Explore the vast range of titles available.

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.

Background Diversity in the reported prevalence of metabolically healthy obesity (MHO), suggests that modifiable factors may be at play. We evaluated differences in dietary patterns and physical activity between MHO and metabolically unhealthy obesity (MUO). Methods Cross-sectional data of 9270 obese individuals (30–69 years) of the Lifelines Cohort Study was used. MHO was defined as obesity and no metabolic syndrome risk factors and no cardiovascular disease history. MUO was defined as obesity and ≥2 metabolic syndrome risk factors. Sex-specific associations of dietary patterns (identified by principal component analysis) and physical activity with MHO were assessed by multivariable logistic regression (reference group: MUO). Analyses were adjusted for multiple covariates. Results Among 3442 men and 5828 women, 10.2% and 24.4% had MHO and 56.9% and 35.3% MUO, respectively. We generated four obesity-specific dietary patterns. Two were related to MHO, and in women only. In the highest quartile (Q) of ‘bread, potatoes and sweet snacks’ pattern, odds ratio (OR) (95% CI) for MHO was 0.52 (0.39–0.70). For the healthier pattern ‘fruit, vegetables and fish’ , an OR of 1.36 (1.09–1.71) in Q3 and 1.55 (1.21–1.97) in Q4 was found for MHO. For physical activity, there was a positive association between moderate physical activity and vigorous physical activity in the highest tertile and MHO in women and men, respectively (OR 1.19 (1.01–1.41) and OR 2.02 (1.50–2.71)). Conclusion The healthier diet -characterized by ‘fruit, vegetables and fish’ - and moderate physical activity in women, and vigorous physical activity in men may be related to MHO. The (refined) carbohydrate-rich ‘bread, potatoes and sweet snacks’ dietary pattern was found to counteract MHO in women.

PurposeThe ‘Biomarkers of heterogeneity in type 1 diabetes’ study cohort was set up to identify genetic, physiological and psychosocial factors explaining the observed heterogeneity in disease progression and the development of complications in people with long-standing type 1 diabetes (T1D).ParticipantsData and samples were collected in two subsets. A prospective cohort of 611 participants aged ≥16 years with ≥5 years T1D duration from four Dutch Diabetes clinics between 2016 and 2021 (median age 32 years; median diabetes duration 12 years; 59% female; mean glycated haemoglobin (HbA1c) 61 mmol/mol (7.7%); 61% on insulin pump; 23% on continuous glucose monitoring (CGM)). Physical assessments were performed, blood and urine samples were collected, and participants completed questionnaires. A subgroup of participants underwent mixed-meal tolerance tests (MMTTs) at baseline (n=169) and at 1-year follow-up (n=104). Genetic data and linkage to medical and administrative records were also available. A second cross-sectional cohort included participants with ≥35 years of T1D duration (currently n=160; median age 64 years; median diabetes duration 45 years; 45% female; mean HbA1c 58 mmol/mol (7.4%); 51% on insulin pump; 83% on CGM), recruited from five centres and measurements, samples and 5-year retrospective data were collected.Findings to dateStimulated residual C-peptide was detectable in an additional 10% of individuals compared with fasting residual C-peptide secretion. MMTT measurements at 90 min and 120 min showed good concordance with the MMTT total area under the curve. An overall decrease of C-peptide at 1-year follow-up was observed. Fasting residual C-peptide secretion is associated with a decreased risk of impaired awareness of hypoglycaemia.Future plansResearch groups are invited to consider the use of these data and the sample collection. Future work will include additional hormones, beta-cell-directed autoimmunity, specific immune markers, microRNAs, metabolomics and gene expression data, combined with glucometrics, anthropometric and clinical data, and additional markers of residual beta-cell function.Trial registration number NCT04977635.

Background The metabolic syndrome (MetS) comprises several cardiometabolic risk factors associated with increased risk for both type 2 diabetes and cardiovascular disease. Skin autofluorescence (SAF), a non-invasive biomarker of advanced glycation end products accumulation, is associated with cardiovascular complications in subjects with diabetes. The aim of the present study was to examine the association between SAF and the presence of MetS as well as its individual components in a general population. Methods For this cross-sectional analysis, we included 78,671 non-diabetic subjects between 18 and 80 years of age who participated in the LifeLines Cohort Study and had SAF measurement obtained non-invasively using the AGE Reader. MetS was defined according to the revised NCEP ATP III criteria. Students unpaired t test was used to test differences between groups. Both logistic and linear regression analyses were performed in order to test associations between the individual MetS components and SAF. Results Subjects with MetS had higher SAF (2.07 ± 0.45 arbitrary units, AU) compared to individuals without MetS (1.89 ± 0.42 AU) (p < 0.001). There was a positive association between the number of MetS components and higher SAF Z-scores (p < 0.001). Individuals in the highest SAF tertile had a higher presence of MetS (OR 2.61; 95% CI 2.48–2.75) and some of the individual components compared to subjects in the lowest SAF tertile. After correction for age, gender, creatinine clearance, HbA1c and smoking status, only elevated blood pressure and low HDL cholesterol remained significantly associated with higher SAF (p = 0.002 and p = 0.001 respectively). Conclusion Skin autofluorescence was associated with the presence of MetS and some of its individual components. In addition, increasing SAF Z-scores were observed with a higher number of MetS components. Prospective studies are needed to establish whether SAF can be used as an (additional) screening tool to predict both cardiovascular disease and type 2 diabetes in high-risk populations.

Background The metabolic syndrome (MetS) is a combination of unfavourable health factors which includes abdominal obesity, dyslipidaemia, elevated blood pressure and impaired fasting glucose. Earlier studies have reported a relationship between thyroid function and some MetS components or suggested that serum free thyroxine (FT4) or free triiodothyronine (FT3) levels within the normal range were independently associated with insulin resistance. We assessed how thyroid function relates to MetS prevalence in a large population-based study. Methods Data of 26,719 people of western European descent, aged 18–80 years from the Dutch LifeLines Cohort study, all with normal thyroid stimulating hormone (TSH), FT4 and FT3 levels (electrochemiluminescent immunoassay, Roche Modular E170 Analyzer), were available. MetS was defined with the revised National Cholesterol Education Programs Adults Treatment Panel III (NCEP ATP III) criteria. We calculated prevalence of all MetS components according to TSH, FT4 and FT3 quartiles. Results At similar TSH levels and age (mean 45 yrs), men had significantly higher levels of FT4, FT3, blood pressure (BP), heart rate, total and LDL-cholesterol, triglycerides (TG), and creatinine, but lower HDL-cholesterol compared to women (all p  < 0.001). In total, 11.8% of women and 20.7% of men had MetS. In men, lower FT4 levels were associated with higher prevalence of MetS and all MetS components. In women, lower FT4 quartile was only associated with a higher prevalence of elevated TG, waist circumference, and MetS. However, when corrected for confounding factors like age, BMI, current smoking and alcohol consumption, a significant relationship was found between FT3 and three MetS components in men, and all five components in women. Moreover, the highest quartiles of FT3 and the FT3FT4 ratio predicted a 49% and 67% higher prevalence of MetS in men, and a 62 and 80% higher prevalence in women. Conclusions When corrected for possible confounding factors, higher plasma levels of FT3 are associated with several components of the MetS. Only in men, lower FT4 is related to MetS. In the highest FT3 and FT3FT4 quartiles, there is a 50–80% increased risk of having MetS compared to the lowest quartile. Further studies are needed to assess the possible causality of this relationship.

We aimed to assess the association of SAF with cardiovascular mortality in the general population and the possible association between SAF with other disease-specific mortality rates. We evaluated 77,143 participants without known diabetes or cardiovascular disease. The cause of death was ascertained by the municipality database. The associations between SAF and all-cause mortality, cardiovascular mortality and cancer mortality were assessed with Cox proportional hazard analysis.After a median follow-up of 115 months, 1447 participants were deceased (1.9%). SAF and age-adjusted SAF-z score were higher in all mortality groups. Cox regression analysis revealed that the highest quartile of SAF was associated with increased odds of cardiovascular mortality, (HR) 12.6 (7.3–21.7) and after adjusting for age (HR 1.8 (1.0–3.2)). Significance was lost after additional adjustments for sex, smoking status, and BMI (HR 1.4 (0.8–2.5). For cancer-related mortality the highest quartile of SAF was associated with higher probability of mortality in all models (unadjusted HR 8.6 (6.6–11.3), adjusted for age HR 2.1 (1.6–2.8)), adjusted for age, sex, smoking status, and BMI HR 1.7 (1.3–2.4)). SAF is associated with all-cause mortality as well as cardiovascular and cancer-related mortality in the general population.

John Chambers and colleagues report a genome-wide association study for markers of liver function. They identify 42 loci associated with concentrations of one or more liver enzymes in plasma, and use a range of functional genomic analyses to suggest candidate genes at these loci. Concentrations of liver enzymes in plasma are widely used as indicators of liver disease. We carried out a genome-wide association study in 61,089 individuals, identifying 42 loci associated with concentrations of liver enzymes in plasma, of which 32 are new associations ( P = 10 −8 to P = 10 −190 ). We used functional genomic approaches including metabonomic profiling and gene expression analyses to identify probable candidate genes at these regions. We identified 69 candidate genes, including genes involved in biliary transport ( ATP8B1 and ABCB11 ), glucose, carbohydrate and lipid metabolism ( FADS1 , FADS2 , GCKR , JMJD1C , HNF1A , MLXIPL , PNPLA3 , PPP1R3B , SLC2A2 and TRIB1 ), glycoprotein biosynthesis and cell surface glycobiology ( ABO , ASGR1 , FUT2 , GPLD1 and ST3GAL4 ), inflammation and immunity ( CD276 , CDH6 , GCKR , HNF1A , HPR , ITGA1 , RORA and STAT4 ) and glutathione metabolism ( GSTT1 , GSTT2 and GGT ), as well as several genes of uncertain or unknown function (including ABHD12 , EFHD1 , EFNA1 , EPHA2 , MICAL3 and ZNF827 ). Our results provide new insight into genetic mechanisms and pathways influencing markers of liver function.

Background: A substantial fraction of familial colorectal cancer (CRC) and polyposis heritability remains unexplained. This study aimed to identify predisposing loci in patients with these disorders. Methods: Homozygosity mapping was performed using 222 563 SNPs in 302 index patients with various colorectal neoplasms and 3367 controls. Linkage analysis, exome and whole-genome sequencing were performed in a family affected by microsatellite stable CRCs. Candidate variants were genotyped in 10 554 cases and 21 480 controls. Gene expression was assessed at the mRNA and protein level. Results: Homozygosity mapping revealed a disease-associated region at 1q32.3 which was part of the linkage region 1q32.2–42.2 identified in the CRC family. This includes a region previously associated with risk of CRC. Sequencing identified the p.Asp1432Glu variant in the MIA3 gene (known as TANGO1 or TANGO ) and 472 additional rare, shared variants within the linkage region. In both cases and controls the population frequency was 0.02% for this MIA3 variant. The MIA3 mutant allele showed predominant mRNA expression in normal, cancer and precancerous tissues. Furthermore, immunohistochemistry revealed increased expression of MIA3 in adenomatous tissues. Conclusions: Taken together, our two independent strategies associate genetic variations in chromosome 1q loci and predisposition to familial CRC and polyps, which warrants further investigation.

Thyroid hormone plays a pivotal role in human metabolism. In epidemiologic studies, adequate registration of thyroid disorders is warranted. We examined the prevalence of thyroid disorders, reported thyroid medication use, thyroid hormone levels, and validity of thyroid data obtained from questionnaires in the Lifelines Cohort Study. We evaluated baseline data of all 152180 subjects (aged 18-93 years) of the Lifelines Cohort Study. At baseline, participants were asked about previous thyroid surgery and current and previous thyroid hormone use. At follow-up (n = 136776, after median 43 months), incident thyroid disorders could be reported in an open, non-structured question. Data on baseline thyroid hormone measurements (TSH, FT4 and FT3) were available in a subset of 39935 participants. Of the 152180 participants, mean (±SD) age was 44.6±13.1 years and 58.5% were female. Thyroid medication was used by 4790 participants (3.1%); the majority (98.2%) used levothyroxine, and 88% were females. 59.3% of levothyroxine users had normal TSH levels. The prevalence of abnormal TSH levels in those not using thyroid medication was 10.8%; 9.4% had a mildly elevated (4.01-10.0 mIU/L), 0.7% had suppressed (<0.40 mIU/L), while 0.7% had elevated (>10.0 mIU/L) TSH levels. Over 98% of subjects with TSH between 4 and 10 mIU/L had normal FT4. Open text questions allowing to report previous thyroid surgery and incident thyroid disorders proved not to be reliable and severely underestimated the true incidence and prevalence of thyroid disorders. Undetected thyroid disorders were prevalent in the general population, whereas the prevalence of thyroid medication use was 3.1%. Less than 60% of individuals using levothyroxine had a normal TSH level. The large group of individuals with subclinical hypothyroidism (9.4%) offers an excellent possibility to prospectively follow the natural course of this disorder. Both structured questions as well as linking to G.P.'s and pharmacists' data are necessary to improve the completeness and reliability of Lifelines' data on thyroid disorders.

Increased skin autofluorescence (SAF) predicts the development of diabetes-related complications and cardiovascular disease. We assessed the performance of a simple model which includes SAF to identify individuals at high risk for undiagnosed and incident type 2 diabetes, in 58,377 participants in the Lifelines Cohort Study without known diabetes. Newly-diagnosed diabetes was defined as fasting blood glucose ≥ 7.0 mmol/l and/or HbA 1c  ≥ 6.5% (≥ 48 mmol/mol) or self-reported diabetes at follow-up. We constructed predictive models based on age, body mass index (BMI), SAF, and parental history of diabetes, and compared to results with the concise FINDRISC model. At 2nd visit to Lifelines, 1113 (1.9%) participants were identified with undiagnosed diabetes and 1033 (1.8%) participants developed diabetes during follow-up. A model comprising age, BMI and SAF yielded an AUC of 0.783 and was non-inferior to the concise FINDRISC model, which had an AUC of 0.797 to predict new diabetes. At a score of 5.8, sensitivity was 78% and specificity of 66%. Model 2 which also incorporated parental diabetes history, had an AUC of 0.792, and a sensitivity of 74% and specificity of 70% at a score of 6.5. Net reclassification index (NRI) did not improve significantly (NRI 1.43% (− 0.50–3.37 p = 0.15). The combination of an easy to perform SAF measurement with age and BMI is a good alternative screening tool suitable for medical and non-medical settings. Parental history of diabetes did not significantly improve model performance in this homogeneous cohort.