| 1. |
- Kaptoge, S., et al.
(författare)
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World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions
- 2019
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Ingår i: Lancet Global Health. - : Elsevier BV. - 2214-109X. ; 7:10, s. E1332-E1345
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Tidskriftsartikel (refereegranskat)abstract
- Background To help adapt cardiovascular disease risk prediction approaches to low-income and middle-income countries, WHO has convened an effort to develop, evaluate, and illustrate revised risk models. Here, we report the derivation, validation, and illustration of the revised WHO cardiovascular disease risk prediction charts that have been adapted to the circumstances of 21 global regions. Methods In this model revision initiative, we derived 10-year risk prediction models for fatal and non-fatal cardiovascular disease (ie, myocardial infarction and stroke) using individual participant data from the Emerging Risk Factors Collaboration. Models included information on age, smoking status, systolic blood pressure, history of diabetes, and total cholesterol. For derivation, we included participants aged 40-80 years without a known baseline history of cardiovascular disease, who were followed up until the first myocardial infarction, fatal coronary heart disease, or stroke event. We recalibrated models using age-specific and sex-specific incidences and risk factor values available from 21 global regions. For external validation, we analysed individual participant data from studies distinct from those used in model derivation. We illustrated models by analysing data on a further 123 743 individuals from surveys in 79 countries collected with the WHO STEPwise Approach to Surveillance. Findings Our risk model derivation involved 376 177 individuals from 85 cohorts, and 19 333 incident cardiovascular events recorded during 10 years of follow-up. The derived risk prediction models discriminated well in external validation cohorts (19 cohorts, 1 096 061 individuals, 25 950 cardiovascular disease events), with Harrell's C indices ranging from 0.685 (95% CI 0 . 629-0 741) to 0.833 (0 . 783-0- 882). For a given risk factor profile, we found substantial variation across global regions in the estimated 10-year predicted risk. For example, estimated cardiovascular disease risk for a 60-year-old male smoker without diabetes and with systolic blood pressure of 140 mm Hg and total cholesterol of 5 mmol/L ranged from 11% in Andean Latin America to 30% in central Asia. When applied to data from 79 countries (mostly low-income and middle-income countries), the proportion of individuals aged 40-64 years estimated to be at greater than 20% risk ranged from less than 1% in Uganda to more than 16% in Egypt. Interpretation We have derived, calibrated, and validated new WHO risk prediction models to estimate cardiovascular disease risk in 21 Global Burden of Disease regions. The widespread use of these models could enhance the accuracy, practicability, and sustainability of efforts to reduce the burden of cardiovascular disease worldwide. Copyright (C) 2019 The Author(s). Published by Elsevier Ltd.
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| 2. |
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| 3. |
- Wilman, H. R., et al.
(författare)
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Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration
- 2019
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Ingår i: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 71:3, s. 594-602
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Tidskriftsartikel (refereegranskat)abstract
- Background & Aims: Excess liver iron content is common and is linked to the risk of hepatic and extrahepatic diseases. We aimed to identify genetic variants influencing liver iron content and use genetics to understand its link to other traits and diseases. Methods: First, we performed a genome-wide association study (GWAS) in 8,289 individuals from UK Biobank, whose liver iron level had been quantified by magnetic resonance imaging, before validating our findings in an independent cohort (n = 1,513 from IMI DIRECT). Second, we used Mendelian randomisation to test the causal effects of 25 predominantly metabolic traits on liver iron content. Third, we tested phenome-wide associations between liver iron variants and 770 traits and disease outcomes. Results: We identified 3 independent genetic variants (rs1800562 [C282Y] and rs1799945 [H63D] in HFE and rs855791 [V736A] in TMPRSS6) associated with liver iron content that reached the GWAS significance threshold (p <5 × 10−8). The 2 HFE variants account for ∼85% of all cases of hereditary haemochromatosis. Mendelian randomisation analysis provided evidence that higher central obesity plays a causal role in increased liver iron content. Phenome-wide association analysis demonstrated shared aetiopathogenic mechanisms for elevated liver iron, high blood pressure, cirrhosis, malignancies, neuropsychiatric and rheumatological conditions, while also highlighting inverse associations with anaemias, lipidaemias and ischaemic heart disease. Conclusion: Our study provides genetic evidence that mechanisms underlying higher liver iron content are likely systemic rather than organ specific, that higher central obesity is causally associated with higher liver iron, and that liver iron shares common aetiology with multiple metabolic and non-metabolic diseases. Lay summary: Excess liver iron content is common and is associated with liver diseases and metabolic diseases including diabetes, high blood pressure, and heart disease. We identified 3 genetic variants that are linked to an increased risk of developing higher liver iron content. We show that the same genetic variants are linked to higher risk of many diseases, but they may also be associated with some health advantages. Finally, we use genetic variants associated with waist-to-hip ratio as a tool to show that central obesity is causally associated with increased liver iron content.
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| 4. |
- Bar, N., et al.
(författare)
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A reference map of potential determinants for the human serum metabolome
- 2020
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Ingår i: Nature. - : Nature Research. - 0028-0836 .- 1476-4687. ; 588:7836, s. 135-140
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Tidskriftsartikel (refereegranskat)abstract
- The serum metabolome contains a plethora of biomarkers and causative agents of various diseases, some of which are endogenously produced and some that have been taken up from the environment1. The origins of specific compounds are known, including metabolites that are highly heritable2,3, or those that are influenced by the gut microbiome4, by lifestyle choices such as smoking5, or by diet6. However, the key determinants of most metabolites are still poorly understood. Here we measured the levels of 1,251 metabolites in serum samples from a unique and deeply phenotyped healthy human cohort of 491 individuals. We applied machine-learning algorithms to predict metabolite levels in held-out individuals on the basis of host genetics, gut microbiome, clinical parameters, diet, lifestyle and anthropometric measurements, and obtained statistically significant predictions for more than 76% of the profiled metabolites. Diet and microbiome had the strongest predictive power, and each explained hundreds of metabolites—in some cases, explaining more than 50% of the observed variance. We further validated microbiome-related predictions by showing a high replication rate in two geographically independent cohorts7,8 that were not available to us when we trained the algorithms. We used feature attribution analysis9 to reveal specific dietary and bacterial interactions. We further demonstrate that some of these interactions might be causal, as some metabolites that we predicted to be positively associated with bread were found to increase after a randomized clinical trial of bread intervention. Overall, our results reveal potential determinants of more than 800 metabolites, paving the way towards a mechanistic understanding of alterations in metabolites under different conditions and to designing interventions for manipulating the levels of circulating metabolites.
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| 5. |
- Koivula, Robert W., et al.
(författare)
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The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes : an IMI DIRECT study
- 2020
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Ingår i: Diabetologia. - : Springer Nature. - 0012-186X .- 1432-0428. ; 63:4, s. 744-756
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Tidskriftsartikel (refereegranskat)abstract
- Aims/hypothesis: It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435). Methods: We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively. Results: The TC and TC-PA models showed better fit than null models (TC: χ2 = 242, p = 0.004 and χ2 = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ2 = 180, p = 0.041 and χ2 = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle. Conclusions/interpretation: These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.
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| 6. |
- Beulens, JWJ, et al.
(författare)
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Risk and management of pre-diabetes
- 2019
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Ingår i: European journal of preventive cardiology. - : Oxford University Press (OUP). - 2047-4881 .- 2047-4873. ; 26:2_SUPPL2_suppl, s. 47-54
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Tidskriftsartikel (refereegranskat)abstract
- Type 2 diabetes mellitus (T2DM) is associated with a two- to four-fold increased risk of developing cardiovascular disease (CVD) and microvascular complications, which may already be present before diagnosis. It is, therefore, important to detect people with an increased risk of T2DM at an early stage. In order to identify individuals with so-called ‘pre-diabetes’, comprising impaired fasting glucose (IFG) and impaired glucose tolerance (IGT), current guidelines have developed definitions based on fasting plasma glucose, two-hour glucose concentrations and haemoglobin A1c. Subjects with pre-diabetes are at an increased risk of developing T2DM and CVD. This elevated risk seems similar according to the different criteria used to define pre-diabetes. The risk of progression to T2DM or CVD does, however, depend on other risk factors such as sex, body mass index and ethnicity. Based on the risk factors to develop T2DM, many risk assessment models have been developed to identify those at highest risk. These models perform well to identify those at risk and could be used to initiate preventive interventions. Many studies have shown that lifestyle modification and metformin are effective in preventing the development of T2DM, although lifestyle modification seems to have a more sustainable effect. In addition, lifestyle modification seems more effective in those with IGT than those with IFG. In this review, we will describe the different definitions used to define pre-diabetes, progression from pre-diabetes to T2DM or other vascular complications, risk factors associated with progressions and the management of progression to T2DM, ending with clinical recommendations.
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| 7. |
- Hagenbeek, FA, et al.
(författare)
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Heritability estimates for 361 blood metabolites across 40 genome-wide association studies
- 2020
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1, s. 39-
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Tidskriftsartikel (refereegranskat)abstract
- Metabolomics examines the small molecules involved in cellular metabolism. Approximately 50% of total phenotypic differences in metabolite levels is due to genetic variance, but heritability estimates differ across metabolite classes. We perform a review of all genome-wide association and (exome-) sequencing studies published between November 2008 and October 2018, and identify >800 class-specific metabolite loci associated with metabolite levels. In a twin-family cohort (N = 5117), these metabolite loci are leveraged to simultaneously estimate total heritability (h2total), and the proportion of heritability captured by known metabolite loci (h2Metabolite-hits) for 309 lipids and 52 organic acids. Our study reveals significant differences in h2Metabolite-hits among different classes of lipids and organic acids. Furthermore, phosphatidylcholines with a high degree of unsaturation have higher h2Metabolite-hits estimates than phosphatidylcholines with low degrees of unsaturation. This study highlights the importance of common genetic variants for metabolite levels, and elucidates the genetic architecture of metabolite classes.
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| 8. |
- Obura, M., et al.
(författare)
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Clinical profiles of post-load glucose subgroups and their association with glycaemic traits over time : An IMI-DIRECT study
- 2021
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Ingår i: Diabetic Medicine. - : Wiley. - 0742-3071 .- 1464-5491. ; 38:2
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Tidskriftsartikel (refereegranskat)abstract
- Aim: To examine the hypothesis that, based on their glucose curves during a seven-point oral glucose tolerance test, people at elevated type 2 diabetes risk can be divided into subgroups with different clinical profiles at baseline and different degrees of subsequent glycaemic deterioration. Methods: We included 2126 participants at elevated type 2 diabetes risk from the Diabetes Research on Patient Stratification (IMI-DIRECT) study. Latent class trajectory analysis was used to identify subgroups from a seven-point oral glucose tolerance test at baseline and follow-up. Linear models quantified the associations between the subgroups with glycaemic traits at baseline and 18 months. Results: At baseline, we identified four glucose curve subgroups, labelled in order of increasing peak levels as 1–4. Participants in Subgroups 2–4, were more likely to have higher insulin resistance (homeostatic model assessment) and a lower Matsuda index, than those in Subgroup 1. Overall, participants in Subgroups 3 and 4, had higher glycaemic trait values, with the exception of the Matsuda and insulinogenic indices. At 18 months, change in homeostatic model assessment of insulin resistance was higher in Subgroup 4 (β = 0.36, 95% CI 0.13–0.58), Subgroup 3 (β = 0.30; 95% CI 0.10–0.50) and Subgroup 2 (β = 0.18; 95% CI 0.04–0.32), compared to Subgroup 1. The same was observed for C-peptide and insulin. Five subgroups were identified at follow-up, and the majority of participants remained in the same subgroup or progressed to higher peak subgroups after 18 months. Conclusions: Using data from a frequently sampled oral glucose tolerance test, glucose curve patterns associated with different clinical characteristics and different rates of subsequent glycaemic deterioration can be identified.
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| 9. |
- Takashima, A, et al.
(författare)
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Declarative memory consolidation in humans: a prospective functional magnetic resonance imaging study
- 2006
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Ingår i: Proceedings of the National Academy of Sciences of the United States of America. - : Proceedings of the National Academy of Sciences. - 0027-8424. ; 103:3, s. 756-761
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Tidskriftsartikel (refereegranskat)abstract
- Retrieval of recently acquired declarative memories depends on the hippocampus, but with time, retrieval is increasingly sustainable by neocortical representations alone. This process has been conceptualized as system-level consolidation. Using functional magnetic resonance imaging, we assessed over the course of three months how consolidation affects the neural correlates of memory retrieval. The duration of slow-wave sleep during a nap/rest period after the initial study session and before the first scan session on day 1 correlated positively with recognition memory performance for items studied before the nap and negatively with hippocampal activity associated with correct confident recognition. Over the course of the entire study, hippocampal activity for correct confident recognition continued to decrease, whereas activity in a ventral medial prefrontal region increased. These findings, together with data obtained in rodents, may prompt a revision of classical consolidation theory, incorporating a transfer of putative linking nodes from hippocampal to prelimbic prefrontal areas.
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| 10. |
- van Dijk, D., et al.
(författare)
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Associations between sleep duration and sleep debt with insulin sensitivity and insulin secretion in the EGIR-RISC Study
- 2019
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Ingår i: Diabetes & Metabolism. - : Elsevier BV. - 1262-3636. ; 45:4, s. 375-381
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Tidskriftsartikel (refereegranskat)abstract
- Aim: Extremes in sleep duration play an important role in the development of type 2 diabetes. We examined the associations between sleep duration and sleep debt with estimates of insulin sensitivity and insulin secretion. Methods: Data were derived from the European multi-centre EGIR-RISC study. Sleep duration and sleep debt were derived from a sleep questionnaire asking about sleeping time during the week and during the weekend. Insulin sensitivity and insulin secretion were estimated from a 2-hour Oral Glucose Tolerance Test, with samples every 30 minutes. Associations between sleep duration and sleep debt with insulin sensitivity and insulin secretion, were analysed by multiple linear regression models corrected for possible confounders. Results: Sleep data were available in 1002 participants, 46% men, mean age 48 ± 8 years, who had an average sleep duration of 7 ± 1 hours [range 3–14] and an average sleep debt (absolute difference hours sleep weekend days minus weekdays) of 1 ± 1 hour [range 0–8]. With regard to insulin sensitivity, we observed an inverted U-shaped association between sleep duration and the Stumvoll MCR in (mL/kg/min), with a corrected β (95% CI) of 2.05 (0.8; 3.3) and for the quadratic term −0.2 (−0.3; −0.1). Similarly, a U-shaped association between sleep duration and log HOMA-IR in (µU/mL), with a corrected βs of −0.83 (−1.4; −0.24) and 0.06 (0.02; 0.10) for the quadratic term. Confounders showed an attenuating effect on the associations, while BMI mediated 60 to 91% of the association between sleep duration and insulin sensitivity. No significant associations were observed between sleep duration with insulin secretion or between sleep debt with either insulin sensitivity or insulin secretion. Conclusions: Short and long sleep duration are associated with a lower insulin sensitivity, suggesting that sleep plays an important role in insulin resistance and may provide the link with development of type 2 diabetes.
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