{"doi":"10.1111/dom.15218","title":"Baseline leptin predicts response to metformin in adolescents with type 1 diabetes and increased body mass index","abstract":"There is an increased prevalence of overweight and obesity among children and adults with type 1 diabetes (T1D).1-4 Further, the rate of overweight and obesity continues to be on the rise among people with T1D compared with general population trends.5 This is problematic because obesity-induced insulin resistance increases exogenous insulin needs, with a higher risk of hypoglycaemia, weight gain, chronic inflammation, dyslipidaemia and long-term cardiovascular complications.4, 6 Metformin is the first-line diabetes therapy in overweight and obese children and adults with type 2 diabetes. It improves insulin sensitivity and inhibits hepatic gluconeogenesis.7 In a multicentre, double-blind,8 placebo-controlled randomized clinical trial of 140 adolescents with overweight or obesity and T1D (NCT01881828) randomized to either metformin or placebo for 26 weeks, the use of metformin as an adjunct to insulin therapy failed to show a sustained effect on glycaemic control after 26 weeks of treatment compared with controls. Despite a small decrease in HbA1c at 13 weeks in the metformin group, mean HbA1c levels increased by 26 weeks in both groups. However, metformin therapy was associated with a reduction in weight, body mass index (BMI), percent body fat (%BF) and total daily insulin dose (TDID). Because the original trial did not show a sustained glycaemic response and effect, as measured by HbA1c, we selected reduction in TDID, which was a positive outcome of the trial, to determine predictors of response. Here, we aimed to determine predictors of response to metformin therapy; in particular, we selected percentage (%) change in TDID. We hypothesized that baseline phenotypic or metabolic predictors may help better identify youth with T1D with a higher reduction in %ΔTDID in response to metformin therapy. We analysed data from the T1D Exchange Clinic Network Metformin Randomized Clinical Trial8 (NCT01881828). Detailed methods for this study were previously described.8 For this analysis, data were extracted from the publicly available dataset as a text file, and Microsoft software was used to convert the data tables to usable .xlsx files. The data were then cleaned, and random checks were performed to ensure accuracy of the data conversion and extraction. Out of the 140 participants, 122 (61 in each of the placebo and the metformin arms) had available data on anthropometrics, physical examinations and laboratory evaluations at baseline, 13 and 26 weeks. Figure S1 shows the analysis flow at each time point and the outcome measures of interest. Statistical analyses were conducted using MATLAB (https://www.mathworks.com/, V.R2019b) and R software (RStudio: Integrated Development for R). Between-group comparisons were made using a Student's t-test while within-group comparisons across multiple time points were performed using a paired t-test. Correlation values were computed via the Spearman rank correlation method under the ‘corrplot’ package in R. Linear regression analyses were performed using the ‘fitlm’ function in MATLAB. TDID was quantified as units/kg of body weight/day. The primary outcome was the relative percentage change in TDID (%ΔTDID) and was calculated as % ΔTDID = 100 * TDI D 13 weeks or 26 weeks − TDI D baseline / TDI D baseline , at 13 and 26 weeks, respectively. The regression models adjusted for potential confounders included participant's age, diabetes duration, sex, race, BMI z-score and %BF at baseline. P values less than .05 were considered statistically significant. Comparisons for reduction in TDID were performed within each arm. Table S1 shows the baseline demographic and clinical data for individuals in each arm. We observed a statistically significant reduction in TDID at both 13 and 26 weeks compared with baseline (P < .0001 at both time points) in the metformin arm. In addition, we observed a reduction in TDID only at 26 weeks in the placebo arm (P < .001) (Figure S2 and Table S2). Linear regression models we","journal":"Diabetes Obesity and Metabolism","year":2023,"id":388553,"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":1,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.958,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2023-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":560367,"name":"Souptik Barua","orcid":"0000-0002-1675-8874","position":1,"is_corresponding":false},{"id":862091,"name":"Johnny Wang","orcid":"0000-0001-5021-681X","position":2,"is_corresponding":false},{"id":936936,"name":"Ashutosh Sabharwal","orcid":"0000-0003-1898-5787","position":3,"is_corresponding":false},{"id":456461,"name":"Ingrid Libman","orcid":"0000-0002-0255-4555","position":4,"is_corresponding":false},{"id":431893,"name":"Fida Bacha","orcid":"0000-0002-9942-1889","position":5,"is_corresponding":false},{"id":7391,"name":"Kristen J. Nadeau","orcid":"0000-0002-0477-3356","position":6,"is_corresponding":false},{"id":513346,"name":"Mustafa Tosur","orcid":"0000-0002-2111-271X","position":7,"is_corresponding":false},{"id":7390,"name":"María J. Redondo","orcid":"0000-0001-5871-4645","position":8,"is_corresponding":false},{"id":577042,"name":"Heba M. Ismail","orcid":"0000-0003-0102-0030","position":0,"is_corresponding":true}],"reference_count":12,"raw_metadata":null,"created_at":"2026-07-19T01:18:18.214733Z","pmid":"37485878","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":[]}