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Author Correction: Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.
Allesøe, RL, Lundgaard, AT, Hernández Medina, R, Aguayo-Orozco, A, Johansen, J, Nissen, JN, Brorsson, C, Mazzoni, G, Niu, L, Biel, JH, et al
Nature biotechnology. 2023;(7):1026
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Genetic analysis of blood molecular phenotypes reveals common properties in the regulatory networks affecting complex traits.
Brown, AA, Fernandez-Tajes, JJ, Hong, MG, Brorsson, CA, Koivula, RW, Davtian, D, Dupuis, T, Sartori, A, Michalettou, TD, Forgie, IM, et al
Nature communications. 2023;(1):5062
Abstract
We evaluate the shared genetic regulation of mRNA molecules, proteins and metabolites derived from whole blood from 3029 human donors. We find abundant allelic heterogeneity, where multiple variants regulate a particular molecular phenotype, and pleiotropy, where a single variant associates with multiple molecular phenotypes over multiple genomic regions. The highest proportion of share genetic regulation is detected between gene expression and proteins (66.6%), with a further median shared genetic associations across 49 different tissues of 78.3% and 62.4% between plasma proteins and gene expression. We represent the genetic and molecular associations in networks including 2828 known GWAS variants, showing that GWAS variants are more often connected to gene expression in trans than other molecular phenotypes in the network. Our work provides a roadmap to understanding molecular networks and deriving the underlying mechanism of action of GWAS variants using different molecular phenotypes in an accessible tissue.
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Discovery of drug-omics associations in type 2 diabetes with generative deep-learning models.
Allesøe, RL, Lundgaard, AT, Hernández Medina, R, Aguayo-Orozco, A, Johansen, J, Nissen, JN, Brorsson, C, Mazzoni, G, Niu, L, Biel, JH, et al
Nature biotechnology. 2023;(3):399-408
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Abstract
The application of multiple omics technologies in biomedical cohorts has the potential to reveal patient-level disease characteristics and individualized response to treatment. However, the scale and heterogeneous nature of multi-modal data makes integration and inference a non-trivial task. We developed a deep-learning-based framework, multi-omics variational autoencoders (MOVE), to integrate such data and applied it to a cohort of 789 people with newly diagnosed type 2 diabetes with deep multi-omics phenotyping from the DIRECT consortium. Using in silico perturbations, we identified drug-omics associations across the multi-modal datasets for the 20 most prevalent drugs given to people with type 2 diabetes with substantially higher sensitivity than univariate statistical tests. From these, we among others, identified novel associations between metformin and the gut microbiota as well as opposite molecular responses for the two statins, simvastatin and atorvastatin. We used the associations to quantify drug-drug similarities, assess the degree of polypharmacy and conclude that drug effects are distributed across the multi-omics modalities.
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Evidence of a causal and modifiable relationship between kidney function and circulating trimethylamine N-oxide.
Andrikopoulos, P, Aron-Wisnewsky, J, Chakaroun, R, Myridakis, A, Forslund, SK, Nielsen, T, Adriouch, S, Holmes, B, Chilloux, J, Vieira-Silva, S, et al
Nature communications. 2023;(1):5843
Abstract
The host-microbiota co-metabolite trimethylamine N-oxide (TMAO) is linked to increased cardiovascular risk but how its circulating levels are regulated remains unclear. We applied "explainable" machine learning, univariate, multivariate and mediation analyses of fasting plasma TMAO concentration and a multitude of phenotypes in 1,741 adult Europeans of the MetaCardis study. Here we show that next to age, kidney function is the primary variable predicting circulating TMAO, with microbiota composition and diet playing minor, albeit significant, roles. Mediation analysis suggests a causal relationship between TMAO and kidney function that we corroborate in preclinical models where TMAO exposure increases kidney scarring. Consistent with our findings, patients receiving glucose-lowering drugs with reno-protective properties have significantly lower circulating TMAO when compared to propensity-score matched control individuals. Our analyses uncover a bidirectional relationship between kidney function and TMAO that can potentially be modified by reno-protective anti-diabetic drugs and suggest a clinically actionable intervention for decreasing TMAO-associated excess cardiovascular risk.
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Microbiome and metabolome features of the cardiometabolic disease spectrum.
Fromentin, S, Forslund, SK, Chechi, K, Aron-Wisnewsky, J, Chakaroun, R, Nielsen, T, Tremaroli, V, Ji, B, Prifti, E, Myridakis, A, et al
Nature medicine. 2022;(2):303-314
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Abstract
Previous microbiome and metabolome analyses exploring non-communicable diseases have paid scant attention to major confounders of study outcomes, such as common, pre-morbid and co-morbid conditions, or polypharmacy. Here, in the context of ischemic heart disease (IHD), we used a study design that recapitulates disease initiation, escalation and response to treatment over time, mirroring a longitudinal study that would otherwise be difficult to perform given the protracted nature of IHD pathogenesis. We recruited 1,241 middle-aged Europeans, including healthy individuals, individuals with dysmetabolic morbidities (obesity and type 2 diabetes) but lacking overt IHD diagnosis and individuals with IHD at three distinct clinical stages-acute coronary syndrome, chronic IHD and IHD with heart failure-and characterized their phenome, gut metagenome and serum and urine metabolome. We found that about 75% of microbiome and metabolome features that distinguish individuals with IHD from healthy individuals after adjustment for effects of medication and lifestyle are present in individuals exhibiting dysmetabolism, suggesting that major alterations of the gut microbiome and metabolome might begin long before clinical onset of IHD. We further categorized microbiome and metabolome signatures related to prodromal dysmetabolism, specific to IHD in general or to each of its three subtypes or related to escalation or de-escalation of IHD. Discriminant analysis based on specific IHD microbiome and metabolome features could better differentiate individuals with IHD from healthy individuals or metabolically matched individuals as compared to the conventional risk markers, pointing to a pathophysiological relevance of these features.
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Effects of 18-months metformin versus placebo in combination with three insulin regimens on RNA and DNA oxidation in individuals with type 2 diabetes: A post-hoc analysis of a randomized clinical trial.
Larsen, EL, Kjær, LK, Lundby-Christensen, L, Boesgaard, TW, Breum, L, Gluud, C, Hedetoft, C, Krarup, T, Lund, SS, Mathiesen, ER, et al
Free radical biology & medicine. 2022;:18-25
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Abstract
Formation of reactive oxygen species has been linked to the development of diabetes complications. Treatment with metformin has been associated with a lower risk of developing diabetes complications, including when used in combination with insulin. Metformin inhibits Complex 1 in isolated mitochondria and thereby decreases the formation of reactive oxygen species. Thus, we post-hoc investigated the effect of metformin in combination with different insulin regimens on RNA and DNA oxidation in individuals with type 2 diabetes. Four hundred and fifteen individuals with type 2 diabetes were randomized (1:1) to blinded treatment with metformin (1,000 mg twice daily) versus placebo and to (1:1:1) open-label biphasic insulin, basal-bolus insulin, or basal insulin therapy in a 2 × 3 factorial design. RNA and DNA oxidation were determined at baseline and after 18 months measured as urinary excretions of 8-oxo-7,8-dihydroguanosine (8-oxoGuo) and 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG), respectively. Urinary excretion of 8-oxoGuo changed by +7.1% (95% CI: 0.5% to 14.0%, P = 0.03) following metformin versus placebo, whereas changes in 8-oxodG were comparable between intervention groups. Biphasic insulin decreased urinary excretion of 8-oxoGuo (within-group: -9.6% (95% CI: -14.4% to -4.4%)) more than basal-bolus insulin (within-group: 5.2% (95% CI: -0.5% to 11.2%)), P = 0.0002 between groups, and basal insulin (within-group: 3.7% (95% CI: -2.0% to 9.7%)), P = 0.0007 between groups. Urinary excretion of 8-oxodG decreased more in the biphasic insulin group (within-group: -9.9% (95% CI: -14.4% to -5.2%)) than basal-bolus insulin (within group effect: -1.2% (95% CI: -6.1% to 3.9%)), P = 0.01 between groups, whereas no difference was observed compared with basal insulin. In conclusion, eighteen months of metformin treatment in addition to different insulin regimens increased RNA oxidation, but not DNA oxidation. Biphasic insulin decreased both RNA and DNA oxidation compared with other insulin regimens.
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Effect of metformin and insulin vs. placebo and insulin on whole body composition in overweight patients with type 2 diabetes: a randomized placebo-controlled trial.
Nordklint, AK, Almdal, TP, Vestergaard, P, Lundby-Christensen, L, Boesgaard, TW, Breum, L, Gade-Rasmussen, B, Sneppen, SB, Gluud, C, Hemmingsen, B, et al
Osteoporosis international : a journal established as result of cooperation between the European Foundation for Osteoporosis and the National Osteoporosis Foundation of the USA. 2021;(9):1837-1848
Abstract
UNLABELLED Some studies indicate potential beneficial effects of metformin on body composition and bone. This trial compared metformin + insulin vs placebo + insulin. Metformin treatment had a small but positive effect on bone quality in the peripheral skeleton, reduced weight gain, and resulted in a more beneficial body composition compared with placebo in insulin-treated patients with type 2 diabetes. INTRODUCTION Glucose-lowering medications affect body composition. We assessed the long-term effects of metformin compared with placebo on whole body bone and body composition measures in patients with type 2 diabetes mellitus. METHODS This was a sub-study of the Copenhagen Insulin and Metformin Therapy trial, which was a double-blinded randomized placebo-controlled trial assessing 18-month treatment with metformin compared with placebo, in combination with different insulin regimens in patients with type 2 diabetes mellitus (T2DM). The sub-study evaluates the effects on bone mineral content (BMC), density (BMD), and body composition from whole body dual-energy X-ray absorptiometry (DXA) scans which were assessed at baseline and after 18 months. RESULTS Metformin had a small, but positive, (p < 0.05) effect on subtotal, appendicular, and legs BMC and BMD compared with placebo. After adjustment for sex, age, vitamin D, smoking, BMI, T2DM duration, HbA1c, and insulin dose, the effects on appendicular BMC and BMD persisted (p < 0.05 for both). The changes in appendicular BMC and BMD corresponded approximately to a 0.7% and 0.5% increase in the metformin group and 0.4% and 0.4% decrease in the placebo group, respectively. These effects were mostly driven by an increase in BMC and BMD in the legs and a loss of BMC and BMD in the arms. During 18 months, all participants increased in weight, fat mass (FM), FM%, and lean mass (LM), but decreased in LM%. The metformin group increased less in weight (subtotal weight (weight-head) - 2.4 [- 3.5, - 1.4] kg, p value < 0.001) and FM (- 1.5 [- 2.3, - 0.8] kg, p value < 0.001) and decreased less in LM% (0.6 [0.2, 1.1] %, p value < 0.001) compared with the placebo group. CONCLUSION Metformin treatment had a small positive effect on BMC and BMD in the peripheral skeleton and reduced weight gain compared with placebo in insulin-treated patients with T2DM.
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The trans-ancestral genomic architecture of glycemic traits.
Chen, J, Spracklen, CN, Marenne, G, Varshney, A, Corbin, LJ, Luan, J, Willems, SM, Wu, Y, Zhang, X, Horikoshi, M, et al
Nature genetics. 2021;(6):840-860
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Abstract
Glycemic traits are used to diagnose and monitor type 2 diabetes and cardiometabolic health. To date, most genetic studies of glycemic traits have focused on individuals of European ancestry. Here we aggregated genome-wide association studies comprising up to 281,416 individuals without diabetes (30% non-European ancestry) for whom fasting glucose, 2-h glucose after an oral glucose challenge, glycated hemoglobin and fasting insulin data were available. Trans-ancestry and single-ancestry meta-analyses identified 242 loci (99 novel; P < 5 × 10-8), 80% of which had no significant evidence of between-ancestry heterogeneity. Analyses restricted to individuals of European ancestry with equivalent sample size would have led to 24 fewer new loci. Compared with single-ancestry analyses, equivalent-sized trans-ancestry fine-mapping reduced the number of estimated variants in 99% credible sets by a median of 37.5%. Genomic-feature, gene-expression and gene-set analyses revealed distinct biological signatures for each trait, highlighting different underlying biological pathways. Our results increase our understanding of diabetes pathophysiology by using trans-ancestry studies for improved power and resolution.
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Combinatorial, additive and dose-dependent drug-microbiome associations.
Forslund, SK, Chakaroun, R, Zimmermann-Kogadeeva, M, Markó, L, Aron-Wisnewsky, J, Nielsen, T, Moitinho-Silva, L, Schmidt, TSB, Falony, G, Vieira-Silva, S, et al
Nature. 2021;(7889):500-505
Abstract
During the transition from a healthy state to cardiometabolic disease, patients become heavily medicated, which leads to an increasingly aberrant gut microbiome and serum metabolome, and complicates biomarker discovery1-5. Here, through integrated multi-omics analyses of 2,173 European residents from the MetaCardis cohort, we show that the explanatory power of drugs for the variability in both host and gut microbiome features exceeds that of disease. We quantify inferred effects of single medications, their combinations as well as additive effects, and show that the latter shift the metabolome and microbiome towards a healthier state, exemplified in synergistic reduction in serum atherogenic lipoproteins by statins combined with aspirin, or enrichment of intestinal Roseburia by diuretic agents combined with beta-blockers. Several antibiotics exhibit a quantitative relationship between the number of courses prescribed and progression towards a microbiome state that is associated with the severity of cardiometabolic disease. We also report a relationship between cardiometabolic drug dosage, improvement in clinical markers and microbiome composition, supporting direct drug effects. Taken together, our computational framework and resulting resources enable the disentanglement of the effects of drugs and disease on host and microbiome features in multimedicated individuals. Furthermore, the robust signatures identified using our framework provide new hypotheses for drug-host-microbiome interactions in cardiometabolic disease.
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Profiles of Glucose Metabolism in Different Prediabetes Phenotypes, Classified by Fasting Glycemia, 2-Hour OGTT, Glycated Hemoglobin, and 1-Hour OGTT: An IMI DIRECT Study.
Tura, A, Grespan, E, Göbl, CS, Koivula, RW, Franks, PW, Pearson, ER, Walker, M, Forgie, IM, Giordano, GN, Pavo, I, et al
Diabetes. 2021;(9):2092-2106
Abstract
Differences in glucose metabolism among categories of prediabetes have not been systematically investigated. In this longitudinal study, participants (N = 2,111) underwent a 2-h 75-g oral glucose tolerance test (OGTT) at baseline and 48 months. HbA1c was also measured. We classified participants as having isolated prediabetes defect (impaired fasting glucose [IFG], impaired glucose tolerance [IGT], or HbA1c indicative of prediabetes [IA1c]), two defects (IFG+IGT, IFG+IA1c, or IGT+IA1c), or all defects (IFG+IGT+IA1c). β-Cell function (BCF) and insulin sensitivity were assessed from OGTT. At baseline, in pooling of participants with isolated defects, they showed impairment in both BCF and insulin sensitivity compared with healthy control subjects. Pooled groups with two or three defects showed progressive further deterioration. Among groups with isolated defect, those with IGT showed lower insulin sensitivity, insulin secretion at reference glucose (ISRr), and insulin secretion potentiation (P < 0.002). Conversely, those with IA1c showed higher insulin sensitivity and ISRr (P < 0.0001). Among groups with two defects, we similarly found differences in both BCF and insulin sensitivity. At 48 months, we found higher type 2 diabetes incidence for progressively increasing number of prediabetes defects (odds ratio >2, P < 0.008). In conclusion, the prediabetes groups showed differences in type/degree of glucometabolic impairment. Compared with the pooled group with isolated defects, those with double or triple defect showed progressive differences in diabetes incidence.