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Search: WFRF:(Atabaki Pasdar Naeimeh)

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1.
  • Wilman, H. R., et al. (author)
  • Genetic studies of abdominal MRI data identify genes regulating hepcidin as major determinants of liver iron concentration
  • 2019
  • In: Journal of Hepatology. - : Elsevier. - 0168-8278 .- 1600-0641. ; 71:3, s. 594-602
  • Journal article (peer-reviewed)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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2.
  • Agudelo, Leandro Z., et al. (author)
  • Metabolic resilience is encoded in genome plasticity
  • 2021
  • Other publication (other academic/artistic)abstract
    • Metabolism plays a central role in evolution, as resource conservation is a selective pressure for fitness and survival.Resource-driven adaptations offer a good model to study evolutionary innovation more broadly. It remains unknown howresource-driven optimization of genome function integrates chromatin architecture with transcriptional phase transitions.Here we show that tuning of genome architecture and heterotypic transcriptional condensates mediate resilience tonutrient limitation. Network genomic integration of phenotypic, structural, and functional relationships reveals that fattissue promotes organismal adaptations through metabolic acceleration chromatin domains and heterotypic PGC1Acondensates. We find evolutionary adaptations in several dimensions; low conservation of amino acid residues withinprotein disorder regions, nonrandom chromatin location of metabolic acceleration domains, condensate-chromatin stabilitythrough cis-regulatory anchoring and encoding of genome plasticity in radial chromatin organization. We show thatenvironmental tuning of these adaptations leads to fasting endurance, through efficient nuclear compartmentalization oflipid metabolic regions, and, locally, human-specific burst kinetics of lipid cycling genes. This process reduces oxidativestress, and fatty-acid mediated cellular acidification, enabling endurance of condensate chromatin conformations.Comparative genomics of genetic and diet perturbations reveal mammalian convergence of phenotype and structuralrelationships, along with loss of transcriptional control by diet-induced obesity. Further, we find that radial transcriptionalorganization is encoded in functional divergence of metabolic disease variant-hubs, heterotypic condensate composition,and protein residues sensing metabolic variation. During fuel restriction, these features license the formation of largeheterotypic condensates that buffer proton excess, and shift viscoelasticity for condensate endurance. This mechanismmaintains physiological pH, reduces pH-resilient inflammatory gene programs, and enables genome plasticity throughtranscriptionally driven cell-specific chromatin contacts. In vivo manipulation of this circuit promotes fasting-likeadaptations with heterotypic nuclear compartments, metabolic and cell-specific homeostasis. In sum, we uncover here ageneral principle by which transcription uses environmental fluctuations for genome function, and demonstrate howresource conservation optimizes transcriptional self-organization through robust feedback integrators, highlighting obesityas an inhibitor of genome plasticity relevant for many diseases.
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3.
  • Atabaki Pasdar, Naeimeh (author)
  • Enhancing prediction and causal inference in metabolic dyshomeostasis
  • 2020
  • Doctoral thesis (other academic/artistic)abstract
    • This thesis is focused on two globally prevalent diseases: i) non-alcoholic fatty liver disease (NAFLD) and ii) type 2 diabetes (T2D), with an overall aim of improving prediction and causal inference in the context of these conditions. Our projects were mainly conducted using IMI DIRECT and UK Biobank datasets including multi-omics data, extensive environmental exposures, and biological intermediates.In paper I, we utilized structural equation modeling to test the 'twin-cycle' hypothesis concerning interactions between the liver and the pancreas in the etiology of T2D. Furthermore, the association of physical activity with glycemic control was investigated within the twin-cycle hypothesis. Our results showed the association of physical activity with several metabolic traits and factors. Moreover, the mediation effect of basal insulin secretion rate, insulin sensitivity and liver fat was identified from physical activity towards glucose regulation.In paper II, we developed a series of machine learning-based models for the diagnosis of fatty liver, using different combinations of complex clinical and omics input data, to screen at-risk populations for NAFLD. Beta-cell function and insulin sensitivity appeared to be the most informative predictors in the developed diagnostic models. Furthermore, the derived importance lists of each data set (clinical, genetic, transcriptomic, proteomic, and metabolomic) were highlighting previous findings and suggesting potential molecular features of the NAFLD etiology.In paper III, Bayesian network and Mendelian randomization approaches were deployed to examine a range of putative causal associations underlying the development of fatty liver. Our analyses identified basal insulin secretion rate and visceral fat as two key drivers. In addition, the sensitivity analysis on diabetes and non-diabetes strata identified a network mostly dominated by dysglycemia in presence of T2D, whereas, it was mainly controlled by excess adiposity in the absence of T2D. In paper IV, genotype-based recall (GBR) clinical trials, in which the genetic burden of individuals is used in recruiting two groups of participants with a high and low genetic risk score, were simulated and compared with the conventional randomized controlled trials (RCTs) in terms of their statistical power and the required sample sizes. The analysis showed that GBR trials are, under several diverse scenarios, more powerful than conventional RCTs for testing gene-treatment interactions.
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4.
  • Atabaki-Pasdar, Naeimeh, et al. (author)
  • Inferring causal pathways between metabolic processes and liver fat accumulation: an IMI DIRECT study
  • 2021
  • Other publication (other academic/artistic)abstract
    • Type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD) often co-occur. Defining causal pathways underlying this relationship may help optimize the prevention and treatment of both diseases. Thus, we assessed the strength and magnitude of the putative causal pathways linking dysglycemia and fatty liver, using a combination of causal inference methods.Measures of glycemia, insulin dynamics, magnetic resonance imaging (MRI)-derived abdominal and liver fat content, serological biomarkers, lifestyle, and anthropometry were obtained in participants from the IMI DIRECT cohorts (n=795 with new onset T2D and 2234 individuals free from diabetes). UK Biobank (n=3641) was used for modelling and replication purposes. Bayesian networks were employed to infer causal pathways, with causal validation using two-sample Mendelian randomization.Bayesian networks fitted to IMI DIRECT data identified higher basal insulin secretion rate (BasalISR) and MRI-derived excess visceral fat (VAT) accumulation as the features of dysmetabolism most likely to cause liver fat accumulation; the unconditional probability of fatty liver (>5%) increased significantly when conditioning on high levels of BasalISR and VAT (by 23%, 32% respectively; 40% for both). Analyses in UK Biobank yielded comparable results. MR confirmed most causal pathways predicted by the Bayesian networks.Here, BasalISR had the highest causal effect on fatty liver predisposition, providing mechanistic evidence underpinning the established association of NAFLD and T2D. BasalISR may represent a pragmatic biomarker for NAFLD prediction in clinical practice.Competing Interest StatementHR is an employee and shareholder of Sanofi. MIM: The views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. MIM has served on advisory panels for Pfizer, NovoNordisk and Zoe Global, has received honoraria from Merck, Pfizer, Novo Nordisk and Eli Lilly, and research funding from Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, NovoNordisk, Pfizer, Roche, Sanofi Aventis, Servier, and Takeda. As of June 2019, MIM is an employee of Genentech, and a holder of Roche stock. AM is a consultant for Lilly and has received research grants from several diabetes drug companies. PWF has received research grants from numerous diabetes drug companies and fess as consultant from Novo Nordisk, Lilly, and Zoe Global Ltd. He is currently the Scientific Director in Patient Care at the Novo Nordisk Foundation. Other authors declare non competing interests.Funding StatementThe work leading to this publication has received support from the Innovative Medicines Initiative Joint Undertaking under grant agreement 115317 (DIRECT) resources of which are composed of financial contribution from the European Union Seventh Framework Programme (FP7/2007-2013) and EFPIA companies in kind contribution. NAP is supported in part by Henning och Johan Throne-Holsts Foundation, Hans Werthen Foundation, an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. HPM is supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. AGJ is supported by an NIHR Clinician Scientist award (17/0005624). RK is funded by the Novo Nordisk Foundation (NNF18OC0031650) as part of a postdoctoral fellowship, an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. AK, PM, HF, JF and GNG are supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. TJM is funded by an NIHR clinical senior lecturer fellowship. S.Bru acknowledges support from the Novo Nordisk Foundation (grants NNF17OC0027594 and NNF14CC0001). ATH is a Wellcome Trust Senior Investigator and is also supported by the NIHR Exeter Clinical Research Facility. JMS acknowledges support from Science for Life Laboratory (Plasma Profiling Facility), Knut and Alice Wallenberg Foundation (Human Protein Atlas) and Erling-Persson Foundation (KTH Centre for Precision Medicine). MIM is supported by the following grants; Wellcome (090532, 098381, 106130, 203141, 212259); NIH (U01-DK105535). PWF is supported by an IRC award from the Swedish Foundation for Strategic Research and a European Research Council award ERC-2015-CoG - 681742_NASCENT. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:Approval for the study protocol was obtained from each of the regional research ethics review boards separately (Lund, Sweden: 20130312105459927, Copenhagen, Denmark: H-1-2012-166 and H-1-2012-100, Amsterdam, Netherlands: NL40099.029.12, Newcastle, Dundee and Exeter, UK: 12/NE/0132), and all participants provided written informed consent at enrolment. The research conformed to the ethical principles for medical research involving human participants outlined in the Declaration of Helsinki.All necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesAuthors agree to make data and materials supporting the results or analyses presented in their paper available upon reasonable request
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5.
  • Atabaki Pasdar, Naeimeh, et al. (author)
  • Predicting and elucidating the etiology of fatty liver disease: A machine learning modeling and validation study in the IMI DIRECT cohorts
  • 2020
  • In: PLoS Medicine. - San Francisco : Public Library of Science (PLoS). - 1549-1676 .- 1549-1277. ; 17:6, s. 1003149-1003149
  • Journal article (peer-reviewed)abstract
    • BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is highly prevalent and causes serious health complications in individuals with and without type 2 diabetes (T2D). Early diagnosis of NAFLD is important, as this can help prevent irreversible damage to the liver and, ultimately, hepatocellular carcinomas. We sought to expand etiological understanding and develop a diagnostic tool for NAFLD using machine learning. METHODS AND FINDINGS: We utilized the baseline data from IMI DIRECT, a multicenter prospective cohort study of 3,029 European-ancestry adults recently diagnosed with T2D (n = 795) or at high risk of developing the disease (n = 2,234). Multi-omics (genetic, transcriptomic, proteomic, and metabolomic) and clinical (liver enzymes and other serological biomarkers, anthropometry, measures of beta-cell function, insulin sensitivity, and lifestyle) data comprised the key input variables. The models were trained on MRI-image-derived liver fat content (
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6.
  • Atabaki-Pasdar, Naeimeh, et al. (author)
  • Statistical power considerations in genotype-based recall randomized controlled trials
  • 2016
  • In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 6
  • Journal article (peer-reviewed)abstract
    • Randomized controlled trials (RCT) are often underpowered for validating gene-treatment interactions. Using published data from the Diabetes Prevention Program (DPP), we examined power in conventional and genotype-based recall (GBR) trials. We calculated sample size and statistical power for gene-metformin interactions (vs. placebo) using incidence rates, gene-drug interaction effect estimates and allele frequencies reported in the DPP for the rs8065082 SLC47A1 variant, a metformin transported encoding locus. We then calculated statistical power for interactions between genetic risk scores (GRS), metformin treatment and intensive lifestyle intervention (ILI) given a range of sampling frames, clinical trial sample sizes, interaction effect estimates, and allele frequencies; outcomes were type 2 diabetes incidence (time-to-event) and change in small LDL particles (continuous outcome). Thereafter, we compared two recruitment frameworks: GBR (participants recruited from the extremes of a GRS distribution) and conventional sampling (participants recruited without explicit emphasis on genetic characteristics). We further examined the influence of outcome measurement error on statistical power. Under most simulated scenarios, GBR trials have substantially higher power to observe gene-drug and gene-lifestyle interactions than same-sized conventional RCTs. GBR trials are becoming popular for validation of gene-treatment interactions; our analyses illustrate the strengths and weaknesses of this design.
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7.
  • Coral, Daniel E, et al. (author)
  • A phenome-wide comparative analysis of genetic discordance between obesity and type 2 diabetes
  • 2023
  • In: Nature Metabolism. - : Springer Science and Business Media LLC. - 2522-5812. ; 5:2, s. 237-247
  • Journal article (peer-reviewed)abstract
    • Obesity and type 2 diabetes are causally related, yet there is considerable heterogeneity in the consequences of both conditions and the mechanisms of action are poorly defined. Here we show a genetic-driven approach defining two obesity profiles that convey highly concordant and discordant diabetogenic effects. We annotate and then compare association signals for these profiles across clinical and molecular phenotypic layers. Key differences are identified in a wide range of traits, including cardiovascular mortality, fat distribution, liver metabolism, blood pressure, specific lipid fractions and blood levels of proteins involved in extracellular matrix remodelling. We find marginal differences in abundance of Bacteroidetes and Firmicutes bacteria in the gut. Instrumental analyses reveal prominent causal roles for waist-to-hip ratio, blood pressure and cholesterol content of high-density lipoprotein particles in the development of diabetes in obesity. We prioritize 17 genes from the discordant signature that convey protection against type 2 diabetes in obesity, which may represent logical targets for precision medicine approaches.
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8.
  • Cresswell, Emily, et al. (author)
  • The value of neck adipose tissue as a predictor for metabolic risk in health and type 2 diabetes
  • 2024
  • In: Biochemical Pharmacology. - 0006-2952. ; 223
  • Journal article (peer-reviewed)abstract
    • Upper-body adiposity is adversely associated with metabolic health whereas the opposite is observed for the lower-body. The neck is a unique upper-body fat depot in adult humans, housing thermogenic brown adipose tissue (BAT), which is increasingly recognised to influence whole-body metabolic health. Loss of BAT, concurrent with replacement by white adipose tissue (WAT), may contribute to metabolic disease, and specific accumulation of neck fat is seen in certain conditions accompanied by adverse metabolic consequences. Yet, few studies have investigated the relationships between neck fat mass (NFM) and cardiometabolic risk, and the influence of sex and metabolic status. Typically, neck circumference (NC) is used as a proxy for neck fat, without considering other determinants of NC, including variability in neck lean mass. In this study we develop and validate novel methods to quantify NFM using dual x-ray absorptiometry (DEXA) imaging, and subsequently investigate the associations of NFM with metabolic biomarkers across approximately 7000 subjects from the Oxford BioBank. NFM correlated with systemic insulin resistance (Homeostatic Model Assessment for Insulin Resistance; HOMA-IR), low-grade inflammation (plasma high-sensitivity C-Reactive Protein; hsCRP), and metabolic markers of adipose tissue function (plasma triglycerides and non-esterified fatty acids; NEFA). NFM was higher in men than women, higher in type 2 diabetes mellitus compared with non-diabetes, after adjustment for total body fat, and also associated with overall cardiovascular disease risk (calculated QRISK3 score). This study describes the development of methods for accurate determination of NFM at scale and suggests a specific relationship between NFM and adverse metabolic health.
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9.
  • Ji, Yingjie, et al. (author)
  • Genome-wide and abdominal MRI data provide evidence that a genetically determined favorable adiposity phenotype is characterized by lower ectopic liver fat and lower risk of type 2 diabetes, heart disease, and hypertension
  • 2019
  • In: Diabetes. - : American Diabetes Association. - 0012-1797 .- 1939-327X. ; 68:1, s. 207-219
  • Journal article (peer-reviewed)abstract
    • Recent genetic studies have identified alleles associated with opposite effects on adiposity and risk of type 2 diabetes. We aimed to identify more of these variants and test the hypothesis that such favorable adiposity alleles are associated with higher subcutaneous fat and lower ectopic fat. We combined MRI data with genome-wide association studies of body fat percentage (%) and metabolic traits. We report 14 alleles, including 7 newly characterized alleles, associated with higher adiposity but a favorable metabolic profile. Consistent with previous studies, individuals carrying more favorable adiposity alleles had higher body fat % and higher BMI but lower risk of type 2 diabetes, heart disease, and hypertension. These individuals also had higher subcutaneous fat but lower liver fat and a lower visceral-to-subcutaneous adipose tissue ratio. Individual alleles associated with higher body fat % but lower liver fat and lower risk of type 2 diabetes included those in PPARG, GRB14, and IRS1, whereas the allele in ANKRD55 was paradoxically associated with higher visceral fat but lower risk of type 2 diabetes. Most identified favorable adiposity alleles are associated with higher subcutaneous and lower liver fat, a mechanism consistent with the beneficial effects of storing excess triglycerides in metabolically low-risk depots.
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10.
  • Jujić, Amra, et al. (author)
  • Glucose-dependent insulinotropic peptide and risk of cardiovascular events and mortality : a prospective study
  • 2020
  • In: Diabetologia. - : Springer. - 0012-186X .- 1432-0428. ; 63:5, s. 1043-1054
  • Journal article (peer-reviewed)abstract
    • Aims/hypothesis: Evidence that glucose-dependent insulinotropic peptide (GIP) and/or the GIP receptor (GIPR) are involved in cardiovascular biology is emerging. We hypothesised that GIP has untoward effects on cardiovascular biology, in contrast to glucagon-like peptide 1 (GLP-1), and therefore investigated the effects of GIP and GLP-1 concentrations on cardiovascular disease (CVD) and mortality risk.Methods: GIP concentrations were successfully measured during OGTTs in two independent populations (Malmo Diet Cancer-Cardiovascular Cohort [MDC-CC] and Prevalence, Prediction and Prevention of Diabetes in Botnia [PPP-Botnia]) in a total of 8044 subjects. GLP-1 (n = 3625) was measured in MDC-CC. The incidence of CVD and mortality was assessed via national/regional registers or questionnaires. Further, a two-sample Mendelian randomisation (2SMR) analysis between the GIP pathway and outcomes (coronary artery disease [CAD] and myocardial infarction) was carried out using a GIP-associated genetic variant, rs1800437, as instrumental variable. An additional reverse 2SMR was performed with CAD as exposure variable and GIP as outcome variable, with the instrumental variables constructed from 114 known genetic risk variants for CAD.Results: In meta-analyses, higher fasting levels of GIP were associated with risk of higher total mortality (HR[95% CI] = 1.22 [1.11, 1.35]; p = 4.5 x 10(-5)) and death from CVD (HR[95% CI] 1.30 [1.11, 1.52]; p = 0.001). In accordance, 2SMR analysis revealed that increasing GIP concentrations were associated with CAD and myocardial infarction, and an additional reverse 2SMR revealed no significant effect of CAD on GIP levels, thus confirming a possible effect solely of GIP on CAD.Conclusions/interpretation: In two prospective, community-based studies, elevated levels of GIP were associated with greater risk of all-cause and cardiovascular mortality within 5-9 years of follow-up, whereas GLP-1 levels were not associated with excess risk. Further studies are warranted to determine the cardiovascular effects of GIP per se.
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11.
  • Jujić, Amra, et al. (author)
  • Glucose-Dependent Insulinotropic Peptide in the High-Normal Range Is Associated With Increased Carotid Intima-Media Thickness
  • 2021
  • In: Diabetes Care. - : American Diabetes Association. - 0149-5992 .- 1935-5548. ; 44:1, s. 224-230
  • Journal article (peer-reviewed)abstract
    • OBJECTIVE While existing evidence supports beneficial cardiovascular effects of glucagon-like peptide 1 (GLP-1), emerging studies suggest that glucose-dependent insulinotropic peptide (GIP) and/or signaling via the GIP receptor may have untoward cardiovascular effects. Indeed, recent studies show that fasting physiological GIP levels are associated with total mortality and cardiovascular mortality, and it was suggested that GIP plays a role in pathogenesis of coronary artery disease. We investigated the associations between fasting and postchallenge GIP and GLP-1 concentrations and subclinical atherosclerosis as measured by mean intima-media thickness in the common carotid artery (IMTmeanCCA) and maximal intima-media thickness in the carotid bifurcation (IMTmaxBulb).RESEARCH DESIGN AND METHODS Participants at reexamination within the Malmö Diet and Cancer–Cardiovascular Cohort study (n = 3,734, mean age 72.5 years, 59.3% women, 10.8% subjects with diabetes, fasting GIP available for 3,342 subjects, fasting GLP-1 available for 3,299 subjects) underwent oral glucose tolerance testing and carotid ultrasound.RESULTS In linear regression analyses, each 1-SD increment of fasting GIP was associated with increased (per mm) IMTmeanCCA (β = 0.010, P = 0.010) and IMTmaxBulb (β = 0.014; P = 0.040) in models adjusted for known risk factors and glucose metabolism. In contrast, each 1-SD increment of fasting GLP-1 was associated with decreased IMTmaxBulb (per mm, β = −0.016, P = 0.014). These associations remained significant when subjects with diabetes were excluded from analyses.CONCLUSIONS In a Swedish elderly population, physiologically elevated levels of fasting GIP are associated with increased IMTmeanCCA, while GLP-1 is associated with decreased IMTmaxBulb, further emphasizing diverging cardiovascular effects of these two incretin hormones.
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12.
  • Koivula, Robert W., et al. (author)
  • The role of physical activity in metabolic homeostasis before and after the onset of type 2 diabetes : an IMI DIRECT study
  • 2020
  • In: Diabetologia. - : Springer Nature. - 0012-186X .- 1432-0428. ; 63:4, s. 744-756
  • Journal article (peer-reviewed)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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13.
  • Mutie, Pascal M., et al. (author)
  • An investigation of causal relationships between prediabetes and vascular complications
  • 2020
  • In: Nature Communications. - : Nature Publishing Group. - 2041-1723. ; 11:1
  • Journal article (peer-reviewed)abstract
    • Prediabetes is a state of glycaemic dysregulation below the diagnostic threshold of type 2 diabetes (T2D). Globally, ~352 million people have prediabetes, of which 35–50% develop full-blown diabetes within five years. T2D and its complications are costly to treat, causing considerable morbidity and early mortality. Whether prediabetes is causally related to diabetes complications is unclear. Here we report a causal inference analysis investigating the effects of prediabetes in coronary artery disease, stroke and chronic kidney disease, complemented by a systematic review of relevant observational studies. Although the observational studies suggest that prediabetes is broadly associated with diabetes complications, the causal inference analysis revealed that prediabetes is only causally related with coronary artery disease, with no evidence of causal effects on other diabetes complications. In conclusion, prediabetes likely causes coronary artery disease and its prevention is likely to be most effective if initiated prior to the onset of diabetes.
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14.
  • Mutie, Pascal M, et al. (author)
  • Investigating the causal relationships between excess adiposity and cardiometabolic health in men and women
  • 2023
  • In: Diabetologia. - : Springer Science and Business Media LLC. - 1432-0428 .- 0012-186X. ; 66:2, s. 321-335
  • Journal article (peer-reviewed)abstract
    • AIMS/HYPOTHESIS: Excess adiposity is differentially associated with increased risk of cardiometabolic disease in men and women, according to observational studies. Causal inference studies largely assume a linear relationship between BMI and cardiometabolic outcomes, which may not be the case. In this study, we investigated the shapes of the causal relationships between BMI and cardiometabolic diseases and risk factors. We further investigated sex differences within the causal framework.METHODS: To assess causal relationships between BMI and the outcomes, we used two-stage least-squares Mendelian randomisation (MR), with a polygenic risk score for BMI as the instrumental variable. To elucidate the shapes of the causal relationships, we used a non-linear MR fractional polynomial method, and used piecewise MR to investigate threshold relationships and confirm the shapes.RESULTS: BMI was associated with type 2 diabetes (OR 3.10; 95% CI 2.73, 3.53), hypertension (OR 1.53; 95% CI 1.44, 1.62) and coronary artery disease (OR 1.20; 95% CI 1.08, 1.33), but not chronic kidney disease (OR 1.08; 95% CI 0.67, 1.72) or stroke (OR 1.08; 95% CI 0.92, 1.28). The data suggest that these relationships are non-linear. For cardiometabolic risk factors, BMI was positively associated with glucose, HbA1c, triacylglycerol levels and both systolic and diastolic BP. BMI had an inverse causal relationship with total cholesterol, LDL-cholesterol and HDL-cholesterol. The data suggest a non-linear causal relationship between BMI and BP and other biomarkers (p<0.001) except lipoprotein A. The piecewise MR results were consistent with the fractional polynomial results. The causal effect of BMI on coronary artery disease, total cholesterol and LDL-cholesterol was different in men and women, but this sex difference was only significant for LDL-cholesterol after controlling for multiple testing (p<0.001). Further, the causal effect of BMI on coronary artery disease varied by menopause status in women.CONCLUSIONS/INTERPRETATION: We describe the shapes of causal effects of BMI on cardiometabolic diseases and risk factors, and report sex differences in the causal effects of BMI on LDL-cholesterol. We found evidence of non-linearity in the causal effect of BMI on diseases and risk factor biomarkers. Reducing excess adiposity is highly beneficial for health, but there is greater need to consider biological sex in the management of adiposity.
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15.
  • Pomares-Millan, Hugo, et al. (author)
  • Estimating the Direct Effect between Dietary Macronutrients and Cardiometabolic Disease, Accounting for Mediation by Adiposity and Physical Activity
  • 2022
  • In: Nutrients. - : MDPI. - 2072-6643. ; 14:6
  • Journal article (peer-reviewed)abstract
    • Assessing the causal effects of individual dietary macronutrients and cardiometabolic disease is challenging owing to the complexity to distinguish direct effects from those mediated or confounded by other factors. To estimate these effects, intake of protein, carbohydrate, sugar, fat, and its subtypes were obtained using food frequency data derived from a Swedish population-based cohort (n~60,000). Data on clinical outcomes (i.e., type 2 diabetes (T2D) and cardiovascular disease (CVD) incidence) were obtained by linking health registry data. We assessed the magnitude of direct and mediated effects of diet, adiposity and physical activity on T2D and CVD using structural equation modelling (SEM). To strengthen causal inference, we used Mendelian randomization (MR) to model macronutrient intake exposures against clinical outcomes. We identified likely causal effects of genetically predicted carbohydrate intake (including sugar intake) and T2D, independent of adiposity and physical activity. Pairwise, serial-and parallel-mediational configurations yielded similar results. In the integrative genomic analyses, the candidate causal variant localized to the established type 2 diabetes gene TCF7L2. These findings may be informative when considering which dietary modifications included in nutritional guidelines are most likely to elicit health-promoting effects.
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16.
  • Pomares-Millan, Hugo, et al. (author)
  • Predicting Sensitivity to Adverse Lifestyle Risk Factors for Cardiometabolic Morbidity and Mortality
  • 2022
  • In: Nutrients. - Basel : MDPI. - 2072-6643. ; 14:15
  • Journal article (peer-reviewed)abstract
    • People appear to vary in their susceptibility to lifestyle risk factors for cardiometabolic disease; determining a priori who is most sensitive may help optimize the timing, design, and delivery of preventative interventions. We aimed to ascertain a person’s degree of resilience or sensitivity to adverse lifestyle exposures and determine whether these classifications help predict cardiometabolic disease later in life; we pooled data from two population-based Swedish prospective cohort studies (n = 53,507), and we contrasted an individual’s cardiometabolic biomarker profile with the profile predicted for them given their lifestyle exposure characteristics using a quantile random forest approach. People who were classed as ‘sensitive’ to hypertension- and dyslipidemia-related lifestyle exposures were at higher risk of developing cardiovascular disease (CVD, hazards ratio 1.6 (95% CI: 1.3, 1.91)), compared with the general population. No differences were observed for type 2 diabetes (T2D) risk. Here, we report a novel approach to identify individuals who are especially sensitive to adverse lifestyle exposures and who are at higher risk of subsequent cardiovascular events. Early preventive interventions may be needed in this subgroup.
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17.
  • Poveda, Alaitz, et al. (author)
  • Association of Established Blood Pressure Loci With 10-Year Change in Blood Pressure and Their Ability to Predict Incident Hypertension
  • 2020
  • In: Journal of the American Heart Association. - : John Wiley & Sons. - 2047-9980. ; 9:16
  • Journal article (peer-reviewed)abstract
    • Background: Genome‐wide association studies have identified >1000 genetic variants cross‐sectionally associated with blood pressure variation and prevalent hypertension. These discoveries might aid the early identification of subpopulations at risk of developing hypertension or provide targets for drug development, amongst other applications. The aim of the present study was to analyze the association of blood pressure‐associated variants with long‐term changes (10 years) in blood pressure and also to assess their ability to predict hypertension incidence compared with traditional risk variables in a Swedish population.Methods and Results: We constructed 6 genetic risk scores (GRSs) by summing the dosage of the effect allele at each locus of genetic variants previously associated with blood pressure traits (systolic blood pressure GRS (GRSSBP): 554 variants; diastolic blood pressure GRS (GRSDBP): 481 variants; mean arterial pressure GRS (GRSMAP): 20 variants; pulse pressure GRS (GRSPP): 478 variants; hypertension GRS (GRSHTN): 22 variants; combined GRS (GRScomb): 1152 variants). Each GRS was longitudinally associated with its corresponding blood pressure trait, with estimated effects per GRS SD unit of 0.50 to 1.21 mm Hg for quantitative traits and odds ratios (ORs) of 1.10 to 1.35 for hypertension incidence traits. The GRScomb was also significantly associated with hypertension incidence defined according to European guidelines (OR, 1.22 per SD; 95% CI, 1.10‒1.35) but not US guidelines (OR, 1.11 per SD; 95% CI, 0.99‒1.25) while controlling for traditional risk factors. The addition of GRScomb to a model containing traditional risk factors only marginally improved discrimination (Δarea under the ROC curve = 0.001–0.002).Conclusions: GRSs based on discovered blood pressure‐associated variants are associated with long‐term changes in blood pressure traits and hypertension incidence, but the inclusion of genetic factors in a model composed of conventional hypertension risk factors did not yield a material increase in predictive ability.
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