G., M.R., G.S.E., J.J., and J.C.H. analyzed data; and J.C.H. wrote the paper.
↵*Present address: Joslin Diabetes Center, 1 Joslin Place, Boston MA 02215.
The authors declare no conflict of interest.
This article is a PNAS Direct Submission.
This article contains supporting information online at www.pnas.org/cgi/content/full/0705894104/DC1.
Abbreviations:

GADA,

glutamate decarboxylase antibodies;

IAA,

antibodies to insulin;

IA2A,

IA2 antibodies;

ICA,

islet cytoplasmic autoantibodies;

T1D,

type 1 diabetes;

ZnTA,

ZnT8 antibodies.