Expression-Based Genome-Wide Association Study Links Vitamin D–Binding Protein With Autoantigenicity in Type 1 Diabetes is a research paper published in Diabetes (2016). On theSindex it has a DataRank of 1.4. It has been cited 36 times, with 34 citing works in its 1-hop citation network.
Type 1 diabetes (T1D) is caused by autoreactive T cells that recognize pancreatic islet antigens and destroy insulin-producing β-cells. This attack results from a breakdown in tolerance for self-antigens, which is controlled by ectopic antigen expression in the thymus and pancreatic lymph nodes (PLNs). The autoantigens known to be involved include a set of islet proteins, such as insulin, GAD65, IA-2, and ZnT8. In an attempt to identify additional antigenic proteins, we performed an expression-based genome-wide association study using microarray data from 118 arrays of the thymus and PLNs of T1D mice. We ranked all 16,089 protein-coding genes by the likelihood of finding repeated differential expression and the degree of tissue specificity for pancreatic islets. The top autoantigen candidate was vitamin D-binding protein (VDBP). T-cell proliferation assays showed stronger T-cell reactivity to VDBP compared with control stimulations. Higher levels and frequencies of serum anti-VDBP autoantibodies (VDBP-Abs) were identified in patients with T1D (n = 331) than in healthy control subjects (n = 77). Serum vitamin D levels were negatively correlated with VDBP-Ab levels in patients in whom T1D developed during the winter. Immunohistochemical localization revealed that VDBP was specifically expressed in α-cells of pancreatic islets. We propose that VDBP could be an autoantigen in T1D.
FAIR checklist signals are shown for context only and do not affect DataRank scoring.
Base Score Contribution
0.542
From this paper's citation signal
Citation Network Contribution
0.850
From 33 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 39% comes from its base citations and 61% from the citation network (33 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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