{"doi":"10.1101/2024.02.09.579673","title":"A Composite Biomarker Signature of Type 1 Diabetes Risk Identified via Augmentation of Parallel Multi-Omics Data from a Small Cohort","abstract":"Background: Biomarkers of early pathogenesis of type 1 diabetes (T1D) are crucial to enable effective prevention measures in at-risk populations before significant damage occurs to their insulin producing beta-cell mass. We recently introduced the concept of integrated parallel multi-omics and employed a novel data augmentation approach which identified promising candidate biomarkers from a small cohort of high-risk T1D subjects. We now validate selected biomarkers to generate a potential composite signature of T1D risk. Methods: Twelve candidate biomarkers, which were identified in the augmented data and selected based on their fold-change relative to healthy controls and cross-reference to proteomics data previously obtained in the expansive TEDDY and DAISY cohorts, were measured in the original samples by ELISA. Results: All 12 biomarkers had established connections with lipid/lipoprotein metabolism, immune function, inflammation, and diabetes, but only 7 were found to be markedly changed in the high-risk subjects compared to the healthy controls: ApoC1 and PON1 were reduced while CETP, CD36, FGFR1, IGHM, PCSK9, SOD1, and VCAM1 were elevated. Conclusions: Results further highlight the promise of our data augmentation approach in unmasking important patterns and pathologically significant features in parallel multi-omics datasets obtained from small sample cohorts to facilitate the identification of promising candidate T1D biomarkers for downstream validation. They also support the potential utility of a composite biomarker signature of T1D risk characterized by the changes in the above markers.","journal":"bioRxiv (Cold Spring Harbor Laboratory)","year":2024,"id":494243,"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":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9493,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2024-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":628501,"name":"Sung-Ting Chuang","orcid":"0000-0002-6433-2384","position":1,"is_corresponding":false},{"id":951916,"name":"Gang Ren","orcid":"0000-0002-3412-0831","position":2,"is_corresponding":false},{"id":804068,"name":"Mitsunori Ogihara","orcid":"0000-0002-5690-7854","position":3,"is_corresponding":false},{"id":237265,"name":"Bobbie‐Jo Webb‐Robertson","orcid":"0000-0002-4744-2397","position":4,"is_corresponding":false},{"id":262804,"name":"Ernesto Nakayasu","orcid":"0000-0002-4056-2695","position":5,"is_corresponding":false},{"id":342810,"name":"Péter Buchwald","orcid":"0000-0003-2732-8180","position":6,"is_corresponding":false},{"id":434282,"name":"Midhat H. Abdulreda","orcid":"0000-0002-0146-5876","position":7,"is_corresponding":false},{"id":450956,"name":"Óscar Garnica","orcid":"0000-0001-5064-2587","position":0,"is_corresponding":true}],"reference_count":106,"raw_metadata":null,"created_at":"2026-07-19T02:09:07.920649Z","pmid":"38405796","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":[]}