Diabetologia最新文献

{"title":"Beyond the loss of beta cells: a quantitative analysis of islet architecture in adults with and without type 1 diabetes","authors":"Nicolás Verschueren van Rees, Peter Ashwin, Conor McMullan, Lars Krogvold, Knut Dahl-Jørgensen, Noel G. Morgan, Pia Leete, Kyle C. A. Wedgwood","doi":"10.1007/s00125-025-06376-9","DOIUrl":"https://doi.org/10.1007/s00125-025-06376-9","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Aims/hypothesis</h3><p>The organisation and cellular architecture of islets of Langerhans are critical to the physiological regulation of hormone secretion but it is debated whether human islets adhere to the characteristic mantle–core (M-C) structure seen in rodents. It is also unclear whether inherent architectural changes contribute to islet dysfunction in type 1 diabetes, aside from the loss of beta cells. Therefore, we have exploited advances in immunostaining, spatial biology and machine learning to undertake a detailed, systematic analysis of adult human islet architecture in health and type 1 diabetes, by a quantitative analysis of a dataset of >250,000 endocrine cells in >3500 islets from ten individuals.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Formalin-fixed paraffin-embedded pancreatic sections (4 μm) from organ donors without diabetes and living donors with recent-onset type 1 diabetes were stained for all five islet hormones and imaged prior to analysis, which employed a novel automated pipeline using QuPath software, capable of running on a standard laptop. Whole-slide image analysis involved segmentation classifiers, cell detection and phenotyping algorithms to identify islets, specific cell types and their locations as (<i>x,y</i>)-coordinates in regions of interest. Each endocrine cell was categorised into binary variables for cell type (i.e. beta or non-beta) and position (mantle or core). A χ<sup>2</sup> test for independence of these properties was performed and the OR was considered to estimate the effect size of the potential association between position and cell type. A quantification of the M-C structure at islet level was performed by computing the probability, <i>r</i>, that the observed number of non-beta cells in the mantle is due to a random arrangement. The distribution of the <i>r</i> values for the islets in the study was contrasted against the <i>r</i> values of a digital population of equivalent randomly arranged islets, termed digital siblings. Both distributions of <i>r</i> values were compared using the earth mover’s distance (EMD), a mathematical tool employed to describe differences in distribution patterns. The EMD was also used to contrast the distribution of islet size and beta cell fraction between type 1 diabetes and control islets.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>The χ<sup>2</sup> test supports the existence of a significant (<i>p</i><0.001) relationship between cell position and type. The effect size was measured via the OR <0.8, showing that non-beta cells are more likely to be found at the mantle (and vice versa). At the islet level, the EMD between the distributions of <i>r</i> values of the observed islets and the digital siblings was emd-1d=0.10951 (0<emd-1d<1). The transport plan showed a substantial group of islets with a small <i>r</i> value, thus supporting the M-C hypothesis. The bidimensional distri","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":"1 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143507123","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Associations between the timing of 24 h physical activity and diabetes mellitus: results from a nationally representative sample of the US population","authors":"Qian Xiao, Qiuyu Feng, Martin K. Rutter, Gali Albalak, Heming Wang, Raymond Noordam","doi":"10.1007/s00125-025-06368-9","DOIUrl":"https://doi.org/10.1007/s00125-025-06368-9","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Aims/hypothesis</h3><p>Growing evidence suggests that timing may be an important aspect of physical activity that influences cardiometabolic health. However, the current literature is inconclusive regarding the time of day that physical activity offers the greatest metabolic advantages. We investigated associations between hourly physical activity levels and diabetes mellitus and glycaemic biomarkers in a cross-sectional and nationally representative sample of US adults.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>We studied 7074 adults (mean age 48 years; 52% women) from the National Health and Nutrition Examination Survey (2011–2014). Physical activity was measured by actigraphy. A monitor-independent movement summary (MIMS) unit was used to derive the total activity level (divided into quintiles) for hourly windows that were defined relative to sleep timing and according to clock time. The primary outcome was prevalent diabetes, and secondary outcomes included fasting glucose, fasting insulin, HOMA-IR and 2 h OGTT results.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>Physical activity levels in late morning and late afternoon were associated with lower adjusted odds of diabetes. Specifically, in late morning (8:01–9:00 h after the sleep midpoint), the highest quintile of activity was associated with a 35% decrease (OR 0.65; 95% CI 0.44, 0.96) in the odds of diabetes when compared with the lowest quintile, while in late afternoon (11:01–17:00 h after the sleep midpoint), the highest quintiles were associated with 56% and 36% lower odds (OR 0.44; 95% CI 0.29, 0.69 and OR 0.64; 95% CI 0.43, 0.95). Higher night-time activity was associated with higher odds of diabetes. Similar patterns of results were observed with OGTT data and across subgroups of age, gender, race/ethnicity, chronotype and sleep duration.</p><h3 data-test=\"abstract-sub-heading\">Conclusions/interpretation</h3><p>Our findings suggest that the timing of physical activity may modulate its metabolic effects.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":"65 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143462531","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification and interpretation of risk factors for Charcot foot.","authors":"Victoria E L Milbourn, Sicco A Bus, Frances Game, Jaap J van Netten","doi":"10.1007/s00125-025-06386-7","DOIUrl":"https://doi.org/10.1007/s00125-025-06386-7","url":null,"abstract":"","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":" ","pages":""},"PeriodicalIF":8.4,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457153","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Identification and interpretation of risk factors for Charcot foot. Reply to Milbourn VEL, Bus SA, Game F, van Netten JJ [letter].","authors":"Georgios Tsatsaris, Neda Rajamand Ekberg, Tove Fall, Sergiu-Bogdan Catrina","doi":"10.1007/s00125-025-06389-4","DOIUrl":"https://doi.org/10.1007/s00125-025-06389-4","url":null,"abstract":"","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":" ","pages":""},"PeriodicalIF":8.4,"publicationDate":"2025-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143457156","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Islet autoantibodies in Thai individuals individuals diagnosed with type 1 diabetes before 30 years of age: a large multicentre nationwide study","authors":"Nattachet Plengvidhya, Sarocha Suthon, Tassanee Nakdontri, Nipaporn Teerawattanapong, Saranya Ingnang, Watip Tangjittipokin","doi":"10.1007/s00125-025-06373-y","DOIUrl":"https://doi.org/10.1007/s00125-025-06373-y","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Aims/hypothesis</h3><p>Type 1 diabetes is categorised into autoantibody positive and autoantibody negative. Most type 1 diabetes research has focused on European populations, leaving a gap in understanding in relation to other ethnic groups, including Thai populations. This lack of data is significant given Thailand’s poor prevention and therapeutic management strategies. We aimed to investigate the frequency and distribution of islet autoantibodies among Thai individuals with long-standing type 1 diabetes diagnosed before the age of 30 years.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>We conducted a nationwide population-based study involving 48 hospitals in Thailand from May 2020 to September 2023, enrolling 953 participants. Demographic and clinical characteristics of individuals with autoantibody-positive and -negative type 1 diabetes were analysed. The autoantibodies GAD65, IA-2 and ZnT8 were measured using ELISA. A random C-peptide level was detected by electrochemiluminescence immunoassay.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>Thai individuals with autoantibody-negative type 1 diabetes comprised 34.2% of the population. Among all individuals, the frequency of GAD65, IA-2 and ZnT8 was 56%, 37% and 33%, respectively. Autoantibody-negative individuals with type 1 diabetes were older at diagnosis, had higher BMI and had higher random C-peptide levels compared with autoantibody-positive individuals with type 1 diabetes. Female individuals had a higher prevalence of type 1 diabetes than male individuals (58% vs 42%; <i>p</i>=1.531 × 10⁻⁵). The southern region of Thailand exhibited a distinct pattern of autoantibody frequency compared with other regions (<i>p</i>=0.0001561).</p><h3 data-test=\"abstract-sub-heading\">Conclusions/interpretation</h3><p>The frequency, distribution and characteristics of autoantibody-positive and -negative long-standing type 1 diabetes in Thailand showed uniqueness from other populations. This provides insight into the disease that may have implications for type 1 diabetes prediction, treatment and pathogenesis, especially in the Southeast Asian population.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":"14 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451494","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Epigenome-wide association study of incident type 2 diabetes in Black and White participants from the Atherosclerosis Risk in Communities Study","authors":"Sowmya Venkataraghavan, James S. Pankow, Eric Boerwinkle, Myriam Fornage, Elizabeth Selvin, Debashree Ray","doi":"10.1007/s00125-024-06352-9","DOIUrl":"https://doi.org/10.1007/s00125-024-06352-9","url":null,"abstract":"&lt;h3 data-test=\"abstract-sub-heading\"&gt;Aims/hypothesis&lt;/h3&gt;&lt;p&gt;DNA methylation studies of incident type 2 diabetes in US populations are limited and to our knowledge none include individuals of African descent. We aimed to fill this gap by identifying methylation sites (CpG sites) and regions likely influencing the development of type 2 diabetes using data from Black and White individuals from the USA.&lt;/p&gt;&lt;h3 data-test=\"abstract-sub-heading\"&gt;Methods&lt;/h3&gt;&lt;p&gt;We prospectively followed 2091 Black and 1029 White individuals without type 2 diabetes from the Atherosclerosis Risk in Communities study over a median follow-up period of 17 years, and performed an epigenome-wide association analysis of blood-based methylation levels with incident type 2 diabetes using Cox regression. We assessed whether significant CpG sites were associated with incident type 2 diabetes independently of BMI or fasting glucose at baseline. We estimated variation in incident type 2 diabetes accounted for by the major non-genetic risk factors and the significant CpG sites. We also examined groups of methylation sites that were differentially methylated. We performed replication of previously discovered CpG sites associated with prevalent and/or incident type 2 diabetes. All analyses were adjusted for batch effects, cell-type proportions and relevant confounders.&lt;/p&gt;&lt;h3 data-test=\"abstract-sub-heading\"&gt;Results&lt;/h3&gt;&lt;p&gt;At an epigenome-wide threshold (10&lt;sup&gt;−7&lt;/sup&gt;), we detected seven novel diabetes-associated CpG sites, of which the sites at &lt;i&gt;MICOS10&lt;/i&gt; (cg05380846: HR 0.89, &lt;i&gt;p&lt;/i&gt;=8.4 × 10&lt;sup&gt;−12&lt;/sup&gt;), &lt;i&gt;ZNF2&lt;/i&gt; (cg01585592: HR 0.88, &lt;i&gt;p&lt;/i&gt;=1.6 × 10&lt;sup&gt;−9&lt;/sup&gt;), &lt;i&gt;JPH3&lt;/i&gt; (cg16696007: HR 0.87, &lt;i&gt;p&lt;/i&gt;=7.8 × 10&lt;sup&gt;−9&lt;/sup&gt;) and &lt;i&gt;GPX6&lt;/i&gt; (cg02793507: HR 0.85, &lt;i&gt;p&lt;/i&gt;=2.7 × 10&lt;sup&gt;−8&lt;/sup&gt;; cg00647063: HR 1.20, &lt;i&gt;p&lt;/i&gt;=2.5 × 10&lt;sup&gt;−8&lt;/sup&gt;) were identified in Black adults; chr17q25 (cg16865890: HR 0.8, &lt;i&gt;p&lt;/i&gt;=6.9 × 10&lt;sup&gt;−8&lt;/sup&gt;) in White adults; and chr11p15 (cg13738793: HR 1.11, &lt;i&gt;p&lt;/i&gt;=7.7 × 10&lt;sup&gt;−8&lt;/sup&gt;) in the meta-analysed group. The &lt;i&gt;JPH3&lt;/i&gt; and &lt;i&gt;GPX6&lt;/i&gt; sites remained epigenome-wide significant on adjustment for BMI, while only the &lt;i&gt;JPH3&lt;/i&gt; site retained significance after adjusting for fasting glucose. We replicated known type 2 diabetes-associated CpG sites, including cg19693031 at &lt;i&gt;TXNIP&lt;/i&gt;, cg00574958 at &lt;i&gt;CPT1A&lt;/i&gt;, cg16567056 at &lt;i&gt;PLCB2&lt;/i&gt;, cg11024682 at &lt;i&gt;SREBF1&lt;/i&gt;, cg08857797 at &lt;i&gt;VPS25&lt;/i&gt; and cg06500161 at &lt;i&gt;ABCG1&lt;/i&gt;, three of which were replicated in Black adults at the epigenome-wide threshold and all of which had directionally consistent effects. We observed a modest increase in type 2 diabetes variance explained by the significantly associated CpG sites over and above traditional type 2 diabetes risk factors and fasting glucose (26.2% vs 30.5% in Black adults; 36.9% vs 39.4% in White adults). At the Šidák-corrected significance threshold of 5%, our differentially methylated region (DMR) analyses revealed severa","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":"14 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143451493","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pregnancy and neonatal outcomes in women with GCK-MODY: an observational study based on standardised insulin modalities","authors":"Cécile Ciangura, Aurélien Seco, Cécile Saint-Martin, Pierre-Yves Ancel, Delphine Bouvet, Sophie Jacqueminet, Agnès Hartemann, Jacques Lepercq, Jacky Nizard, José Timsit, Christine Bellanné-Chantelot","doi":"10.1007/s00125-025-06363-0","DOIUrl":"https://doi.org/10.1007/s00125-025-06363-0","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Aims/hypothesis</h3><p>The management of <i>GCK</i>-MODY during pregnancy remains challenging. We evaluated the impact on pregnancy and neonatal outcomes of two standardised insulin strategies.</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>In this prospective observational study, participants chose (in agreement with their physician) to be treated with insulin either when maternal capillary blood glucose (CBG) ≥ thresholds for gestational diabetes (5.3 mmol/l before or 6.7 mmol/l 2 h after meals) (MG group) or when fetal abdominal circumference ≥75th percentile (FG group). In the FG group, insulin was also initiated if CBG ≥ safety levels (6.7 mmol/l before meals or 11.1 mmol/l 2 h after meals). Data on glycaemic management, modalities and timing of insulin therapy and maternal and neonatal outcomes were recorded.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>In the MG group (<i>n</i>=25), insulin was initiated more frequently (100% vs 75%, <i>p</i>=0.01) and earlier (<i>p</i>=0.001), with lower CBG and more frequent hypoglycaemic episodes compared with the FG group (<i>n</i>=21). However, there were no differences in pregnancy and neonatal outcomes. In the total cohort, the rate of large for gestational age (LGA) neonates, preterm deliveries and Caesarean sections was 22.2%, 2.2% and 40%, respectively. The rate of LGA was 0% among the neonates with the <i>GCK</i> variant vs 36% in those without (<i>p</i>=0.005). There were no associations between LGA and pregnancy characteristics, insulin therapy strategy or glycaemic management.</p><h3 data-test=\"abstract-sub-heading\">Conclusions/interpretation</h3><p>In our study, the rate of LGA primarily depended on the fetal <i>GCK</i> genotype rather than the treatment strategy or glycaemic management. Our results suggest that a standardised strategy based on ultrasound monitoring of fetal growth and glycaemic safety thresholds, leading to delayed insulin initiation, offers a good fetal prognosis and minimises the risk of maternal hypoglycaemia.</p><h3 data-test=\"abstract-sub-heading\">Trial registration</h3><p>ClinTrials.gov NCT02556840.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":"29 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2025-02-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143452342","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Referees 2024.","authors":"","doi":"10.1007/s00125-025-06380-z","DOIUrl":"https://doi.org/10.1007/s00125-025-06380-z","url":null,"abstract":"","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":" ","pages":""},"PeriodicalIF":8.4,"publicationDate":"2025-02-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143439963","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Differential associations of somatic and cognitive-affective symptoms of depression with inflammation and insulin resistance: cross-sectional and longitudinal results from the Emotional Distress Sub-Study of the GRADE study.","authors":"Dominic Ehrmann, Heidi Krause-Steinrauf, Diane Uschner, Hui Wen, Claire J Hoogendoorn, Gladys Crespo-Ramos, Caroline Presley, Valerie L Arends, Robert M Cohen, W Timothy Garvey, Thomas Martens, Holly J Willis, Andrea Cherrington, Jeffrey S Gonzalez","doi":"10.1007/s00125-025-06369-8","DOIUrl":"10.1007/s00125-025-06369-8","url":null,"abstract":"&lt;p&gt;&lt;strong&gt;Aims/hypothesis: &lt;/strong&gt;Insulin resistance and inflammation are components of a biological framework that is hypothesised to be shared by type 2 diabetes and depression. However, depressive symptoms include a large heterogeneity of somatic and cognitive-affective symptoms, and this may obscure the associations within this biological framework. Cross-sectional and longitudinal data were used to disentangle the contributions of insulin resistance and inflammation to somatic and cognitive-affective symptoms of depression.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Methods: &lt;/strong&gt;This secondary analysis used data from the Emotional Distress Sub-Study of the GRADE trial. Insulin resistance and inflammation were assessed using the HOMA-IR estimation and high-sensitivity C-reactive protein (hsCRP) levels, respectively, at baseline and at the study visits at year 1 and year 3 (HOMA-IR) and every 6 months (hsCRP) for up to 3 years of follow-up. Depressive symptoms were assessed at baseline using the Patient Health Questionnaire (PHQ-8), and a total score as well as symptom cluster scores for cognitive-affective and somatic symptoms were calculated. For the cross-sectional analyses, linear regression analyses were performed, with inflammation and insulin resistance at baseline as dependent variables. For the longitudinal analyses, linear mixed-effect regression analyses were performed, with inflammation and insulin resistance at the various time points as dependent variables. In all analyses, depressive symptoms (total score and symptom cluster scores) were the independent variables, controlled for important demographic, anthropometric and metabolic confounders. For the analysis of insulin resistance (HOMA-IR), data from 1321 participants were analysed. For the analysis of inflammation (hsCRP), data from 1739 participants were analysed.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Results: &lt;/strong&gt;In cross-sectional analysis and after adjustment for potential confounders, a one-unit increase in PHQ-8 total score was significantly associated with a 0.8% increase in HOMA-IR (p=0.007), but not with hsCRP (0.6% increase, p=0.283). The somatic symptom score was associated with a 5.8% increase in HOMA-IR (p=0.004). Single-item analyses of depressive symptoms showed that fatigue (3.6% increase, p=0.002) and increased/decreased appetite (3.5% increase, p=0.009) were significantly associated with HOMA-IR cross-sectionally. The cognitive-affective symptom score was not significantly associated with HOMA-IR at baseline. In longitudinal analyses, a one-unit increase in PHQ-8 total score was significantly associated with a 0.8% increase in hsCRP over time (p=0.014), but not with HOMA-IR over time (0.1% decrease, p=0.564). Again, only the somatic symptom cluster was significantly associated with hsCRP over time (5.2% increase, p=0.017), while the cognitive-affective symptom score was not.&lt;/p&gt;&lt;p&gt;&lt;strong&gt;Conclusion/interpretation: &lt;/strong&gt;The results highlight the associations of depressive symptoms with markers ","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":" ","pages":""},"PeriodicalIF":8.4,"publicationDate":"2025-02-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143413654","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Continuous glucose monitor metrics from five studies identify participants at risk for type 1 diabetes development","authors":"Peter Calhoun, Charles Spanbauer, Andrea K. Steck, Brigitte I. Frohnert, Mark A. Herman, Bart Keymeulen, Riitta Veijola, Jorma Toppari, Aster Desouter, Frans Gorus, Mark Atkinson, Darrell M. Wilson, Susan Pietropaolo, Roy W. Beck","doi":"10.1007/s00125-025-06362-1","DOIUrl":"https://doi.org/10.1007/s00125-025-06362-1","url":null,"abstract":"<h3 data-test=\"abstract-sub-heading\">Aims/hypothesis</h3><p>We aimed to assess whether continuous glucose monitor (CGM) metrics can accurately predict stage 3 type 1 diabetes diagnosis in those with islet autoantibodies (AAb).</p><h3 data-test=\"abstract-sub-heading\">Methods</h3><p>Baseline CGM data were collected from participants with ≥1 positive AAb type from five studies: ASK (<i>n</i>=79), BDR (<i>n</i>=22), DAISY (<i>n</i>=18), DIPP (<i>n</i>=8) and TrialNet Pathway to Prevention (<i>n</i>=91). Median follow-up time was 2.6 years (quartiles: 1.5 to 3.6 years). A participant characteristics-only model, a CGM metrics-only model and a full model combining characteristics and CGM metrics were compared.</p><h3 data-test=\"abstract-sub-heading\">Results</h3><p>The full model achieved a numerically higher performance predictor estimate (C statistic=0.74; 95% CI 0.66, 0.81) for predicting stage 3 type 1 diabetes diagnosis compared with the characteristics-only model (C statistic=0.69; 95% CI 0.60, 0.77) and the CGM-only model (C statistic=0.68; 95% CI 0.61, 0.75). Greater percentage of time &gt;7.8 mmol/l (<i>p</i>&lt;0.001), HbA_1c (<i>p</i>=0.02), having a first-degree relative with type 1 diabetes (<i>p</i>=0.02) and testing positive for IA-2 AAb (<i>p</i>&lt;0.001) were associated with greater risk of type 1 diabetes diagnosis. Additionally, being male (<i>p</i>=0.06) and having a negative GAD AAb (<i>p</i>=0.09) were selected but not found to be significant. Participants classified as having low (<i>n</i>=79), medium (<i>n</i>=98) or high (<i>n</i>=41) risk of stage 3 type 1 diabetes diagnosis using the full model had a probability of developing symptomatic disease by 2 years of 5%, 13% and 48%, respectively.</p><h3 data-test=\"abstract-sub-heading\">Conclusions/interpretation</h3><p>CGM metrics can help predict disease progression and classify an individual’s risk of type 1 diabetes diagnosis in conjunction with other factors. CGM can also be used to better assess the risk of type 1 diabetes progression and define eligibility for potential prevention trials.</p><h3 data-test=\"abstract-sub-heading\">Graphical Abstract</h3>\u0000","PeriodicalId":11164,"journal":{"name":"Diabetologia","volume":"58 1","pages":""},"PeriodicalIF":8.2,"publicationDate":"2025-02-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143393334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}