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Targeted Deep Sequencing in Multiple-Affected Sibships of European Ancestry Identifies
Rare Deleterious Variants in PTPN22 that Confer Risk for Type 1 Diabetes
Short title: Rare PTPN22 Variants Contributing to T1D
Yan Ge,1 Suna Onengut Gumuscu,2,3 Aaron R. Quinlan,4,5 Aaron J. Mackey,2,3 Jocyndra A.
Wright,1 Jane H. Buckner,6 Tania Habib,6 Stephen S. Rich,2,3 Patrick Concannon1,7
1Department of Pathology, Immunology, and Laboratory Medicine, University of Florida,
Gainesville, FL
2Center for Public Health Genomics, University of Virginia, Charlottesville, VA
3Department of Public Health Sciences, University of Virginia, Charlottesville, VA
4Department of Human Genetics, University of Utah, Salt Lake City, UT
5Department of Biomedical Informatics, University of Utah, Salt Lake City, UT
6Translational Research Program, Benaroya Research Institute at Virginia Mason, Seattle, WA
7Genetics Institute, University of Florida, Gainesville, FL
Corresponding author:
Name: Patrick Concannon
Address: University of Florida Genetics Institute, 2033 Mowry Road, CGRC Room 115, Box
103610, Gainesville, FL 32610
Tel: (352) 294 5735
Fax: (352) 273 8284
1
Diabetes Publish Ahead of Print, published online December 2, 2015 Diabetes Page 2 of 47
Email: [email protected]
Word count: 3,932
2 tables, 4 figures, 3 supplementary tables, and 2 supplementary figures
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ABSTRACT
Despite the finding of over 40 risk loci for type 1 diabetes (T1D), the causative variants and
genes remain largely unknown. Here, we sought to identify rare deleterious variants of moderate
to large effects contributing to T1D. We deeply sequenced 301 protein coding genes located in
49 previously reported T1D risk loci in 70 T1D cases of European ancestry. These cases were
selected from putatively high risk families that had three or more siblings diagnosed with T1D at
early ages. A cluster of rare deleterious variants in PTPN22 was identified, including two novel
frameshift mutations (ss538819444 and rs371865329) and two missense variants (rs74163663
and rs56048322). Genotyping in 3,609 T1D families showed that rs56048322 was significantly
associated with T1D, and that this association was independent of the T1D associated, common
variant rs2476601. The risk allele at rs56048322 affects splicing of PTPN22 resulting in the
production of two alternative PTPN22 transcripts and a novel isoform of LYP (the protein
encoded by PTPN22). This isoform competes with the wild type LYP for binding to CSK and
results in hyporesponsiveness of CD4+ T cells to antigen stimulation in T1D subjects. These
findings demonstrate that in addition to common variants, rare deleterious variants in PTPN22
exist and can affect T1D risk.
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INTRODUCTION
Type 1 diabetes (T1D) results from the autoimmune destruction of insulin producing β cells in the pancreatic islets, culminating in complete insulin deficiency and lifelong reliance on administration of exogenous insulin. Although there exist rare monogenic forms of T1D (1,2), the common form is regarded as genetically complex, arising from the actions, and possible interactions, of multiple genetic and environmental risk factors. The human leukocyte antigen
(HLA) region on chromosome 6p21 accounts for approximately half of the genetic risk for T1D
(3,4). Genome wide association studies (GWAS) and meta analyses have identified over 40 additional, non HLA T1D risk loci (5–13), most of which have modest individual effects on disease risk (14).
Despite the identification of numerous T1D associated genomic regions from GWAS, the specific causative variants for T1D located in these, and other regions of the genome, as well as the genes they impact, remain largely unknown. Linkage disequilibrium within disease associated regions limits the power to pinpoint, by association mapping, the causative variants among a number of tightly correlated, and common, alleles at different polymorphic sites.
Additional difficulties are posed by associations detected at sites that are neither coding nor obviously regulatory and, therefore, without predicted biological functions.
One solution to these challenges may lie in the identification of infrequent or rare protein
altering variants, which might be expected to cluster in the gene or genes relevant to pathogenesis in a disease associated region and, having more readily discernible effects on gene
function, could provide insights into the role of the gene in pathogenesis. In a prior study of a
subset of T1D associated loci, the exons and splice sites of 10 candidate genes in T1D cases and
healthy controls were deeply sequenced (15). Four infrequent variants (minor allele frequency,
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MAF, <3%) in IFIH1 were found to be independently associated with lower risk for T1D,
providing important clues as to the role of IFIH1 in T1D pathogenesis.
In the current study, we searched for rare deleterious variants of moderate to high
penetrance by deep sequencing of the coding regions of 301 genes in 49 non HLA T1D risk loci
in T1D cases from families with three or more siblings diagnosed with T1D at early ages. Such
families are rare and putatively at high risk, given that the risk to siblings of a T1D case is
approximately 6% (16). We identified a cluster of rare deleterious variants in PTPN22 and found
that one of them, rs56048322, affected the splicing of PTPN22 transcripts and the function of
PTPN22 in T cells.
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RESEARCH DESIGN AND METHODS
Human Subjects
Genomic DNA samples from T1D affected sib pairs (ASP) and trio families were obtained from two sources: the Human Biological Data Interchange (HBDI) (375 ASP families, n = 1,840) (17,18) and the Type 1 Diabetes Genetics Consortium (T1DGC) (3,234 ASP/trio families, n = 12,424) (19). DNA and peripheral blood mononuclear cells (PBMC) were obtained from the Benaroya Research Institute Immune Mediated Disease Registry for Translational
Research. Research protocols were approved by the Benaroya Research Institute Institutional
Review Board.
Selection Criteria
Potential high risk T1D families were identified based on the following criteria: (1) the parents of the T1D cases were of European ancestry and had three or more children diagnosed with T1D at or after one year of age (to exclude neonatal diabetes) and prior to 21 years; and (2) neither of the parents had T1D (to reduce the risk of selecting subjects with dominantly inherited maturity onset diabetes of the young, MODY).
Targeted Deep Sequencing and Bioinformatic Analyses
For sequencing, ten genomic DNA samples were combined into each of 7 pools, and libraries were constructed using the Paired End Sample Preparation kit (Illumina). Target regions were enriched using the SureSelect Paired End Target Enrichment System (Agilent
Technologies). Seven target enriched libraries were sequenced on an Illumina Genome Analyzer
II, and 63 bp paired end reads were generated.
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The sequencing reads were aligned to the UCSC hg18 human reference genome with the
Burrows Wheeler Aligner (version 0.5.9) (20). PCR duplicate reads were removed using
SAMtools, and one sorted Binary Alignment/Map (BAM) file was generated and indexed for
each sequencing library (21). Single nucleotide polymorphisms (SNPs) and indels were
identified using FreeBayes (version 0.5.1) and the Genome Analysis Toolkit (GATK, version
2.4 9) (22), respectively. Sequencing depths were calculated using the Picard package (version
1.87). Variants were annotated using the Variant Effect Predictor (VEP, version 71) (23). The
impacts of missense variants on protein functions were predicted using SIFT (version 5.0.2) (24)
and PolyPhen (version 2.2.2) (25). Variants with the following consequences were considered
deleterious: frameshift, in frame insertion/deletion, stop codon lost or gained, predicted
damaging missense by both SIFT and PolyPhen, or occurring in a splice donor or acceptor
region. A variant was regarded as rare if its MAF was ≤0.00036 in European populations; this
corresponded to a probability of 0.05 of detecting a variant allele in 70 randomly sampled
individuals.
Genotyping
The MGB Eclipse system (ELITechGroup, EPOCH BIOSCIENCES) was used to
genotype 3,609 T1D ASP/trio families consisting of 14,264 participants collected by the HBDI
and the T1DGC, according to the manufacturer’s protocol.
Cell Isolation, Stimulation, and Culture
Primary B cells, T cells, and monocytes were purified from PBMC by positive selection
with CD19, CD3, and CD14 magnetic beads, respectively (Miltenyi). For quantitative PCR,
CD4+ T cells were purified from PBMC by negative selection using the human CD4+ T cell
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isolation kit (Miltenyi), and were stimulated with 2.5 ug/ml plate bound anti CD3 antibody
(clone OKT3) and 0.25 ug/ml soluble anti CD28 antibody for 0, 6, 18, and 24 hours. Jurkat cells
and B lymphoblastoid cell lines (B LCLs) were cultured in RPMI 1640 medium supplemented
with 10% FBS (Thermo Scientific HyClone), 2.05 mM L glutamine, 100 units/ml penicillin, 100
o ug/ml streptomycin, and 1 mM sodium pyruvate (Life Technologies) at 37 C with 5% CO2.
Quantitative RT-PCR
Total RNA was extracted using the RNeasy Mini kit (QIAGEN), and contaminating genomic DNA was removed with Ambion DNA freeTM DNase Treatment and Removal
Reagents (Life Technologies). First strand cDNA was synthesized using random hexamer primers and Superscript II Reverse Transcriptase (Life Technologies). PCRs containing SYBR
Green I and ROX reference dye were performed on an ABI 7900HT Fast Real Time PCR
System (Life Technologies). All samples were tested in triplicate. Relative gene expression levels were calculated using the comparative CT method (26), where CT = mean CT (PTPN22) –
mean CT (GAPDH). The primers used for the assay are provided in Supplementary Table 1. The
heat map in Fig. 1C was generated using the 2 CT values and the R packages, gplots and
RColorBrewer.
Co-immunoprecipitation and Immunoblotting
Cells were lysed in EBC lysis buffer (50 mM Tris HCl, pH 7.5, 120 mM NaCl, 0.5% NP
40, and 1 mM EDTA) containing protease and phosphatase inhibitors (Complete Mini and
PhosSTOP, Roche). One milligram of lysate in 1 ml EBC lysis buffer was pre cleared with
GammaBind Plus Sepharose beads (GE Healthcare) for 2 h at 4oC and then incubated overnight at 4oC with 0.6 g rabbit anti CSK antibody (Cell Signaling TECHNOLOGY, #4980) or 0.6 g
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normal rabbit IgG (SouthernBiotech). Immune complexes were captured by incubating the lysate
with 20 l GammaBind Plus Sepharose beads for 2 h at 4oC. The beads were washed four times
with 1 ml EBC lysis buffer containing 1 mM PMSF and 1 mM sodium orthovanadate. The
immunoprecipitates were eluted by heating the beads for 5 min at 95oC in 25 l LDS sample
buffer (Life Technologies) containing 50 mM DTT.
Whole cell lysates and immunoprecipitates were resolved on 7% NuPAGE Novex Tris
Acetate gels (Life Technologies). Immunoblotting was performed using antibodies to LYP
(R&D Systems, AF3428, 0.3 g/ml), CSK (Abnova, H00001445 M01, 1 g/ml), and γ Tubulin
(Sigma Aldrich, T6557, 1:10,000 dilution).
Calcium Flux Measurement
Previously frozen PBMC were incubated with the cell permeant dye, Indo 1 AM
(Molecular Probes), for 45 minutes at 37°C, and then surface stained with anti CD8 PE/Cy5
(BioLegend), CD27 APC (BD Biosciences), CD45RO PE (BD Biosciences), CD45RA FITC
(BioLegend), CD4 PerCP/Cy5.5 (BioLegend), and CD19 PE/Cy7 (BioLegend). The indo 1
fluorescence ratio was acquired as a function of time on an LSRII flow cytometer, and kinetics
curves were generated using the FlowJo software. Collection of a 30 second or 1 minute baseline
was followed by stimulation with 10 g/ml soluble anti CD3 (clone UCHT1, BioLegend), 20
g/ml anti κ + anti λ F(ab’)2 (Southern Biotech), or 1 g/ml ionomycin. All the calcium flux
profiles were generated using a standard protocol.
Statistical Analyses
The Family Based Association Test (FBAT) program (version 2.0.4) was used for single
marker association tests and haplotype analyses, as well as for checking Mendelian inconsistency
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in genotyping (27). Minor allele frequencies were estimated using PLINK (v.1.07) (28).
Conditional association analyses were conducted using the UNPHASED program (version 3.1)
(29).
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RESULTS
Identification of Rare Deleterious Variants by Targeted Sequencing of T1D Cases from
Multiple-Affected Families of European Ancestry
We applied our selection criteria for putatively high risk families (see Research Design
and Methods) and chose 70 T1D cases of European ancestry from the T1D affected families
collected by the T1DGC. In these 70 cases, the coding regions of all 301 known protein coding
genes located in 49 T1D associated chromosomal regions, excluding the HLA region, were
captured (1.12 Mb per subject) (Supplementary Table 2) and sequenced in pools of 10 subjects,
each.
For each pool, on average, 97.64% of the target regions were covered by at least two
reads (ranging from 97.56% to 97.74%), and 93.4% of the target bases were covered at ≥30x
(ranging from 92.9% to 94.0%). All pools had mean target coverage of >660x (ranging from
661x to 1018x). Fifty one genes were identified that harbored two or more rare (MAF ≤0.00036)
predicted deleterious variants. In the T1D associated region on chromosome 1p13.2, 10 genes
were sequenced; only two rare (MAF ≤0.00036) predicted deleterious variants were identified,
and both occurred in PTPN22—a 4 bp deletion in exon 11 (ss538819444) and a 1 bp deletion in
exon 13 (rs371865329). Two infrequent (MAF <0.01) coding missense variants with predicted
deleterious effects, rs74163663 (p.Arg748Gly) and rs56048322 (p.Lys750Asn), were also
identified, and, similarly, clustered in PTPN22. A simulation in which 10,000 sets of 70 T1D
cases were randomly selected from the initial study population showed that the probability of
identifying all four of the deleterious variants seen in PTPN22 was 1.3 x 10 4, suggesting that the
criteria used to define high risk T1D families had effectively enriched for infrequent variants
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with predicted deleterious effects in PTPN22. Of note, the selection criteria did not enrich for the
most common genetic risk variants for T1D, which are high risk HLA DRB1 DRA1 DQB1
haplotypes (Supplementary Table 3).
PTPN22 is an established risk locus for T1D and several other autoimmune disorders
(30–34). Risk at PTPN22 is associated with the minor allele at a common non synonymous
coding region SNP, rs2476601, which results in the missense substitution R620W.
The Rare Allele of rs56048322 in PTPN22 Has an Independent Effect on T1D Risk
We genotyped ss538819444, rs371865329, rs74163663 and rs56048322 in 14,264
individuals from 3,609 T1D affected ASP/trio families. Single marker family based association
tests (27), were performed to examine association between variants in PTPN22 and T1D.
Positive and negative Z scores of FBAT indicate risk and protection, respectively. The single
marker FBAT showed that the minor alleles of rs56048322 (P = 0.0014), rs74163663 (P =
0.028), and rs2476601 (P = 8.62 x 10 36) were each associated with T1D (Table 1). Comparable results were obtained assessing sharing of alleles at these markers among ASPs by the transmission disequilibrium test (TDT). No association with T1D was detected for ss538819444 or rs371865329, but their rarity in the population (each occurred in fewer than three families) limited power to assess their effects on T1D risk.
Six haplotypes for ss538819444, rs371865329, rs74163663, rs56048322, and the common T1D risk variant, rs2476601, were identified in the T1D ASP/trio families (Table 2).
(Differences in the numbers of informative families shown in Tables 1 and 2 are due to missing genotypes.) The H2 haplotype carrying the minor 1858T risk allele at rs2476601 was significantly associated with T1D (P = 1.81 x 10 34), as expected. The H3 haplotype, which
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carried the 2250C risk allele at rs56048322, was also associated with T1D (P = 0.0014) in the
absence of the common risk allele at rs2476601 (Table 2). The minor allele at rs56048322 still
exhibited a significant association with T1D (P = 0.0003) after conditioning on rs2476601. The
minor allele of rs74163663 co occurred with the 1858T risk allele at rs2476601 (Table 2), and
showed a marginally significant association with T1D (P = 0.06) after conditioning on
rs2476601.
The Minor Allele of rs56048322 Is Associated with the Production of Alternative PTPN22
Transcripts
The SNP rs56048322 alters the last nucleotide of exon 18 of PTPN22. In a prior report,
PBMC from one individual heterozygous at rs56048322 produced an alternative PTPN22
transcript in which exon 17 was spliced to exon 19 creating a premature stop codon at the exon
17 to 19 junction (Fig. 1A) (35). In B LCLs derived from subjects heterozygous at rs56048322,
both this previously reported alternative transcript and a second more common alternative
PTPN22 transcript, resulting from run on transcription into intron 18, were detected (Fig. 1C).
These alternative transcripts and the full length PTPN22 transcript were quantified in primary T
cells, B cells, and monocytes from five subjects, including one healthy control, two rheumatoid
arthritis (RA) and two relapsing polychondritis (RP) cases (Fig. 1B). The use of samples from
subjects with autoimmune disorders other than T1D were necessitated by both the rarity of
carriers of the minor allele at rs56048322 and the availability of comparably treated, viably
frozen PBMCs from these subjects. As shown in Fig. 1C, the presence of the risk allele was
associated with a substantial enrichment for the two alternative PTPN22 transcripts in all three
primary cell types and in B LCLs derived from T1D families (Fig. 1C). The average relative
expression level of the intron 18 run on transcript in the heterozygous B LCLs was 72 times as
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high as that in the B LCLs homozygous for the major allele (Fig. 1C). The exon 18 skipping
transcript was detected only at low levels in individuals heterozygous at rs56048322 (Fig. 1C). In
B 1.1 and B 1.2, which were heterozygous for c.878_881delAGAT, transcripts carrying the 4 bp
deletion were detected by Sanger sequencing of PCR products generated from cDNA, but the
relative expression level of full length PTPN22 was not evidently lower in these cells than in the
wild type B LCLs (Fig. 1C).
In human primary CD4+ T cells stimulated with anti CD3 and anti CD28 antibodies, the amounts of the full length PTPN22 transcript peaked at 6 hours post stimulation and then decreased to below basal levels by 24 hours, regardless of the genotype at rs56048322 (Fig. 2A,
2B). The intron 18 run on PTPN22 transcript was expressed at low levels in CD4+ T cells from subjects homozygous for the major allele of rs56048322, and the expression levels decreased upon stimulation (Fig. 2A, 2C). In contrast, in CD4+ T cells from carriers of the risk allele of
rs56048322, the amounts of the intron 18 run on transcript, which were markedly higher than
those in the non carriers, increased upon stimulation and peaked at 6 hours (Fig. 2A, 2C) as the
full length transcript did. The exon 18 skipping PTPN22 transcript was detected only in carriers
of the risk allele of rs56048322, and the expression levels decreased upon stimulation (Fig. 2A,
2D).
The Rare Allele of rs56048322 Produces a Novel LYP Isoform that Can Bind to CSK
PTPN22 encodes the intracellular lymphoid protein tyrosine phosphatase (LYP) which
regulates signaling through the T and B cell receptors. LYP forms a complex with the C terminal
Src kinase (CSK), a negative regulator of T cell receptor (TCR) mediated signaling. This
complex of LYP and CSK is reported to exert synergistic inhibition on TCR signaling (36). LYP
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has four proline rich motifs (P1 P4) at the C terminus, of which the P1 motif interacts with the
SH3 domain of CSK (37,38). The tryptophan residue introduced at position 620 by the risk allele
of rs2476601 is located in the P1 motif and decreases the binding of LYP to CSK (30). It has
been proposed that this effect on the interaction between LYP and CSK is responsible for the risk
for autoimmunity associated with the risk allele at rs2476601. In whole cell lysates derived from
B LCLs heterozygous at rs56048322, two LYP isoforms were detected, one corresponding to the
predicted size for full length LYP (91.7 kDa) and the second to the predicted size for the intron
18 run on product (87.2 kDA). Both isoforms could be co immunoprecipitated with CSK at
comparable levels (Fig. 3B), indicating comparable ability to bind to CSK.
The Rare Allele of rs56048322 Impairs TCR-Mediated Calcium Flux in CD4+ T Cells
Although the association of the minor allele at rs2476601 with autoimmunity is well
established, there are conflicting reports as to whether this allele results in loss or gain of
function of LYP (30,39–43). The availability of a second independent risk allele affecting the
coding region of PTPN22 provided an opportunity to further explore the mechanism whereby
PTPN22 mediates risk for autoimmunity. To determine the effects of the independent T1D risk
allele of rs56048322, intracellular calcium flux induced by TCR crosslinking in CD4+ T cells
from the peripheral blood of a healthy subject and age matched cases with T1D or RA was
compared (Fig. 4). All subjects were homozygous for the non risk 1858C allele at rs2476601.
Compared to the cases homozygous for the major allele of rs56048322, CD4+ T cells from cases
heterozygous at rs56048322 exhibited decreased TCR mediated intracellular calcium flux (Fig.
4), consistent with a gain of function. However, the risk allele of rs56048322 did not impair
calcium flux in TCR stimulated CD4+ T cells from non autoimmune control subjects
(Supplementary Fig. 1), nor in human primary B cells stimulated via B cell receptor (BCR)
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(Supplementary Fig. 2).
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DISCUSSION
In this study, we searched for rare risk variants of moderate to large effect sizes in
chromosomal regions implicated as harboring risk loci for T1D in prior GWAS. We
implemented a family based approach, based on the hypothesis that T1D families having
multiple affected siblings with early ages at onset would be enriched for risk variants with large
effect sizes which might be expected to be rare in the population. We focused on rare variants
that had substantial predicted impacts on the encoded proteins, including protein altering indels,
stop gain/loss variants, and splice variants, with the expectation that their distribution among
genes in a region might identify the relevant causative gene and their predicted deleterious
effects provide insight into the mechanism whereby the implicated gene might act to confer risk
for T1D. Multiple novel deleterious variants in different T1D risk regions were identified by this
approach. Functional studies were performed for one gene, PTPN22, where the enrichment for
rare indels and predicted deleterious missense variants supported its role as the causative gene in
the region and provided an opportunity to explore the mechanism of its effect on T1D risk.
Conflicting results have been reported as to whether the risk allele of rs2476601 in
PTPN22 which encodes an R to W amino acid substitution at position 620 results in loss (30,39)
or gain (40–43) of function. Two of the deleterious variants identified by sequencing of PTPN22
were predicted to result in premature termination, consistent with a possible loss of function, but
had MAFs of <0.0002, limiting the ability to carry out functional studies. In B lymphoblastoid
cells from carriers of these variants, no alternative PTPN22 isoforms were observed and the
wild type isoform occurred at normal levels. A rare, predicted deleterious missense variant,
rs74163663, was detected but only on haplotypes also containing the common risk allele at
rs2476601. The minor allele of the remaining rare deleterious variants identified in PTPN22,
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rs56048322, was associated with increased T1D risk independent of the common T1D associated
risk allele of rs2476601 (Table 2). The risk allele of rs56048322 interfered with the correct
splicing of PTPN22 resulting in production of two alternative PTPN22 transcripts, one of which was degraded upon T cell activation, while the other generated significant amounts of a lower molecular weight C terminally truncated LYP isoform. Unlike the product of the risk allele at rs2476601 (30), this LYP isoform bound CSK through its P1 domain but lacked the C terminal
P3 and P4 proline rich domains which likely mediate additional, as yet uncharacterized, protein protein interactions. Despite the ability of its protein product to bind CSK, the rs56048322 risk allele, similar to the risk allele at rs2476601, resulted in blunted TCR mediated calcium flux in
CD4+ T cells, a phenotype most pronounced in the memory CD4+ T cell compartment (data not shown) (41). Unlike carriers of the rs2476601 risk allele, carriers of the risk allele at rs56048322 displayed more variability in the degree of T cell hyporeactivity, and this phenotype was only observed in subjects with existing autoimmunity. No effect of rs56048322 was observed on
BCR mediated calcium flux in CD19+ B cells (Supplementary Fig. 2), and further investigation
will be required to determine whether rs56048322 affects signaling in specific subtypes of B
cells as rs2476601 does (41). It should be noted that carriers of the rs56048322 risk allele are
rare. Only 6 carriers were available for the functional studies carried out here; a comprehensive
description of immune phenotypes associated with this variant will require further ascertainment
and study. Nevertheless, the findings presented here suggest that the rare risk allele at
rs56048322 and the more common risk allele at rs2476601 exert similar effects on T cell
activation and function, but likely do so through different mechanisms. We propose that both act by dominant interference, producing a protein product either lacking or defective in selected proline rich domains but differing in which domains are affected and, presumably, what
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interactions are disrupted. The evidence from these two, independently disease associated
genetic variants, acting by distinct mechanisms but resulting in a common phenotype, suggests
that risk alleles at PTPN22 contribute to T1D susceptibility via blunted TCR signaling that may
be due to either direct effects of the risk variants or compensatory alterations in this pathway in
response to these variants.
In addition to providing insight into the mechanism of action of PTPN22 in
autoimmunity, the enrichment we observed for rare deleterious variants in this single gene in the
1p13.2 region raises the possibility that resequencing in high risk families, as defined here, could
be used to identify causative genes in other regions delineated by GWAS, or more broadly to
identify novel risk loci. Although we did identify additional deleterious variants in other T1D
associated regions in our study, the small number of the families studied (n = 70) limited our
power to detect any enrichment for deleterious variants in single genes at additional sites.
Certainly, the use of high risk families has been instrumental in identifying highly penetrant risk
variants in various cancers. Our success in the current study with PTPN22 encourages the
application of this approach on a larger scale in autoimmunity. Of note, the T1DGC family
collection, which was ascertained based on the presence of at least two affected siblings, is
already enriched for high risk HLA DR DQ haplotypes; our selection criteria for high risk
families, which require one additional affected sibling, did not further increase the frequencies of
high risk HLA DR DQ haplotypes (Supplementary Table 3) but were effective at identifying
low frequency deleterious variants of T1D associated loci with lower overall risk than the HLA
locus. While the current study utilized a targeted approach focusing on chromosomal regions
previously implicated by GWAS, an exome sequencing approach would be more efficient and
offer the possibility of identifying novel risk loci not previously identified by GWAS. In the case
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of multiple sclerosis (MS), exome sequencing was recently performed in 43 affected individuals
selected from families with four or more MS affected members in more than one generation.
One novel loss of function variant was identified in CYP27B1 in one of the cases, and the variant was significantly associated with MS, indicating a causative role for CYP27B1 in MS (44).
Results such as these, and the findings from the current study, support the examination of the human exome in families with high disease burdens as an approach for the identification of causative genes and variants for common, autoimmune disorders.
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Acknowledgments. This research utilizes resources and data provided by the Type 1 Diabetes
Genetics Consortium, the NHLBI GO Exome Sequencing Project, and the ImmunoChip project.
We thank investigators and staff at the Benaroya Research Institute at Virginia Mason for subject
recruitment and sample processing.
Funding. This work was supported by National Institutes for Health Grants DK046635 and
DK085678 to P.C. and DK097672 to J.H.B.
Duality of Interest. No potential conflicts of interest relevant to this article were reported.
Author Contributions. Y.G., S.O., and P.C. designed the study. Y.G., S.O., A.J.M., J.A.W., and
T.H. performed research. J.H.B. and S.S.R. contributed new reagents/analytic tools. Y.G., S.O.,
and A.R.Q. analyzed data. Y.G. and P.C. wrote the paper. P.C. is the guarantor of this work and,
as such, had full access to all the data in the study and takes responsibility for the integrity of the
data and the accuracy of the data analysis.
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TABLE 1. Single-marker family-based association analysis of variants in the PTPN22 gene
Exon rsID cDNA Amino acid 22 12 11 MAF Famil Z P value
chang change y (n)
e
11 ss5388 c.878_ p.Gln293Ar 14,210 5 0 0.00018 2 0.447 0.65
19444 881del gfs*45
AGAT
13 rs3718 c.1040 p.Ile348Serf 14,184 6 0 0.00008 1 1.000 0.32
65329 delA s*14 8
14 rs2476 c.1858 p.Arg620Tr 10,600 3,30 341 0.12 1,023 12.489 8.62E 36
601 C>T p 3
18 rs7416 c.2242 p.Arg748Gl 14,154 22 0 0.00053 7 2.191 0.028
3663 A>G y
18 rs5604 c.2250 p.Lys750As 13,943 284 0 0.0087 93 3.190 0.0014
8322 G>C n
22, homozygous for the major allele; 12, heterozygous; 11, homozygous for the minor allele;
MAF, minor allele frequency; n, number of informative families. cDNA and amino acid changes
are based on NM_015967.5 and NP_057051.3, respectively. Z scores and p values are calculated
for the minor alleles.
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TABLE 2. Family-based haplotype association analysis of PTPN22
Haploty ss5388 rs3718 rs2476 rs7416 rs5604 Famil Freq. Z P value pe 19444 65329 601 3663 8322 y (n)
H1 2 2 2 2 2 0.872 1,072 12.98 1.68E 38
H2 2 2 1 2 2 0.119 1,012 12.24 1.81E 34
H3 2 2 2 2 1 0.008 92 3.19 0.0014
H4 2 2 1 1 2 0.001 7 2.19 0.028
<0.00 H5 1 2 2 2 2 2 0.45 0.65 1
<0.00 H6 2 1 2 2 2 1 1.00 0.32 1
1, minor allele; 2, major allele; freq., frequency; n, number of informative families.
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FIG. 1. Relative expression levels of three PTPN22 transcripts. (A) Schematic diagrams of the locations of c.2250G>C (rs56048322) and primers (indicated by arrows) used for quantitative real time PCR. Transcript 1 depicts full length PTPN22, transcript 2 an alternative PTPN22 transcript that extends into intron 18, and transcript 3 an alternative PTPN22 transcript that skips exon 18 by splicing exon 17 to exon 19. (B) Characteristics of human subjects. RA, rheumatoid arthritis; RP, relapsing polychondritis. (C) A heat map of the relative expression levels of the three PTPN22 transcripts. CT values were calculated by subtracting the mean CT of GAPDH
CT from the mean CT of PTPN22. The 2 values are represented by colors: dark red indicates high
relative expression levels, and light yellow low relative expression levels; gray indicates values below the detection limit of the assay. The pedigree information of the B lymphoblastoid cell
lines is shown (white circle = unaffected female; black circle = T1D affected female; black
square = T1D affected male). c.2250G/C heterozygous samples are marked in red. All the
subjects and cell lines are homozygous for the major, non risk allele of rs2476601 in PTPN22.
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FIG. 2. Relative expression levels of three PTPN22 transcripts in human primary CD4+ T cells
upon T cell receptor mediated stimulation. (A) Information on the human subjects in panel (B
D). Carriers of the minor, risk allele of rs56048322 are shown in red. All the subjects are
homozygous for the major, non risk allele of rs2476601 in PTPN22. RA, rheumatoid arthritis.
(B D) Primary CD4+ T cells from five human subjects were stimulated with anti CD3 and anti
CD28 antibodies for 0, 6, 18, and 24 hours. The relative expression levels of three PTPN22
+ transcripts (depicted in Fig. 1A) in the stimulated CD4 T cells are shown. CT values were
CT calculated by subtracting the mean CT of GAPDH from the mean CT of PTPN22, and the 2
values are shown.
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FIG. 3. Characterization of the effects of c.2250G>C on LYP. (A) Immunoblotting of whole cell
lysates from the following cell lines: Jurkat, GM12155, four B lymphoblastoid cell lines derived
from two T1D affected families, and HEK293T. The pedigree information and genotypes for
c.2250G>C (rs56048322) are shown (white circle = unaffected female; black circle = T1D
affected female; black square = T1D affected male). The c.2250G/C heterozygous genotype is
highlighted in bold. LYP was detected using an anti LYP antibody. The blot was stripped and re probed with an anti γ Tubulin antibody. (B) Whole cell lysates from B 3.1 and B 3.2 were
immunoprecipitated with a rabbit anti CSK antibody or normal rabbit IgG. The
immunoprecipitated samples and the whole cell lysates were subjected to immunoblotting with
an anti LYP antibody. The blot was stripped and re probed with an anti CSK antibody.
30 Page 31 of 47 Diabetes
FIG. 4. The risk allele of rs56048322 affects T cell receptor mediated intracellular calcium flux
in CD4+ T cells from subjects with T1D or RA. Previously frozen peripheral blood mononuclear
cells from a healthy subject and from subjects with T1D or RA were loaded with cell permeant
indo 1 AM dye and stained with antibodies against T cell surface markers. Shown are kinetics
profiles depicting the mean indo 1 ratio (violet/blue) as a function of time in gated total CD4+ T
cells before and after stimulation with 10 g/ml anti CD3 antibody. Percent maximal calcium
flux is expressed as [(peak anti CD3 flux – mean baseline)/(peak ionomycin flux – mean
baseline)] x100. All the subjects are homozygous for the major, non risk allele of rs2476601 in
PTPN22. RA, rheumatoid arthritis; T1D, type 1 diabetes.
31 Diabetes Page 32 of 47
86x60mm (300 x 300 DPI)
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96x72mm (300 x 300 DPI)
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132x243mm (300 x 300 DPI)
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91x63mm (300 x 300 DPI)
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Targeted Deep Sequencing in Multiple-Affected Sibships of European Ancestry
Identifies Rare Deleterious Variants in PTPN22 that Confer Risk for Type 1
Diabetes
Justification on the necessity of the online supplement
The supplementary tables and figures do not warrant inclusion in the main text, but they provide additional information related to the methods and data of the main text.
Supplementary Table 1 lists the primers used in the quantitative real-time PCR (Fig. 1 and 2). Supplementary Table 2 lists the protein-coding genes that were captured and deeply sequenced in this study. Supplementary Table 3 shows the distributions of HLA haplotypes in the 70 T1D cases sequenced in this study and in the initial T1DGC population from which the 70 cases were selected. Supplementary Figures 1 and 2 show intracellular calcium flux profiles in CD4+ T cells from subjects without autoimmune diseases and in CD19+ B cells, respectively. Page 37 of 47 Diabetes
Supplementary Table 1. Primers used for quantitative RT-PCR
Transcrip Forward primer (5’ to 3’) Reverse primer (5’ to 3’)
t
PTPN22 TCCTGACACCATGGAAAATTCA GGTGGATTCCTTGGTCCTTTG
transcript
1
PTPN22 GTGTAAAACTCCGAAGTCCTAAA CGGCATGTTTCCCAAAACTCT
transcript TCAG T
2
PTPN22 TCTTGCCGATGAAGATTAGTTTG CCAAAATTCAGAAATGAGCT
transcript AA GGA
3
GAPDH CAGCCGAGCCACATCGC CATGGGTGGAATCATATTGG
AACA
PTPN22 transcript 1 is the full-length PTPN22 transcript, PTPN22 transcript 2 the intron-
18-run-on transcript, and PTPN22 transcript 3 the exon-18-skipping transcript (see Fig.
1A).
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Supplementary Table 2. Known protein-coding genes in T1D-associated regions targeted in deep sequencing
T1D-associated Protein-coding genes regions
1p13.2 OLFML3, DCLRE1B, AP4B1, BCL2L15, PTPN22, HIPK1,
RSBN1, PHTF1, MAGI3, SYT6
1q31.2 RGS1
1q32.1 IL20, IL19, IL10, MAPKAPK2, DYRK3
2q11.2 CHST10, LONRF2, AFF3
2q12.1 SLC9A4, IL18RAP, IL18R1, IL1RL1, IL1RL2
2q24.2 GCA, IFIH1, FAP, KCNH7, GCG
2q32.2 STAT4
2q33.2 ICOS, CTLA4
3p21.31 TDGF1, LRRC2, RTP3, LTF, CCRL2, CCR5, CCR3, CCR2,
CCR1, XCR1, CXCR6, FYCO1
4p15.2 -
4q27 IL21, ADAD1, IL2, KIAA1109
5p13.2 UGT3A2, UGT3A1, CAPSL, IL7R, SPEF2
6q15 BACH2
6q22.32 CENPW
6q23.3 TNFAIP3
6q25.3 TAGAP, RSPH3, C6orf99 Page 39 of 47 Diabetes
7p15.2 HOXA7, HOXA6, HOXA5, HOXA4, HOXA3, HOXA2, HOXA1,
SKAP2, C7orf71, HOXA9
7p12.1 COBL
9p24.2 GLIS3
10p15.1 PFKFB3, RBM17, IL2RA
10p15.1 PRKCQ
10q22.3 ZMIZ1
10q23.31 RNLS
11p15.5 ASCL2, TH, INS, IGF2-AS, IGF2
12p13.31 CD69, CLECL1, CLEC2D, KLRB1
12q13.2 APOF, STAT2, IL23A, PAN2, CNPY2, CS, COQ10A,
ANKRD52, SLC39A5, NABP2, RNF41, SMARCC2, MYL6,
MYL6B, ZC3H10, ESYT1, PA2G4P4, IKZF4, RPS26P53,
ERBB3, SUOX, RAB5B, CDK2, PMEL
12q13.3 CTDSP2, AVIL, TSFM, METTL21B, METTL1, MARCH9,
CYP27B1, CDK4, AGAP2, TSPAN31, OS9, B4GALNT1,
ARHGEF25, DTX3, PIP4K2C, KIF5A, DCTN2, MBD6, MARS,
DDIT3, ARHGAP9, GLI1, INHBE, INHBC, R3HDM2, STAC3,
NDUFA4L2, SHMT2, NXPH4, LRP1, NAB2, STAT6,
TMEM194A, MYO1A, TAC3, ZBTB39, GPR182, RDH16,
SDR9C7, HSD17B6, PRIM1, NACA, PTGES3, ATP5B, BAZ2A,
RBMS2P1, XRCC6BP1
12q24.12 PTPN11, RPL6P27, HECTD4, TRAFD1, NAA25, ERP29, Diabetes Page 40 of 47
TMEM116, MAPKAPK5, ALDH2, ACAD10, BRAP, SH2B3,
ATXN2, FAM109A, CUX2, MYL2, CCDC63, RPH3A
14q24.1 ZFP36L1, C14orf181*
14q32.2 -
14q32.2 -
15q14 RASGRP1, C15orf53
15q25.1 CTSH, RASGRF1, MORF4L1, ADAMTS7
16p13.13 RMI2, PRM1, PRM2, PRM3, TNP2, SOCS1, CLEC16A, DEXI,
CIITA, LITAF
16p11.2 NFATC2IP, SPNS1, CD19, RABEP2, ATP2A1, SH2B1,
ATXN2L, TUFM, EIF3C, SULT1A2, SULT1A1, CCDC101,
IL27, APOBR, CLN3, EIF3CL, SBK1, LAT
16q23.1 CHST6, TMEM170A, CFDP1, BCAR1, CTRB1, CTRB2, ZFP1
17q12 THRA, MED24, CSF3, GSDMA, PSMD3, ORMDL3, GSDMB,
ZPBP2, IKZF3, GRB7, MIEN1, ERBB2, PGAP3, PNMT, TCAP,
PPP1R1B, STARD3, NEUROD2, CDK12, MED1, FBXL20,
STAC2, NR1D1
17q21.2 KRT24, KRT222, SMARCE1
18p11.21 PTPN2
18q22.2 CD226, DOK6
19p13.2 S1PR5, KEAP1, PDE4A, CDC37, TYK2, ICAM3, RAVER1,
FDX1L, ZGLP1, ICAM5, ICAM4, ICAM1
19q13.32 FKRP, STRN4, PRKD2, DACT3, SLC1A5 Page 41 of 47 Diabetes
20p13 SIRPG, SIRPB1, SIRPD
21q22.3 TMPRSS3, UBASH3A
22q12.2 LIF, HORMAD2, MTMR3, ASCC2, UQCR10, ZMAT5, CABP7,
NF2, THOC5, NIPSNAP1, OSM, NEFH, RFPL1
22q12.3 IL2RB
22q13.1 RAC2, SSTR3, C1QTNF6
Xp22.2 TMSB4X, TLR8
Xq28 BRCC3, CMC4, MTCP1, FUNDC2, H2AFB1, F8A1, F8,
MPP1, DKC1, GAB3, CTAG2, CTAG1B, VBP1
*C14orf181 was withdrawn from the online repository of HGNC-approved genes.
(http://www.genenames.org/ accessed on April 19, 2013).
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Supplementary Table 3. Distribution of HLA DR-DQ haplotypes associated with type 1 diabetes
Exon T1DGC Chi- Seq EUR square HLA * DRB1 DQA1 DQB1 Freq.† Freq.* P value Risk Haplotype 1 (S1) 04:05 03:01 03:02 0.021 0.025 1.00 Risk Haplotype 2 (S2) 04:01 03:01 03:02 0.264 0.281 0.74 Risk Haplotype 3 (S3) 03:01 05:01 02:01 0.307 0.341 0.48 Risk Haplotype 4 (S4) 04:02 03:01 03:02 0.043 0.035 0.80 Risk Haplotype 5 (S5) 04:04 03:01 03:02 0.064 0.050 0.61 Protective Haplotype 1 (P1) 07:01 02:01 03:03 0 0.001 1.00 Protective Haplotype 2 (P2) 14:01 01:01 05:03 0 0 / Protective Haplotype 3 (P3) 15:01 01:02 06:02 0 0.004 0.98 Protective Haplotype 4 (P4) 11:04 05:01 03:01 0 0.002 1.00 Protective Haplotype 5 (P5) 13:03 05:01 03:01 0 0.001 1.00 Risk Haplotype 1-5 0.700 0.732 0.42 Protective Haplotype 1-5 0 0.008 0.58 DR3/DR4 Diplotype 0.400 0.394 1.00
*Information on the risk DR-DQ haplotypes (S1-S5), the protective DR-DQ haplotypes
(P1-P5), and the haplotype/diplotype frequencies in 606 probands of T1D families of
European ancestry ascertained by the Type 1 Diabetes Genetics Consortium was obtained from Reference (1).
†Frequencies in the 70 T1D cases that were deeply sequenced in this study. Page 43 of 47 Diabetes
Supplementary Figure 1. The risk allele of rs56048322 does not impair T cell receptor-
mediated intracellular calcium flux in CD4+ T cells from subjects without autoimmune
diseases. Previously frozen peripheral blood mononuclear cells were loaded with cell-
permeant indo-1 AM dye and stained with antibodies against T cell surface markers.
Shown are kinetics profiles depicting the mean indo-1 ratio (violet/blue) as a function of
time in gated total CD4+ T cells before and after stimulation with 10 µg/ml of anti-CD3
antibody. Percent maximal calcium flux is expressed as [(peak anti-CD3 flux – mean
baseline)/(peak ionomycin flux – mean baseline)] x100. All the subjects are homozygous
for the major, non-risk allele of rs2476601 in PTPN22.
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Supplementary Figure 2. The risk allele of rs56048322 does not alter B cell receptor- mediated intracellular calcium flux in human primary CD19+ B cells. Previously frozen peripheral blood mononuclear cells were loaded with cell-permeant indo-1 AM dye and surface-stained with anti-CD19. Shown are kinetics profiles depicting the mean indo-1 ratio (violet/blue) as a function of time in gated total CD19+ B cells before and after stimulation with 20 µg/ml anti-κ + anti-λ F(ab’)2. Percent maximal calcium flux is expressed as [(peak anti-κ/λ flux – mean baseline)/(peak ionomycin flux – mean baseline)] x100. All the subjects are homozygous for the major, non-risk allele of rs2476601 in
PTPN22. T1D, type 1 diabetes. Page 45 of 47 Diabetes
References:
1. Erlich H, Valdes AM, Noble J, Carlson JA, Varney M, Concannon P, et al. HLA DR- DQ haplotypes and genotypes and type 1 diabetes risk: analysis of the type 1 diabetes genetics consortium families. Diabetes. 2008 Apr;57(4):1084–92.
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91x62mm (300 x 300 DPI)