Skin autofluorescence improves the Finnish Diabetes Risk Score in the detection of diabetes in a large population-based cohort: The LifeLines Cohort Study

Fokkens, Bernardina T.; Waateringe, Robert P. van; Mulder, Douwe J.; Wolffenbuttel, Bruce H. R.; Smit, Andries J.

doi:10.1016/j.diabet.2017.09.002

Cited by 19 publications

(20 citation statements)

References 39 publications

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“…Analyses in a subgroup of individuals, classified a priori as intermediate risk, showed that the SAF-based decision model had a higher sensitivity and specificity compared with fasting plasma glucose alone and the FINDRISC questionnaire, and had a performance equal to HbA 1c . Finally, our group recently demonstrated in the same Lifelines cohort that measurement of SAF is of additional value to the FINDRISC for detecting current undiagnosed diabetes [36]. Reclassification analysis showed that SAF reclassified 8–15% of the total population into more accurate risk categories.…”

Section: Discussionmentioning

confidence: 99%

Skin autofluorescence predicts incident type 2 diabetes, cardiovascular disease and mortality in the general population

et al. 2018

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Aims/hypothesisEarlier studies have shown that skin autofluorescence measured with an AGE reader estimates the accumulation of AGEs in the skin, which increases with ageing and is associated with the metabolic syndrome and type 2 diabetes. In the present study, we examined whether the measurement of skin autofluorescence can predict 4 year risk of incident type 2 diabetes, cardiovascular disease (CVD) and mortality in the general population.MethodsFor this prospective analysis, we included 72,880 participants of the Dutch Lifelines Cohort Study, who underwent baseline investigations between 2007 and 2013, had validated baseline skin autofluorescence values available and were not known to have diabetes or CVD. Individuals were diagnosed with incident type 2 diabetes by self-report or by a fasting blood glucose ≥7.0 mmol/l or HbA1c ≥48 mmol/mol (≥6.5%) at follow-up. Participants were diagnosed as having incident CVD (myocardial infarction, coronary interventions, cerebrovascular accident, transient ischaemic attack, intermittent claudication or vascular surgery) by self-report. Mortality was ascertained using the Municipal Personal Records Database.ResultsAfter a median follow-up of 4 years (range 0.5–10 years), 1056 participants (1.4%) had developed type 2 diabetes, 1258 individuals (1.7%) were diagnosed with CVD, while 928 (1.3%) had died. Baseline skin autofluorescence was elevated in participants with incident type 2 diabetes and/or CVD and in those who had died (all p < 0.001), compared with individuals who survived and remained free of the two diseases. Skin autofluorescence predicted the development of type 2 diabetes, CVD and mortality, independent of several traditional risk factors, such as the metabolic syndrome, glucose and HbA1c.Conclusions/interpretationThe non-invasive skin autofluorescence measurement is of clinical value for screening for future risk of type 2 diabetes, CVD and mortality, independent of glycaemic measures and the metabolic syndrome.Electronic supplementary materialThe online version of this article (10.1007/s00125-018-4769-x) contains peer-reviewed but unedited supplementary material, which is available to authorised users.

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Section: Discussionmentioning

confidence: 99%

Skin autofluorescence predicts incident type 2 diabetes, cardiovascular disease and mortality in the general population

et al. 2018

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“…Type 2 diabetes can be prevented in high‐risk subjects by lifestyle intervention 20 thus providing strong arguments for screening risk subjects 28 . In our clinical everyday life, traditional risk factors, such as the Finnish Diabetes Risk Score (FINDRISC), 29 are commonly assessed to predict future type 2 diabetes risk and several attempts have been done to improve FINDRISC further 30 . Our data shows that both lower ISI and lower CIR were associated with a higher risk for type 2 diabetes independent of the other traditional risk factors used in FINDRISC.…”

Section: Discussionmentioning

confidence: 81%

Insulin action and secretion independent of traditional risk factors predict new‐onset type 2 diabetes in Iraqi and Swedish born citizens – The MEDIM cohort study

Pikkemaat

Lönn

Bennet

2021

Diabetes Metabolism Res

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Aims Our aim was to study the incidence of type 2 diabetes in a population‐based cohort of Swedish and Iraqi born individuals, focussing on traditional risk factors, insulin action, insulin secretion and ethnicity. Materials and Methods The cohort consisted of 1164 Iraqi and 693 Swedish‐born citizens. We investigated the association between new‐onset type 2 diabetes and the predictors including lifestyle factors, metabolic risk markers, country of birth, insulin sensitivity and secretion assessed by Matsuda index with Cox regression. Results Eighty‐nine individuals were diagnosed with type 2 diabetes with a mean follow‐up of 7.5 years. Both lower insulin sensitivity (ISI, HR 0.02 [0.01–0.08]) as well as insulin secretion (CIR, HR 0.13 [0.07–0.24]) at baseline predicted type 2 diabetes onset, independent of traditional risk factors. Our results were not modified by country of birth. Regarding traditional risk factors, WHR (1.05 [1.00–1.09]), blood glucose (3.27 [2.35–4.55]), LDL/HDL (1.46 [1.20–1.78]) and diastolic blood pressure (1.04 [1.00–1.07]) predicted diabetes incidence in the full model. Conclusions Both impaired insulin sensitivity index and corrected insulin response predicted type 2 diabetes onset, independent of traditional risk factors. We conclude that insulin secretion and action might be useful additional predictors for type 2 diabetes in populations of European and Middle Eastern ethnicities.

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“…AGEs can predict the severity of complications in diabetes [40]. The inclusion of skin autofluorescence in the Finnish Diabetes Risk Score improved the ability to detect undiagnosed diabetes and reclassify people in the intermediate risk category [41].…”

Section: Metabolic Healthmentioning

confidence: 99%

A Biological Age Model Designed for Health Promotion Interventions: Protocol for an Interdisciplinary Study for Model Development

Husted¹,

Fogelstrøm²,

Hulst³

et al. 2020

JMIR Res Protoc

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Background Actions to improve healthy aging and delay morbidity are crucial, given the global aging population. We believe that biological age estimation can help promote the health of the general population. Biological age reflects the heterogeneity in functional status and vulnerability to disease that chronological age cannot. Thus, biological age assessment is a tool that provides an intuitively meaningful outcome for the general population, and as such, facilitates our understanding of the extent to which lifestyle can increase health span. Objective This interdisciplinary study intends to develop a biological age model and explore its usefulness. Methods The model development comprised three consecutive phases: (1) conducting a cross-sectional study to gather candidate biomarkers from 100 individuals representing normal healthy aging people (the derivation cohort); (2) estimating the biological age using principal component analysis; and (3) testing the clinical use of the model in a validation cohort of overweight adults attending a lifestyle intervention course. Results We completed the data collection and analysis of the cross-sectional study, and the initial results of the principal component analysis are ready. Interpretation and refinement of the model is ongoing. Recruitment to the validation cohort is forthcoming. We expect the results to be published by December 2021. Conclusions We expect the biological age model to be a useful indicator of disease risk and metabolic risk, and further research should focus on validating the model on a larger scale. Trial Registration ClinicalTrials.gov NCT03680768, https://clinicaltrials.gov/ct2/show/NCT03680768 (Phase 1 study); NCT04279366 https://clinicaltrials.gov/ct2/show/NCT04279366 (Phase 3 study). International Registered Report Identifier (IRRID) DERR1-10.2196/19209

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Skin autofluorescence improves the Finnish Diabetes Risk Score in the detection of diabetes in a large population-based cohort: The LifeLines Cohort Study

Cited by 19 publications

References 39 publications

Skin autofluorescence predicts incident type 2 diabetes, cardiovascular disease and mortality in the general population

Skin autofluorescence predicts incident type 2 diabetes, cardiovascular disease and mortality in the general population

Insulin action and secretion independent of traditional risk factors predict new‐onset type 2 diabetes in Iraqi and Swedish born citizens – The MEDIM cohort study

A Biological Age Model Designed for Health Promotion Interventions: Protocol for an Interdisciplinary Study for Model Development

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