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Little is known about the timing of changes in glucose metabolism before occurrence of type 2 diabetes. We aimed to characterise trajectories of fasting and postload glucose, insulin sensitivity, and insulin secretion in individuals who develop type 2 diabetes. We analysed data from our prospective occupational cohort study (Whitehall II study) of 6538 (71% male and 91% white) British civil servants without diabetes mellitus at baseline. During a median follow-up period of 9·7 years, 505 diabetes cases were diagnosed (49·1% on the basis of oral glucose tolerance test). We assessed retrospective trajectories of fasting and 2-h postload glucose, homoeostasis model assessment (HOMA) insulin sensitivity, and HOMA β-cell function from up to 13 years before diabetes diagnosis (diabetic group) or at the end of follow-up (non-diabetics). Multilevel models adjusted for age, sex, and ethnic origin confirmed that all metabolic measures followed linear trends in the group of non-diabetics (10 989 measurements), except for insulin secretion that did not change during follow-up. In the diabetic group (801 measurements), a linear increase in fasting glucose was followed by a steep quadratic increase (from 5·79 mmol/L to 7·40 mmol/L) starting 3 years before diagnosis of diabetes. 2-h postload glucose showed a rapid increase starting 3 years before diagnosis (from 7·60 mmol/L to 11·90 mmol/L), and HOMA insulin sensitivity decreased steeply during the 5 years before diagnosis (to 86·7%). HOMA β-cell function increased between years 4 and 3 before diagnosis (from 85·0% to 92·6%) and then decreased until diagnosis (to 62·4%). In this study, we show changes in glucose concentrations, insulin sensitivity, and insulin secretion as much as 3–6 years before diagnosis of diabetes. The description of biomarker trajectories leading to diabetes diagnosis could contribute to more-accurate risk prediction models that use repeated measures available for patients through regular check-ups. Medical Research Council (UK); Economic and Social Research Council (UK); British Heart Foundation (UK); Health and Safety Executive (UK); Department of Health (UK); National Institute of Health (USA); Agency for Health Care Policy Research (USA); the John D and Catherine T MacArthur Foundation (USA); and Academy of Finland (Finland).

Aims/hypothesis Fasting plasma levels of branched-chain amino acids (BCAAs) are associated with insulin resistance, but it remains unclear whether there is a causal relation between the two. We aimed to disentangle the causal relations by performing a Mendelian randomisation study using genetic variants associated with circulating BCAA levels and insulin resistance as instrumental variables. Methods We measured circulating BCAA levels in blood plasma by NMR spectroscopy in 1,321 individuals from the ADDITION-PRO cohort. We complemented our analyses by using previously published genome-wide association study (GWAS) results from the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) ( n  = 46,186) and from a GWAS of serum BCAA levels ( n  = 24,925). We used a genetic risk score (GRS), calculated using ten established fasting serum insulin associated variants, as an instrumental variable for insulin resistance. A GRS of three variants increasing circulating BCAA levels was used as an instrumental variable for circulating BCAA levels. Results Fasting plasma BCAA levels were associated with higher HOMA-IR in ADDITION-PRO (β 0.137 [95% CI 0.08, 0.19] p  = 6 × 10 −7 ). However, the GRS for circulating BCAA levels was not associated with fasting insulin levels or HOMA-IR in ADDITION-PRO (β −0.011 [95% CI −0.053, 0.032] p  = 0.6 and β −0.011 [95% CI −0.054, 0.031] p  = 0.6, respectively) or in GWAS results for HOMA-IR from MAGIC (β for valine-increasing GRS −0.012 [95% CI −0.069, 0.045] p  = 0.7). By contrast, the insulin-resistance-increasing GRS was significantly associated with increased BCAA levels in ADDITION-PRO (β 0.027 [95% CI 0.005, 0.048] p  = 0.01) and in GWAS results for serum BCAA levels (β 1.22 [95% CI 0.71, 1.73] p  = 4 × 10 −6 , β 0.96 [95% CI 0.45, 1.47] p  = 3 × 10 −4 , and β 0.67 [95% CI 0.16, 1.18] p  = 0.01 for isoleucine, leucine and valine levels, respectively) and instrumental variable analyses in ADDITION-PRO indicated that HOMA-IR is causally related to higher circulating fasting BCAA levels (β 0.73 [95% CI 0.26, 1.19] p  = 0.002). Conclusions/interpretation Our results suggest that higher BCAA levels do not have a causal effect on insulin resistance while increased insulin resistance drives higher circulating fasting BCAA levels.

Frail elderly people experience elevated mortality. However, no consensus exists on the definition of frailty, and many frailty scores have been developed. The main aim of this study was to compare the association between 35 frailty scores and incident cardiovascular disease (CVD), incident cancer, and all-cause mortality. Also, we aimed to assess whether frailty scores added predictive value to basic and adjusted models for these outcomes. Through a structured literature search, we identified 35 frailty scores that could be calculated at wave 2 of the English Longitudinal Study of Ageing (ELSA), an observational cohort study. We analysed data from 5,294 participants, 44.9% men, aged 60 years and over. We studied the association between each of the scores and the incidence of CVD, cancer, and all-cause mortality during a 7-year follow-up using Cox proportional hazard models at progressive levels of adjustment. We also examined the added predictive performance of each score on top of basic models using Harrell's C statistic. Using age of the participant as a timescale, in sex-adjusted models, hazard ratios (HRs) (95% confidence intervals) for all-cause mortality ranged from 2.4 (95% CI: 1.7-3.3) to 26.2 (95% CI: 15.4-44.5). In further adjusted models including smoking status and alcohol consumption, HR ranged from 2.3 (95% CI: 1.6-3.1) to 20.2 (95% CI: 11.8-34.5). In fully adjusted models including lifestyle and comorbidity, HR ranged from 0.9 (95% CI: 0.5-1.7) to 8.4 (95% CI: 4.9-14.4). HRs for CVD and cancer incidence in sex-adjusted models ranged from 1.2 (95% CI: 0.5-3.2) to 16.5 (95% CI: 7.8-35.0) and from 0.7 (95% CI: 0.4-1.2) to 2.4 (95% CI: 1.0-5.7), respectively. In sex- and age-adjusted models, all frailty scores showed significant added predictive performance for all-cause mortality, increasing the C statistic by up to 3%. None of the scores significantly improved basic prediction models for CVD or cancer. A source of bias could be the differences in mortality follow-up time compared to CVD/cancer, because the existence of informative censoring cannot be excluded. There is high variability in the strength of the association between frailty scores and 7-year all-cause mortality, incident CVD, and cancer. With regard to all-cause mortality, some scores give a modest improvement to the predictive ability. Our results show that certain scores clearly outperform others with regard to three important health outcomes in later life. Finally, we think that despite their limitations, the use of frailty scores to identify the elderly population at risk is still a useful measure, and the choice of a frailty score should balance feasibility with performance.

The microbial communities of the oral cavity are important elements of oral and systemic health. With emerging evidence highlighting the heritability of oral bacterial microbiota, this study aimed to identify host genome variants that influence oral microbial traits. Using data from 16S rRNA gene amplicon sequencing, we performed genome-wide association studies with univariate and multivariate traits of the salivary microbiota from 610 unrelated adults from the Danish ADDITION-PRO cohort. We identified six single nucleotide polymorphisms (SNPs) in human genomes that showed associations with abundance of bacterial taxa at different taxonomical tiers ( P  < 5 × 10 –8 ). Notably, SNP rs17793860 surpassed our study-wide significance threshold ( P  < 1.19 × 10 –9 ). Additionally, rs4530093 was linked to bacterial beta diversity ( P  < 5 × 10 –8 ). Out of these seven SNPs identified, six exerted effects on metabolic traits, including glycated hemoglobin A1c, triglyceride and high-density lipoprotein cholesterol levels, the risk of type 2 diabetes and stroke. Our findings highlight the impact of specific host SNPs on the composition and diversity of the oral bacterial community. Importantly, our results indicate an intricate interplay between host genetics, the oral microbiota, and metabolic health. We emphasize the need for integrative approaches considering genetic, microbial, and metabolic factors.

Aims/hypothesisThe role of burden and duration of multiple microvascular complications on mortality rate has not been explored in detail in type 1 diabetes. Taking complication burden and time-updated duration into account we aimed to quantify mortality rate in individuals with and without microvascular complications.MethodsThis observational clinical cohort included 3828 individuals with type 1 diabetes attending the Steno Diabetes Center Copenhagen in 2001–2013. We used information on mortality and detailed clinical measures of microvascular complications from electronic patient records. Poisson models were used to model mortality rates according to complication burden.ResultsDuring 26,665 person-years of follow-up, 503 deaths occurred. Compared with individuals without microvascular complications, the mortality rate ratio was 2.20 (95% CI 1.79, 2.69) for individuals with diabetic kidney disease, 1.72 (95% CI 1.39, 2.12) for individuals with neuropathy and 1.02 (95% CI 0.77, 1.37) for individuals with retinopathy, all adjusted for calendar time (year/month/day), age, duration of diabetes, sex, HbA1c, LDL-cholesterol, BMI, smoking status, systolic blood pressure, use of antihypertensive and lipid-lowering medication, and cardiovascular disease status. In individuals with two complications or more, the risk of mortality did not exceed the combined risk from each individual complication. Mortality rate ratios increased immediately after diagnosis of neuropathy and diabetic kidney disease. Mortality rate ratios were independent of the duration of neuropathy and retinopathy, while the mortality rate associated with diabetic kidney disease reached a stable level after approximately 3 years.Conclusions/interpretationNeuropathy and diabetic kidney disease are strong and independent risk markers of mortality in type 1 diabetes, whereas no evidence of higher mortality rate was found for retinopathy. We found no indication that the mortality risk with multiple complications exceeds the risk conferred by each complication separately. The duration spent with microvascular complications had only a marginal effect on mortality.

Aims/hypothesisThe secretion of glucagon is controlled by blood glucose and inappropriate secretion of glucagon contributes to hyperglycaemia in diabetes. Besides its role in glucose regulation, glucagon regulates amino acid metabolism in hepatocytes by increasing ureagenesis. Disruption of this mechanism causes hyperaminoacidaemia, which in turn increases glucagon secretion. We hypothesised that hepatic insulin resistance (secondary to hepatic steatosis) via defective glucagon signalling/glucagon resistance would lead to impaired ureagenesis and, hence, increased plasma concentrations of glucagonotropic amino acids and, subsequently, glucagon.MethodsTo examine the association between glucagon and amino acids, and to explore whether this relationship was modified by hepatic insulin resistance, we studied a well-characterised cohort of 1408 individuals with normal and impaired glucose regulation. In this cohort, we have previously reported insulin resistance to be accompanied by increased plasma concentrations of glucagon. We now measure plasma levels of amino acids in the same cohort. HOMA-IR was calculated as a marker of hepatic insulin resistance.ResultsFasting levels of glucagonotropic amino acids and glucagon were significantly and inversely associated in linear regression models (persisting after adjustment for age, sex and BMI). Increasing levels of hepatic, but not peripheral insulin resistance (p > 0.166) attenuated the association between glucagon and circulating levels of alanine, glutamine and tyrosine, and was significantly associated with hyperaminoacidaemia and hyperglucagonaemia. A doubling of the calculated glucagon–alanine index was significantly associated with a 30% increase in hepatic insulin resistance, a 7% increase in plasma alanine aminotransferase levels, and a 14% increase in plasma γ-glutamyltransferase levels.Conclusions/interpretationThis cross-sectional study supports the existence of a liver–alpha cell axis in humans: glucagon regulates plasma levels of amino acids, which in turn feedback to regulate the secretion of glucagon. With hepatic insulin resistance, reflecting hepatic steatosis, the feedback cycle is disrupted, leading to hyperaminoacidaemia and hyperglucagonaemia. The glucagon–alanine index is suggested as a relevant marker for hepatic glucagon signalling.

Background We aimed to estimate the age-specific and age-standardized incidence rate of diabetes for men and women in Mexico between 2003 and 2015, and to assess the relative change in incidence of diabetes between 2003 and 2015. Methods We use a partial differential equation describing the illness-death model to estimate the incidence rate (IR) of diabetes for the years 2003, 2009 and 2015 based on prevalence data from National Health Surveys conducted in Mexico, the mortality rate of the Mexican general population and plausible input values for age-specific mortality rate ratios associated with diabetes. Results The age-standardized IR of diabetes per 1000 person years (pryr) was similar among men (IRm) and women (IRw) in the year 2003 (IRm 6.1 vs. IRw 6.5 1000/pryr), 2009 (IRm: 7.0 vs. IRw: 8.4 1000/pryr), and in 2015 (IRm 8.0 vs. IRw 10.6 1000/pryr). The highest incident rates were observed among men and women in the 60–69 age group. Conclusions Overall, the incidence rate of diabetes in Mexico between the years 2003 and 2015 remained stable. However, rates were markedly higher among women in the age group 40–49 and 50–59 in the year 2015 compared with rates in 2003.

Introduction: Previous research indicates that the salivary microbiota may be a biomarker of oral as well as systemic disease. However, clarifying the potential bias from general health status and lifestyle-associated factors is a prerequisite of using the salivary microbiota for screening.Materials & Methods: ADDDITION-PRO is a nationwide Danish cohort, nested within the Danish arm of the Anglo-Danish-Dutch Study of Intensive treatment in People with Screen-Detected Diabetes in Primary Care. Saliva samples from n=746 individuals from the ADDITION-PRO cohort were characterized using 16s rRNA sequencing. Alpha- and beta diversity as well as relative abundance of genera was examined in relation to general health and lifestyle-associated variables. Permutational multivariate analysis of variance (PERMANOVA) was performed on individual variables and all variables together. Classification models were created using sparse partial-least squares discriminant analysis (sPLSDA) for variables that showed statistically significant differences based on PERMANOVA analysis (p < 0.05).Results: Glycemic status, hemoglobin-A1c (HbA1c) level, sex, smoking and weekly alcohol intake were found to be significantly associated with salivary microbial composition (individual variables PERMANOVA, p < 0.05). Collectively, these variables were associated with approximately 5.8% of the observed differences in the composition of the salivary microbiota. Smoking status was associated with 3.3% of observed difference, and smoking could be detected with good accuracy based on salivary microbial composition (AUC 0.95, correct classification rate 79.6%).Conclusions: Glycemic status, HbA1c level, sex, smoking and weekly alcohol intake were significantly associated with the composition of the salivary microbiota. Despite smoking only being associated with 3.3% of the difference in overall salivary microbial composition, it was possible to create a model for detection of smoking status with a high correct classification rate. However, the lack of information on the oral health status of participants serves as a limitation in the present study. Further studies in other cohorts are needed to validate the external validity of these findings.

A major question in evolutionary biology is how natural selection has shaped patterns of genetic variation across the human genome. Previous work has documented a reduction in genetic diversity in regions of the genome with low recombination rates. However, it is unclear whether other summaries of genetic variation, like allele frequencies, are also correlated with recombination rate and whether these correlations can be explained solely by negative selection against deleterious mutations or whether positive selection acting on favorable alleles is also required. Here we attempt to address these questions by analyzing three different genome-wide resequencing datasets from European individuals. We document several significant correlations between different genomic features. In particular, we find that average minor allele frequency and diversity are reduced in regions of low recombination and that human diversity, human-chimp divergence, and average minor allele frequency are reduced near genes. Population genetic simulations show that either positive natural selection acting on favorable mutations or negative natural selection acting against deleterious mutations can explain these correlations. However, models with strong positive selection on nonsynonymous mutations and little negative selection predict a stronger negative correlation between neutral diversity and nonsynonymous divergence than observed in the actual data, supporting the importance of negative, rather than positive, selection throughout the genome. Further, we show that the widespread presence of weakly deleterious alleles, rather than a small number of strongly positively selected mutations, is responsible for the correlation between neutral genetic diversity and recombination rate. This work suggests that natural selection has affected multiple aspects of linked neutral variation throughout the human genome and that positive selection is not required to explain these observations.

Visceral adipose tissue measured by CT or MRI is strongly associated with an adverse metabolic risk profile. We assessed whether similar associations can be found with ultrasonography, by quantifying the strength of the relationship between different measures of obesity and indices of glucose metabolism in a population at high risk of type 2 diabetes. A cross-sectional analysis of 1342 participants of the ADDITION-PRO study. We measured visceral adipose tissue and subcutaneous adipose tissue with ultrasonography, anthropometrics and body fat percentage by bioelectrical impedance. Indices of glucose metabolism were derived from a three point oral glucose tolerance test. Linear regression of obesity measures on indices of glucose metabolism was performed. Mean age was 66.2 years, BMI 26.9kg/m2, subcutaneous adipose tissue 2.5cm and visceral adipose tissue 8.0cm. All measures of obesity were positively associated with indicators of glycaemia and inversely associated with indicators of insulin sensitivity. Associations were of equivalent magnitude except for subcutaneous adipose tissue and the visceral/subcutaneous adipose tissue ratio, which showed weaker associations. One standard deviation difference in BMI, visceral adipose tissue, waist circumference, waist/height ratio and body fat percentage corresponded approximately to 0.2mmol/l higher fasting glucose, 0.7mmol/l higher 2-hr glucose, 0.06-0.1% higher HbA1c, 30 % lower HOMA index of insulin sensitivity, 20% lower Gutt's index of insulin sensitivity, and 100 unit higher Stumvoll's index of beta-cell function. After adjustment for waist circumference visceral adipose tissue was still significantly associated with glucose intolerance and insulin resistance, whereas there was a trend towards inverse or no associations with subcutaneous adipose tissue. After adjustment, a 1cm increase in visceral adipose tissue was associated with ~5% lower insulin sensitivity (p≤0.0004) and ~0.18mmol/l higher 2-hr glucose (p≤0.001). Visceral and subcutaneous adipose tissue assessed by ultrasonography are significantly associated with glucose metabolism, even after adjustment for other measures of obesity.