Aims: To select a core list of standard outcomes for diabetes to be routinely applied internationally, including patient‐reported outcomes.Methods: We conducted a structured systematic review of outcome measures, focusing on adults with either type 1 or type 2 diabetes. This process was followed by a consensus‐driven modified Delphi panel, including a multidisciplinary group of academics, health professionals and people with diabetes. External feedback to validate the set of outcome measures was sought from people with diabetes and health professionals.Results: The panel identified an essential set of clinical outcomes related to diabetes control, acute events, chronic complications, health service utilisation, and survival that can be measured using routine administrative data and/or clinical records. Three instruments were recommended for annual measurement of patient‐reported outcome measures: the WHO Well‐Being Index for psychological well‐being; the depression module of the Patient Health Questionnaire for depression; and the Problem Areas in Diabetes scale for diabetes distress. A range of factors related to demographic, diagnostic profile, lifestyle, social support and treatment of diabetes were also identified for case‐mix adjustment.Conclusions: We recommend the standard set identified in this study for use in routine practice to monitor, benchmark and improve diabetes care. The inclusion of patient‐reported outcomes enables people living with diabetes to report directly on their condition in a structured way.

OBJECTIVE To investigate the role of epigenetics in statins’ diabetogenic effect comparing DNA methylation (DNAm) between statin users and nonusers in an epigenome-wide association study in blood. RESEARCH DESIGN AND METHODS Five cohort studies’ participants (n = 8,270) were classified as statin users when they were on statin therapy at the time of DNAm assessment with Illumina 450K or EPIC array or noncurrent users otherwise. Associations of DNAm with various outcomes like incident type 2 diabetes, plasma glucose, insulin, and insulin resistance (HOMA of insulin resistance [HOMA-IR]) as well as with gene expression were investigated. RESULTS Discovery (n = 6,820) and replication (n = 1,450) phases associated five DNAm sites with statin use: cg17901584 (1.12 × 10⁻²⁵ [DHCR24]), cg10177197 (3.94 × 10⁻⁰⁸ [DHCR24]), cg06500161 (2.67 × 10⁻²³ [ABCG1]), cg27243685 (6.01 × 10⁻⁰⁹ [ABCG1]), and cg05119988 (7.26 × 10⁻¹² [SC4MOL]). Two sites were associated with at least one glycemic trait or type 2 diabetes. Higher cg06500161 methylation was associated with higher fasting glucose, insulin, HOMA-IR, and type 2 diabetes (odds ratio 1.34 [95% CI 1.22, 1.47]). Mediation analyses suggested that ABCG1 methylation partially mediates the effect of statins on high insulin and HOMA-IR. Gene expression analyses showed that statin exposure and ABCG1 methylation were associated with ABCG1 downregulation, suggesting epigenetic regulation of ABCG1 expression. Further, outcomes insulin and HOMA-IR were significantly associated with ABCG1 expression. CONCLUSIONS This study sheds light on potential mechanisms linking statins with type 2 diabetes risk, providing evidence on DNAm partially mediating statins’ effects on insulin traits. Further efforts shall disentangle the molecular mechanisms through which statins may induce DNAm changes, potentially leading to ABCG1 epigenetic regulation.

Nonalcoholic fatty liver disease (NAFLD) is a risk factor for type 2 diabetes (T2D). We aimed to identify the peripheral blood DNA methylation signature of hepatic fat. We conducted epigenome-wide association studies of hepatic fat in 3,400 European ancestry (EA) participants and in 401 Hispanic ancestry and 724 African ancestry participants from four population-based cohort studies. Hepatic fat was measured using computed tomography or ultrasound imaging and DNA methylation was assessed at >400,000 cytosine-guanine dinucleotides (CpGs) in whole blood or CD14+ monocytes using a commercial array. We identified 22 CpGs associated with hepatic fat in EA participants at a false discovery rate <0.05 (corresponding P = 6.9 × 10−6) with replication at Bonferroni-corrected P < 8.6 × 10−4. Mendelian randomization analyses supported the association of hypomethylation of cg08309687 (LINC00649) with NAFLD (P = 2.5 × 10−4). Hypomethylation of the same CpG was also associated with risk for new-onset T2D (P = 0.005). Our study demonstrates that a peripheral blood–derived DNA methylation signature is robustly associated with hepatic fat accumulation. The hepatic fat–associated CpGs may represent attractive biomarkers for T2D. Future studies are warranted to explore mechanisms and to examine DNA methylation signatures of NAFLD across racial/ethnic groups.

Early and precise identification of individuals with prediabetes and type 2 diabetes (T2D) at risk for progressing to chronic kidney disease (CKD) is essential to prevent complications of diabetes. Here, we identify and evaluate prospective metabolite biomarkers and the best set of predictors of CKD in the longitudinal, population-based Cooperative Health Research in the Region of Augsburg (KORA) cohort by targeted metabolomics and machine learning approaches. Out of 125 targeted metabolites, sphingomyelin C18:1 and phosphatidylcholine diacyl C38:0 were identified as candidate metabolite biomarkers of incident CKD specifically in hyperglycemic individuals followed during 6.5 years. Sets of predictors for incident CKD developed from 125 metabolites and 14 clinical variables showed highly stable performances in all three machine learning approaches and outperformed the currently established clinical algorithm for CKD. The two metabolites in combination with five clinical variables were identified as the best set of predictors, and their predictive performance yielded a mean area value under the receiver operating characteristic curve of 0.857. The inclusion of metabolite variables in the clinical prediction of future CKD may thus improve the risk prediction in people with prediabetes and T2D. The metabolite link with hyperglycemia-related early kidney dysfunction warrants further investigation.

Understanding normal aging of kidney function is pivotal to help distinguish individuals at particular risk for chronic kidney disease. Glomerular filtration rate (GFR) is typically estimated via serum creatinine (eGFRcrea) or cystatin C (eGFRcys). Since population-based age-group-specific reference values for eGFR and eGFR-decline are scarce, we aimed to provide such reference values from population-based data of a wide age range. In four German population-based cohorts (KORA-3, KORA-4, AugUR, DIACORE), participants underwent medical exams, interview, and blood draw up to five times within up to 25 years. We analyzed eGFRcrea and eGFRcys cross-sectionally and longitudinally (12,000 individuals, age 25-95 years). Cross-sectionally, we found age-group-specific eGFRcrea to decrease approximately linearly across the full age range, for eGFRcys up to the age of 60 years. Within age-groups, there was little difference by sex or diabetes status. Longitudinally, linear mixed models estimated an annual eGFRcrea decline of -0.80 [95% confidence interval -0.82, -0.77], -0.79 [-0.83, -0.76], and -1.20 mL/min/1.73m² [-1.33, -1.08] for the general population, "healthy" individuals, or individuals with diabetes, respectively. Reference values for eGFR using cross-sectional data were shown as percentile curves for "healthy" individuals and for individuals with diabetes. Reference values for eGFR-decline using longitudinal data were presented as 95% prediction intervals for "healthy" individuals and for individuals with diabetes, obesity, and/or albuminuria. Thus, our results can help clinicians to judge eGFR values in individuals seen in clinical practice according to their age and to understand the expected range of annual eGFR-decline based on their risk profile.

Background: Prior studies have reported inconsistent results or less well-explored associations between sex hormones and non-alcoholic fatty liver disease (NAFLD). Here, we aimed to investigate the associations of NAFLD with sex steroids and sex hormone-binding globulin (SHBG) in the population-based study and conduct a comprehensive systematic review and meta-analysis of all published observational studies. Methods: Analyses included 755 men and 1109 women with available data on sex steroids, SHBG, and ultrasound-based NAFLD from the Rotterdam Study. Multivariable regression models were used to examine the associations. Additionally, we searched five databases from inception to 1 April 2022 and performed a systematic review and meta-analysis. Random-effects (DerSimonian-Laird) method was used for meta-analysis, odds ratios (ORs) were calculated for the effect estimate, subgroup and leave-one-out sensitivity analyses were conducted, and meta-regression was performed to explore the pooled statistics with high heterogeneity. Results: In the Rotterdam Study, lower levels of SHBG were associated with NAFLD in both sexes, while lower testosterone was associated with NAFLD only among women. Similarly, the meta-analysis of 16 studies indicated no sex-specific association between SHBG and NAFLD (men: OR = 0.37, 95%CI 0.21–0.53; women: OR = 0.40, 95%CI 0.21–0.60), yet there was a sex-specific association between testosterone and NAFLD (men: OR = 0.59, 95%CI 0.42–0.76; women: OR = 1.06, 95%CI 0.68–1.44). Moreover, men with NAFLD had lower estradiol levels than those without NAFLD. Conclusions: Lower SHBG levels were associated with NAFLD in both sexes, but testosterone levels were associated in a sex-specific manner. In addition, our results showed estradiol with the potential as a protective factor for NAFLD in healthy men.