{"doi":"10.1101/2025.05.14.654045","title":"3D imaging of human pancreas suggests islet size and endocrine composition influence their loss in type 1 diabetes","abstract":"Summary A high-definition description of pancreatic islets would prove beneficial for understanding the pathophysiology of type 1 diabetes (T1D), yet significant knowledge voids exist in terms of their size, endocrine cell composition, and number in both health and disease. Here, 3-dimensional (3D) analyses of pancreata from control persons without diabetes (ND) revealed heretofore underappreciated frequencies (approximately 50%) of insulin-positive (INS+) glucagon-negative (GCG-) islets. Non-diabetic individuals positive for a single Glutamic acid decarboxylase autoantibody (GADA+) yet at increased risk for disease consistently demonstrated endocrine features, including islet volume and cell composition, closely resembling the age-matched ND controls. In contrast, pancreata from individuals with short-duration T1D demonstrated significantly reduced islet density and a dramatic loss of INS+GCG- islets with preservation of large INS+GCG+ islets. The size and cellular composition of pancreatic islets may, therefore, represent influential factors that impact β-cell loss during T1D disease progression. Graphical Abstract Highlights 3D imaging of non-diabetic (ND) pancreas suggests up to 50% of INS+ islets lack GCG INS+GCG- islets are typically small-sized in ND and preferentially lost in T1D In T1D pancreas, INS+ beta cells are preserved in large INS+GCG+ islets Islets from GADA+ individuals appear similar to ND for size and β-to-α cell ratios","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2025,"id":555567,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":3,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9228,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2025-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":251267,"name":"Amanda L. Posgai","orcid":"0000-0002-9491-0958","position":1,"is_corresponding":false},{"id":807521,"name":"Seth Currlin","orcid":null,"position":2,"is_corresponding":false},{"id":356517,"name":"Maigan A. Brusko","orcid":"0000-0002-4331-2202","position":3,"is_corresponding":false},{"id":707815,"name":"MacKenzie D. Williams","orcid":"0000-0003-3473-2747","position":4,"is_corresponding":false},{"id":283021,"name":"John S. Kaddis","orcid":"0000-0002-6752-7670","position":5,"is_corresponding":false},{"id":23923,"name":"Irina Kusmartseva","orcid":"0000-0003-2614-0813","position":6,"is_corresponding":false},{"id":477240,"name":"Clive Wasserfall","orcid":"0000-0002-3522-8932","position":7,"is_corresponding":false},{"id":251270,"name":"Martha Campbell‐Thompson","orcid":"0000-0001-6878-1235","position":8,"is_corresponding":false},{"id":23929,"name":"Mark A. Atkinson","orcid":"0000-0001-8489-4782","position":9,"is_corresponding":false},{"id":1452827,"name":"A. Rippa","orcid":"0000-0001-7300-8466","position":0,"is_corresponding":true}],"reference_count":50,"raw_metadata":null,"created_at":"2026-07-19T02:54:59.329539Z","pmid":"40463108","pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}