scholarly journals Associations among circulating sphingolipids, β-cell function, and risk of developing type 2 diabetes: A population-based cohort study in China

PLoS Medicine ◽  
2020 ◽  
Vol 17 (12) ◽  
pp. e1003451
Author(s):  
Huan Yun ◽  
Liang Sun ◽  
Qingqing Wu ◽  
Geng Zong ◽  
Qibin Qi ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Cell Function ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Β Cell ◽  
Nutrition Survey ◽  
Cell Dysfunction ◽  
Independent Population

Background Animal studies suggest vital roles of sphingolipids, especially ceramides, in the pathogenesis of type 2 diabetes (T2D) via pathways involved in insulin resistance, β-cell dysfunction, and inflammation, but human studies are limited. We aimed to evaluate the associations of circulating sphingolipids with incident T2D and to explore underlying mechanisms. Methods and findings The current study included 826 men and 1,148 women who were aged 50–70 years, from Beijing and Shanghai, and without T2D in 2005 and who were resurveyed in 2011. Cardiometabolic traits were measured at baseline and follow-up surveys. A total of 76 sphingolipids were quantified using high-coverage targeted lipidomics. Summary data for 2-sample Mendelian randomization were obtained from genome-wide association studies of circulating sphingolipids and the China Health and Nutrition Survey (n = 5,731). During the 6-year period, 529 participants developed T2D. Eleven novel and 3 reported sphingolipids, namely ceramides (d18:1/18:1, d18:1/20:0, d18:1/20:1, d18:1/22:1), saturated sphingomyelins (C34:0, C36:0, C38:0, C40:0), unsaturated sphingomyelins (C34:1, C36:1, C42:3), hydroxyl-sphingomyelins (C34:1, C38:3), and a hexosylceramide (d18:1/20:1), were positively associated with incident T2D (relative risks [RRs]: 1.14–1.21; all P < 0.001), after multivariate adjustment including lifestyle characteristics and BMI. Network analysis further identified 5 modules, and 2 modules containing saturated sphingomyelins showed the strongest associations with increased T2D risk (RRQ4 versus Q1 = 1.59 and 1.43; both Ptrend < 0.001). Mediation analysis suggested that the detrimental associations of 13 sphingolipids with T2D were largely mediated through β-cell dysfunction, as indicated by HOMA-B (mediation proportion: 11.19%–42.42%; all P < 0.001). Moreover, Mendelian randomization evidenced a positive association between a genetically instrumented ceramide (d18:1/20:1) and T2D (odds ratio: 1.15 [95% CI 1.05–1.26]; P = 0.002). Main limitations in the current study included potential undiagnosed cases and lack of an independent population for replication. Conclusions In this study, we observed that a panel of novel sphingolipids with unique structures were positively associated with incident T2D, largely mediated through β-cell dysfunction, in Chinese individuals.

scholarly journals A comprehensive evaluation of methods for Mendelian randomization using realistic simulations and an analysis of 38 biomarkers for risk of type 2 diabetes

2021 ◽  
Author(s):  
Guanghao Qi ◽  
Nilanjan Chatterjee
Keyword(s):  
Type 2 Diabetes ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Real Data ◽  
Causal Effects ◽  
Type I ◽  
Genome Wide Association Studies ◽  
Simulation Studies ◽  
Sample Sizes

Abstract Background Previous studies have often evaluated methods for Mendelian randomization (MR) analysis based on simulations that do not adequately reflect the data-generating mechanisms in genome-wide association studies (GWAS) and there are often discrepancies in the performance of MR methods in simulations and real data sets. Methods We use a simulation framework that generates data on full GWAS for two traits under a realistic model for effect-size distribution coherent with the heritability, co-heritability and polygenicity typically observed for complex traits. We further use recent data generated from GWAS of 38 biomarkers in the UK Biobank and performed down sampling to investigate trends in estimates of causal effects of these biomarkers on the risk of type 2 diabetes (T2D). Results Simulation studies show that weighted mode and MRMix are the only two methods that maintain the correct type I error rate in a diverse set of scenarios. Between the two methods, MRMix tends to be more powerful for larger GWAS whereas the opposite is true for smaller sample sizes. Among the other methods, random-effect IVW (inverse-variance weighted method), MR-Robust and MR-RAPS (robust adjust profile score) tend to perform best in maintaining a low mean-squared error when the InSIDE assumption is satisfied, but can produce large bias when InSIDE is violated. In real-data analysis, some biomarkers showed major heterogeneity in estimates of their causal effects on the risk of T2D across the different methods and estimates from many methods trended in one direction with increasing sample size with patterns similar to those observed in simulation studies. Conclusion The relative performance of different MR methods depends heavily on the sample sizes of the underlying GWAS, the proportion of valid instruments and the validity of the InSIDE assumption. Down-sampling analysis can be used in large GWAS for the possible detection of bias in the MR methods.

scholarly journals Evaluation of glycemic traits in susceptibility to COVID-19 risk: a Mendelian randomization study

BMC Medicine ◽  
2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Shiu Lun Au Yeung ◽  
Jie V Zhao ◽  
C Mary Schooling
Keyword(s):  
Type 2 Diabetes ◽  
Genetic Predisposition ◽  
Mendelian Randomization ◽  
Fasting Glucose ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Inverse Association ◽  
Wide Confidence Interval

Abstract Background Observational studies suggest poorer glycemic traits and type 2 diabetes associated with coronavirus disease 2019 (COVID-19) risk although these findings could be confounded by socioeconomic position. We conducted a two-sample Mendelian randomization to clarify their role in COVID-19 risk and specific COVID-19 phenotypes (hospitalized and severe cases). Method We identified genetic instruments for fasting glucose (n = 133,010), 2 h glucose (n = 42,854), glycated hemoglobin (n = 123,665), and type 2 diabetes (74,124 cases and 824,006 controls) from genome wide association studies and applied them to COVID-19 Host Genetics Initiative summary statistics (17,965 COVID-19 cases and 1,370,547 population controls). We used inverse variance weighting to obtain the causal estimates of glycemic traits and genetic predisposition to type 2 diabetes in COVID-19 risk. Sensitivity analyses included MR-Egger and weighted median method. Results We found genetic predisposition to type 2 diabetes was not associated with any COVID-19 phenotype (OR: 1.00 per unit increase in log odds of having diabetes, 95%CI 0.97 to 1.04 for overall COVID-19; OR: 1.02, 95%CI 0.95 to 1.09 for hospitalized COVID-19; and OR: 1.00, 95%CI 0.93 to 1.08 for severe COVID-19). There were no strong evidence for an association of glycemic traits in COVID-19 phenotypes, apart from a potential inverse association for fasting glucose albeit with wide confidence interval. Conclusion We provide some genetic evidence that poorer glycemic traits and predisposition to type 2 diabetes unlikely increase the risk of COVID-19. Although our study did not indicate glycemic traits increase severity of COVID-19, additional studies are needed to verify our findings.

scholarly journals RFX6-mediated dysregulation defines human β cell dysfunction in early type 2 diabetes

2021 ◽  
Author(s):  
John T Walker ◽  
Diane C Saunders ◽  
Vivek Rai ◽  
Chunhua Dai ◽  
Peter Orchard ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Insulin Secretion ◽  
Association Studies ◽  
Critical Role ◽  
Regulatory Elements ◽  
Genome Wide Association Studies ◽  
Β Cells ◽  
Β Cell ◽  
Gene Regulatory

A hallmark of type 2 diabetes (T2D), a major cause of world-wide morbidity and mortality, is dysfunction of insulin-producing pancreatic islet β cells. T2D genome-wide association studies (GWAS) have identified hundreds of signals, mostly in the non-coding genome and overlapping β cell regulatory elements, but translating these into biological mechanisms has been challenging. To identify early disease-driving events, we performed single cell spatial proteomics, sorted cell transcriptomics, and assessed islet physiology on pancreatic tissue from short-duration T2D and control donors. Here, through integrative analyses of these diverse modalities, we show that multiple gene regulatory modules are associated with early-stage T2D β cell-intrinsic defects. One notable example is the transcription factor RFX6, which we show is a highly connected β cell hub gene that is reduced in T2D and governs a gene regulatory network associated with insulin secretion defects and T2D GWAS variants. We validated the critical role of RFX6 in β cells through direct perturbation in primary human islets followed by physiological and single nucleus multiome profiling, which showed reduced dynamic insulin secretion and large-scale changes in the β cell transcriptome and chromatin accessibility landscape. Understanding the molecular mechanisms of complex, systemic diseases necessitates integration of signals from multiple molecules, cells, organs, and individuals and thus we anticipate this approach will be a useful template to identify and validate key regulatory networks and master hub genes for other diseases or traits with GWAS data.

scholarly journals An Integrative Phenotype–Genotype Approach Using Phenotypic Characteristics from the UAE National Diabetes Study Identifies HSD17B12 as a Candidate Gene for Obesity and Type 2 Diabetes

Genes ◽  
2020 ◽  
Vol 11 (4) ◽  
pp. 461 ◽  
Author(s):  
Mahmood Y. Hachim ◽  
Hayat Aljaibeji ◽  
Rifat A. Hamoudi ◽  
Ibrahim Y. Hachim ◽  
Noha M. Elemam ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Candidate Gene ◽  
United Arab Emirates ◽  
Cell Function ◽  
Association Studies ◽  
Diabetic Patients ◽  
Genome Wide Association Studies ◽  
Phenotypic Characteristics ◽  
Obstructive Sleep

The United Arab Emirates National Diabetes and Lifestyle Study (UAEDIAB) has identified obesity, hypertension, obstructive sleep apnea, and dyslipidemia as common phenotypic characteristics correlated with diabetes mellitus status. As these phenotypes are usually linked with genetic variants, we hypothesized that these phenotypes share single nucleotide polymorphism (SNP)-clusters that can be used to identify causal genes for diabetes. We explored the National Human Genome Research Institute-European Bioinformatics Institute Catalog of Published Genome-Wide Association Studies (NHGRI-EBI GWAS) to list SNPs with documented association with the UAEDIAB-phenotypes as well as diabetes. The shared chromosomal regions affected by SNPs were identified, intersected, and searched for Enriched Ontology Clustering. The potential SNP-clusters were validated using targeted DNA next-generation sequencing (NGS) in two Emirati diabetic patients. RNA sequencing from human pancreatic islets was used to study the expression of identified genes in diabetic and non-diabetic donors. Eight chromosomal regions containing 46 SNPs were identified in at least four out of the five UAEDIAB-phenotypes. A list of 34 genes was shown to be affected by those SNPs. Targeted NGS from two Emirati patients confirmed that the identified genes have similar SNP-clusters. ASAH1, LRP4, FES, and HSD17B12 genes showed the highest SNPs rate among the identified genes. RNA-seq analysis revealed high expression levels of HSD17B12 in human islets and to be upregulated in type 2 diabetes (T2D) donors. Our integrative phenotype-genotype approach is a novel, simple, and powerful tool to identify clinically relevant potential biomarkers in diabetes. HSD17B12 is a novel candidate gene for pancreatic β-cell function.

scholarly journals Monogenic Diabetes in the Young, Pharmacogenetics and Relevance to Multifactorial Forms of Type 2 Diabetes

2008 ◽  
Vol 29 (3) ◽  
pp. 254-264 ◽  
Author(s):  
Martine Vaxillaire ◽  
Philippe Froguel
Keyword(s):  
Type 2 Diabetes ◽  
Glucose Sensor ◽  
Cell Function ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Dominant Form ◽  
Genes Encoding ◽  
Autosomal Dominant Form ◽  
Β Cell Function

Abstract Most valuable breakthroughs in the genetics of type 2 diabetes for the past two decades have arisen from candidate gene studies and familial linkage analysis of maturity-onset diabetes of the young (MODY), an autosomal dominant form of diabetes typically occurring before 25 years of age caused by primary insulin secretion defects. Despite its low prevalence, MODY is not a single entity but presents genetic, metabolic and clinical heterogeneity. MODY can result from mutations in at least six different genes encoding the glucose sensor enzyme glucokinase and transcription factors that participate in a regulatory network essential for adult β-cell function. Additional genes have been described in other discrete phenotypes or syndromic forms of diabetes. Whereas common variants in the MODY genes contribute very modestly to type 2 diabetes susceptibility in adults, major findings emerging from the advent of genome-wide association studies will deliver an increasing number of genes and new pathways for the pathological events of the disease.

Determinants of reversibility of β-cell dysfunction in response to short-term intensive insulin therapy in patients with early type 2 diabetes

2013 ◽  
Vol 305 (11) ◽  
pp. E1398-E1407 ◽  
Author(s):  
Caroline Kaercher Kramer ◽  
Haysook Choi ◽  
Bernard Zinman ◽  
Ravi Retnakaran
Keyword(s):  
Type 2 Diabetes ◽  
Insulin Therapy ◽  
Intensive Insulin Therapy ◽  
Cell Function ◽  
Sensitivity Index ◽  
Β Cell ◽  
Short Term ◽  
Cell Dysfunction ◽  
Β Cell Function

Short-term intensive insulin therapy (IIT) can improve pancreatic β-cell function when administered early in the course of type 2 diabetes mellitus (T2DM). However, the degree of improvement in response to this therapy varies between patients. Thus, we sought to characterize the determinants of improvement in β-cell function in response to short-term IIT in early T2DM. Sixty-three patients with mean 3.0 ± 2.1 yr duration of T2DM and Hb A1c of 6.8 ± 0.8% underwent 4 wk of IIT consisting of basal insulin detemir and premeal insulin aspart, with oral glucose tolerance test administered at baseline and 1 day post-IIT. β-Cell function before and after IIT was assessed by Insulin Secretion Sensitivity Index-2 (ISSI-2). Reversibility of β-cell dysfunction was defined as percentage change in ISSI-2 of ≥25%. Overall, the study population experienced an increase in ISSI-2 from baseline to post-IIT ( P = 0.01), with one-third of participants achieving ≥25% improvement in ISSI-2. Compared with their peers, those with increases in ISSI-2 of ≥25% had greater decrements in fasting glucose ( P < 0.0001), Hb A1c ( P = 0.001), ALT ( P = 0.04), AST ( P = 0.02), and HOMA-IR ( P < 0.0001). On logistical regression analysis, baseline Hb A1c (OR = 2.83, 95% CI 1.16–6.88, P = 0.02) and change in HOMA-IR (OR = 0.008, 95%CI 0.0004–0.16, P = 0.001) emerged as independent predictors of reversibility of β-cell dysfunction. Indeed, reversibility of β-cell dysfunction was achieved in only those participants in whom IIT yielded an improvement in HOMA-IR. In conclusion, decline in HOMA-IR may be a key determinant of improvement of β-cell function in response to short-term IIT, suggesting a fundamental contribution of insulin resistance to the reversible component of β-cell dysfunction in early T2DM.

scholarly journals Causal Evaluation of Laboratory Markers in Type 2 Diabetes on Cancer and Vascular Diseases Using Various Mendelian Randomization Tools

2020 ◽  
Author(s):  
Heejin Jin ◽  
Sanghun Lee ◽  
Sungho Won
Keyword(s):  
Type 2 Diabetes ◽  
Plasma Glucose ◽  
Large Scale ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Density Lipoprotein ◽  
Genome Wide Association Studies ◽  
Postprandial Plasma Glucose ◽  
Weighted Median

Multiple studies have demonstrated the effects of type 2 diabetes (T2D) on various human diseases; however, most of these were observational epidemiological studies that suffered from many potential biases including reported confounding and reverse causations. In this article, we investigated whether cancer and vascular disease can be affected by T2D-related traits, including fasting plasma glucose (FPG), 2-h postprandial plasma glucose (2h-PG), and glycated hemoglobin A1c (HbA1c) levels, by using Mendelian randomization (MR). The summary statistics for FPG, 2h-PG, and HbA1c were obtained through meta-analyses of large-scale genome-wide association studies that included data from 133,010 non-diabetic individuals from collaborating Meta-Analysis of Glucose and Insulin related traits Consortium studies. Thereafter, based on the statistical assumptions for MR analyses, the most reliable approaches including inverse-variance-weighted (IVW), MR-Egger, MR-Egger with a simulation extrapolation (SIMEX), weighted median and MR-Pleiotropy RESidual Sum and Outlier (MR-PRESSO) methods were applied to identify traits affected by FPG, 2h-PG, and HbAlc. We found that coronary artery disease is affected by FPG, as per the IVW [log odds ratio (logOR): 0.21; P=0.012], MR-Egger (SIMEX) (logOR: 0.22; P=0.014), MR-PRESSO (logOR: 0.18; P=0.045), and weighted median (logOR: 0.29; P<0.001) methods, but not as per the MR-Egger (logOR: 0.13; P=0.426) approach. Furthermore, low-density lipoprotein cholesterol levels are affected by HbA1c, as per the IVW (beta (B): 0.23; P=0.015), MR-Egger (B: 0.45; P=0.046), MR-Egger (SIMEX) (B: 0.27; P=0.007), MR-PRESSO (B; 0.14; P=0.010), and the weighted median (B: 0.15; P=0.012) methods. Further studies of the associated biological mechanisms are required to validate and understand the disease-specific differences identified in the TD2-related causal effects of each trait.

scholarly journals The putative causal effect of type 2 diabetes in risk of cataract: a Mendelian randomization study in East Asian

2021 ◽  
Author(s):  
Haoyang Zhang ◽  
Xuehao Xiu ◽  
Angli Xue ◽  
Yuedong Yang ◽  
Yuanhao Yang ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Genetic Correlation ◽  
Mendelian Randomization ◽  
Causal Effect ◽  
Association Studies ◽  
Population Based ◽  
P Value ◽  
Genome Wide Association Studies ◽  
Genome Wide

AbstractBackgroundThe epidemiological association between type 2 diabetes and cataract has been well-established. However, it remains unclear whether the two diseases share a genetic basis, and if so, whether this reflects a causal relationship.MethodsWe utilized East Asian population-based genome-wide association studies (GWAS) summary statistics of type 2 diabetes (Ncase=36,614, Ncontrol=155,150) and cataract (Ncase=24,622, Ncontrol=187,831) to comprehensively investigate the shared genetics between the two diseases. We performed 1. linkage disequilibrium score regression (LDSC) and heritability estimation from summary statistics (ρ-HESS) to estimate the genetic correlation and local genetic correlation between type 2 diabetes and cataract; 2. multiple Mendelian randomization (MR) analyses to infer the putative causality between type 2 diabetes and cataract; and 3. Summary-data-based Mendelian randomization (SMR) to identify candidate risk genes underling the causality.ResultsWe observed a strong genetic correlation (rg=0.58; p-value=5.60×10−6) between type 2 diabetes and cataract. Both ρ-HESS and multiple MR methods consistently showed a putative causal effect of type 2 diabetes on cataract, with estimated liability-scale MR odds ratios (ORs) at around 1.10 (95% confidence interval [CI] ranging from 1.06 to 1.17). In contrast, no evidence supports a causal effect of cataract on type 2 diabetes. SMR analysis identified two novel genes MIR4453HG (βSMR=−0.34, p-value=6.41×10−8) and KCNK17 (βSMR=−0.07, p-value=2.49×10−10), whose expression levels were likely involved in the putative causality of type 2 diabetes on cataract.ConclusionsOur results provided robust evidence supporting a causal effect of type 2 diabetes on the risk of cataract in East Asians, and posed new paths on guiding prevention and early-stage diagnosis of cataract in type 2 diabetes patients.Key MessagesWe utilized genome-wide association studies of type 2 diabetes and cataract in a large Japanese population-based cohort and find a strong genetic overlap underlying the two diseases.We performed multiple Mendelian randomization models and consistently disclosed a putative causal effect of type 2 diabetes on the development of cataract.We revealed two candidate genes MIR4453HG and KCNK17 whose expression levelss are likely relevant to the causality between type 2 diabetes and cataract.Our study provided theoretical fundament at the genetic level for improving early diagnosis, prevention and treatment of cataract in type 2 diabetes patients in clinical practice

scholarly journals Type 2 Diabetes, Metabolic Traits, and Risk of Heart Failure: A Mendelian Randomization Study

2021 ◽  
Author(s):  
Ify R Mordi ◽  
R Thomas Lumbers ◽  
Colin NA Palmer ◽  
Ewan R Pearson ◽  
Naveed Sattar ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Glycated Haemoglobin ◽  
Sensitivity Analyses ◽  
Genome Wide Association Studies ◽  
Fasting Insulin ◽  
Genetic Liability ◽  
Level Data

<b>Objective</b> <p>The aim of this study was to use Mendelian randomization (MR) techniques to estimate the causal relationships between genetic liability to type 2 diabetes, glycaemic traits and risk of HF.</p> <p><b>Research Design and Methods</b></p> <p>Summary-level data were obtained from genome-wide association studies (GWAS) of type 2 diabetes, insulin resistance (IR), glycated haemoglobin, fasting insulin and glucose and HF. MR was conducted using the inverse variance weighted (IVW) method. Sensitivity analyses included MR-Egger, weighted median and mode methods, and multivariable MR conditioning on potential mediators.</p> <p><b>Results</b></p> <p>Genetic liability to type 2 diabetes was causally related to higher risk of HF (OR: 1.13 per 1 log-unit higher risk of type 2 diabetes; 95% CI 1.11-1.14, p<0.001), however sensitivity analysis revealed evidence of directional pleiotropy. The relationship between type 2 diabetes and HF was attenuated when adjusted for coronary disease, body mass index, LDL-cholesterol and blood pressure. Genetically-instrumented higher IR was associated with higher risk of HF (OR 1.19 per 1 log-unit higher risk of IR; 95% CI 1.00-1.41, p=0.041). There were no notable associations identified between fasting insulin, glucose or glycated haemoglobin and risk of HF. Genetic liability to HF was causally linked to higher risk of type 2 diabetes (OR 1.49; 95% CI 1.01-2.19, p=0.042) though again with evidence of pleiotropy.</p> <p><b>Conclusions</b></p> These findings suggest a causal role of type 2 diabetes and IR in HF aetiology, though both the presence of bidirectional effects and directional pleiotropy highlight potential sources of bias that need to be considered.

scholarly journals Mendelian randomization studies of biomarkers and type 2 diabetes

2015 ◽  
Vol 4 (4) ◽  
pp. 249-260 ◽  
Author(s):  
Ali Abbasi
Keyword(s):  
Type 2 Diabetes ◽  
Genetic Variants ◽  
Large Scale ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Causal Effects ◽  
Current Evidence ◽  
Genome Wide Association Studies ◽  
Glycaemic Traits

Many biomarkers are associated with type 2 diabetes (T2D) risk in epidemiological observations. The aim of this study was to identify and summarize current evidence for causal effects of biomarkers on T2D. A systematic literature search in PubMed and EMBASE (until April 2015) was done to identify Mendelian randomization studies that examined potential causal effects of biomarkers on T2D. To replicate the findings of identified studies, data from two large-scale, genome-wide association studies (GWAS) were used: DIAbetes Genetics Replication And Meta-analysis (DIAGRAMv3) for T2D and the Meta-Analyses of Glucose and Insulin-related traits Consortium (MAGIC) for glycaemic traits. GWAS summary statistics were extracted for the same genetic variants (or proxy variants), which were used in the original Mendelian randomization studies. Of the 21 biomarkers (from 28 studies), ten have been reported to be causally associated with T2D in Mendelian randomization. Most biomarkers were investigated in a single cohort study or population. Of the ten biomarkers that were identified, nominally significant associations with T2D or glycaemic traits were reached for those genetic variants related to bilirubin, pro-B-type natriuretic peptide, delta-6 desaturase and dimethylglycine based on the summary data from DIAGRAMv3 or MAGIC. Several Mendelian randomization studies investigated the nature of associations of biomarkers with T2D. However, there were only a few biomarkers that may have causal effects on T2D. Further research is needed to broadly evaluate the causal effects of multiple biomarkers on T2D and glycaemic traits using data from large-scale cohorts or GWAS including many different genetic variants.

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