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1.
  • Ademuyiwa, Adesoji O., et al. (author)
  • Determinants of morbidity and mortality following emergency abdominal surgery in children in low-income and middle-income countries
  • 2016
  • In: BMJ Global Health. - : BMJ Publishing Group Ltd. - 2059-7908. ; 1:4
  • Journal article (peer-reviewed)abstract
    • Background: Child health is a key priority on the global health agenda, yet the provision of essential and emergency surgery in children is patchy in resource-poor regions. This study was aimed to determine the mortality risk for emergency abdominal paediatric surgery in low-income countries globally.Methods: Multicentre, international, prospective, cohort study. Self-selected surgical units performing emergency abdominal surgery submitted prespecified data for consecutive children aged <16 years during a 2-week period between July and December 2014. The United Nation's Human Development Index (HDI) was used to stratify countries. The main outcome measure was 30-day postoperative mortality, analysed by multilevel logistic regression.Results: This study included 1409 patients from 253 centres in 43 countries; 282 children were under 2 years of age. Among them, 265 (18.8%) were from low-HDI, 450 (31.9%) from middle-HDI and 694 (49.3%) from high-HDI countries. The most common operations performed were appendectomy, small bowel resection, pyloromyotomy and correction of intussusception. After adjustment for patient and hospital risk factors, child mortality at 30 days was significantly higher in low-HDI (adjusted OR 7.14 (95% CI 2.52 to 20.23), p<0.001) and middle-HDI (4.42 (1.44 to 13.56), p=0.009) countries compared with high-HDI countries, translating to 40 excess deaths per 1000 procedures performed.Conclusions: Adjusted mortality in children following emergency abdominal surgery may be as high as 7 times greater in low-HDI and middle-HDI countries compared with high-HDI countries. Effective provision of emergency essential surgery should be a key priority for global child health agendas.
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2.
  • Ahlqvist, Emma, et al. (author)
  • Novel subgroups of adult-onset diabetes and their association with outcomes : a data-driven cluster analysis of six variables
  • 2018
  • In: The Lancet Diabetes and Endocrinology. - 2213-8587 .- 2213-8595. ; 6:5, s. 361-369
  • Journal article (peer-reviewed)abstract
    •  BackgroundDiabetes is presently classified into two main forms, type 1 and type 2 diabetes, but type 2 diabetes in particular is highly heterogeneous. A refined classification could provide a powerful tool to individualise treatment regimens and identify individuals with increased risk of complications at diagnosis.MethodsWe did data-driven cluster analysis (k-means and hierarchical clustering) in patients with newly diagnosed diabetes (n=8980) from the Swedish All New Diabetics in Scania cohort. Clusters were based on six variables (glutamate decarboxylase antibodies, age at diagnosis, BMI, HbA1c, and homoeostatic model assessment 2 estimates of β-cell function and insulin resistance), and were related to prospective data from patient records on development of complications and prescription of medication. Replication was done in three independent cohorts: the Scania Diabetes Registry (n=1466), All New Diabetics in Uppsala (n=844), and Diabetes Registry Vaasa (n=3485). Cox regression and logistic regression were used to compare time to medication, time to reaching the treatment goal, and risk of diabetic complications and genetic associations.FindingsWe identified five replicable clusters of patients with diabetes, which had significantly different patient characteristics and risk of diabetic complications. In particular, individuals in cluster 3 (most resistant to insulin) had significantly higher risk of diabetic kidney disease than individuals in clusters 4 and 5, but had been prescribed similar diabetes treatment. Cluster 2 (insulin deficient) had the highest risk of retinopathy. In support of the clustering, genetic associations in the clusters differed from those seen in traditional type 2 diabetes.InterpretationWe stratified patients into five subgroups with differing disease progression and risk of diabetic complications. This new substratification might eventually help to tailor and target early treatment to patients who would benefit most, thereby representing a first step towards precision medicine in diabetes.
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3.
  • Asplund, Olof, et al. (author)
  • Islet Gene View-a tool to facilitate islet research
  • 2022
  • In: Life Science Alliance. - : Life Science Alliance, LLC. - 2575-1077. ; 5:12
  • Journal article (peer-reviewed)abstract
    • Characterization of gene expression in pancreatic islets and its alteration in type 2 diabetes (T2D) are vital in understanding islet function and T2D pathogenesis. We leveraged RNA sequencing and genome-wide genotyping in islets from 188 donors to create the Islet Gene View (IGW) platform to make this information easily accessible to the scientific community. Expression data were related to islet phenotypes, diabetes status, other islet-expressed genes, islet hormone-encoding genes and for expression in insulin target tissues. The IGW web application produces output graphs for a particular gene of interest. In IGW, 284 differentially expressed genes (DEGs) were identified in T2D donor islets compared with controls. Forty percent of DEGs showed cell-type enrichment and a large proportion significantly co-expressed with islet hormone-encoding genes; glucagon (GCG, 56%), amylin (IAPP, 52%), insulin (INS, 44%), and somatostatin (SST, 24%). Inhibition of two DEGs, UNC5D and SERPINE2, impaired glucose-stimulated insulin secretion and impacted cell survival in a human beta-cell model. The exploratory use of IGW could help designing more comprehensive functional follow-up studies and serve to identify therapeutic targets in T2D.
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4.
  • Bennet, Louise, et al. (author)
  • Adult-onset diabetes in Middle Eastern immigrants to Sweden : Novel subgroups and diabetic complications—The All New Diabetes in Scania cohort diabetic complications and ethnicity
  • 2021
  • In: Diabetes/Metabolism Research and Reviews. - : Wiley. - 1520-7552 .- 1520-7560. ; 37:6
  • Journal article (peer-reviewed)abstract
    • Background: Middle Eastern immigrants to Europe represent a high risk population for type 2 diabetes. We compared prevalence of novel subgroups and assessed risk of diabetic macro- and microvascular complications between diabetes patients of Middle Eastern and European origin. Methods: This study included newly diagnosed diabetes patients born in Sweden (N = 10641) or Iraq (N = 286), previously included in the All New Diabetes in Scania cohort. The study was conducted between January 2008 and August 2016. Patients were followed to April 2017. Incidence rates in diabetic macro- and microvascular complications were assessed using cox-regression adjusting for the confounding effect of age at onset, sex, anthropometrics, glomerular filtration rate (eGFR) and HbA1c. Findings: In Iraqi immigrants versus native Swedes, severe insulin-deficient diabetes was almost twice as common (27.9 vs. 16.2% p < 0.001) but severe insulin-resistant diabetes was less prevalent. Patients born in Iraq had higher risk of coronary events (hazard ratio [HR] 1.84, 95% CI 1.06–3.12) but considerably lower risk of chronic kidney disease (CKD) than Swedes (HR 0.19; 0.05–0.76). The lower risk in Iraqi immigrants was partially attributed to better eGFR. Genetic risk scores (GRS) showed more genetic variants associated with poor insulin secretion but lower risk of insulin resistance in the Iraqi than native Swedish group. Interpretation: People with diabetes, born in the Middle East present with a more insulin-deficient phenotype and genotype than native Swedes. They have a higher risk of coronary events but lower risk of CKD. Ethnic differences should be considered in the preventive work towards diabetes and its complications.
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5.
  • Breitfeld, Jana, et al. (author)
  • Genetic dissection of serum vaspin highlights its causal role in lipid metabolism
  • 2023
  • In: Obesity. - 1930-7381. ; 31:11, s. 2862-2874
  • Journal article (peer-reviewed)abstract
    • Objective: Vaspin (visceral adipose tissue derived serine protease inhibitor, SERPINA12) is associated with obesity-related metabolic traits, but its causative role is still elusive. The role of genetics in serum vaspin variability to establish its causal relationship with metabolically relevant traits was investigated. Methods: A meta-analysis of genome-wide association studies for serum vaspin from six independent cohorts (N = 7446) was conducted. Potential functional variants of vaspin were included in Mendelian randomization (MR) analyses to assess possible causal pathways between vaspin and homeostasis model assessment and lipid traits. To further validate the MR analyses, data from Genotype-Tissue Expression (GTEx) were analyzed, db/db mice were treated with vaspin, and serum lipids were measured. Results: A total of 468 genetic variants represented by five independent variants (rs7141073, rs1956709, rs4905216, rs61978267, rs73338689) within the vaspin locus were associated with serum vaspin (all p < 5×10−8, explained variance 16.8%). MR analyses revealed causal relationships between serum vaspin and triglycerides, low-density lipoprotein, and total cholesterol. Gene expression correlation analyses suggested that genes, highly correlated with vaspin expression in adipose tissue, are enriched in lipid metabolic processes. Finally, in vivo vaspin treatment reduced serum triglycerides in obese db/db mice. Conclusions: The data show that serum vaspin is strongly determined by genetic variants within vaspin, which further highlight vaspin's causal role in lipid metabolism.
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6.
  • Edstorp, Jessica, et al. (author)
  • Incidence of lada and type 2 diabetes in relation to tobacco use and genetic susceptibility to type 2 diabetes and related traits : Findings from a swedish case-control study and the norwegian hunt study
  • 2023
  • In: Diabetes Care. - : American Diabetes Association. - 0149-5992 .- 1935-5548. ; 46:5, s. 1028-1036
  • Journal article (peer-reviewed)abstract
    • OBJECTIVE Smoking and Swedish smokeless tobacco (snus) are associated with latent autoimmune diabetes in adults (LADA) and type 2 diabetes (T2D). Our aim was to investigate whether genetic susceptibility to T2D, insulin resistance (IR), and insulin secretion (IS) aggravate these associations. RESEARCH DESIGN AND METHODS We used data from two population-based Scandinavian studies with case subjects with LADA (n = 839) and T2D (n = 5,771), matched control subjects (n = 3,068), and 1,696,503 person-years at risk. Pooled, multivariate relative risks (RR) with 95% CI were estimated for smoking/genetic risk scores (T2D-GRS, IS-GRS, and IR-GRS), and ORs for snus or tobacco/GRS (case-control data). We estimated additive (proportion attributable to interaction [AP]) and multiplicative interaction between tobacco use and GRS. RESULTS The RR of LADA was elevated in high IR-GRS heavy smokers (‡15 pack-years; RR 2.01 [CI 1.30, 3.10]) and tobacco users (‡15 box/pack-years; RR 2.59 [CI 1.54, 4.35]) compared with low IR-GRS individuals without heavy use, with evidence of additive (AP 0.67 [CI 0.46, 0.89]; AP 0.52 [CI 0.21, 0.83]) and multiplicative (P = 0.003; P = 0.034) interaction. In heavy users, there was additive interaction between T2D-GRS and smoking, snus, and total tobacco use. The excess risk conferred by tobacco use did not differ across GRS categories in T2D. CONCLUSIONS Tobacco use may confer a higher risk of LADA in individuals with genetic susceptibility to T2D and insulin resistance, whereas genetic susceptibility does not seem to influence the increased T2D incidence associated with tobacco use.
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7.
  • Mansour Aly, Dina (author)
  • Genetics of Diabetes Subtypes. Characterization of novel cluster-based diabetes subtypes.
  • 2022
  • Doctoral thesis (other academic/artistic)abstract
    • BACKGROUND: Type 2 diabetes (T2D) has been reproducibly clustered into five subtypes based on six-clinical variables; age at diabetes onset, body mass index (BMI), Glutamic acid decarboxylase autoantibodies (GADA), glycated hemoglobin (HbA1c) and insulin secretion and resistance estimated as HOMA2B and HOMA2IR derived from fasting glucose and Cpeptide. These subtypes have different disease progression and risk of complications. The newly defined subtypes are called Severe Autoimmune Diabetes (SAID), Severe Insulin Deficient Diabetes (SIDD), Severe InsulinResistant Diabetes (SIRD), Mild Obesity-related Diabetes (MOD), and Mild Age-Related Diabetes (MARD). AIM: The main aim of the thesis was to characterize the subtypes using genetics and biomarkers to investigate potential etiological differences, identify subtype-specific genetic associations and determine the underlying mechanisms of kidney complications in the subtypes.METHODS: The project included individuals with diabetes (cases) from the Swedish cohort All New Diabetics In Scania (ANDIS, n=10927) and the Finnish cohort Diabetes Registry Vasa (DIREVA, n=4754) as well as diabetes-free individuals (controls) from the Swedish Malmö Diet and Cancer cohort (MDC,n=2744) and the Finnish Botnia cohort (n=1683). Clusters defined in Ahlqvist et al, 2018, were used for all analyses. The number of individuals in the subtypes were as follows: SAID (n=452, n=327), SIDD (n=1193, n=394), SIRD (n=1130, n=453), MOD (n=1374, n=596) and MARD (n=2861, n=1178), in ANDIS and DIREVA respectively. In Paper I and III, genome-wide association studies (GWAS) and genetic risk score (GRS) analyses were performed to compare underlying genetic drivers in the Swedish cohorts and replicated in the Finnish cohorts. In Paper III, the primary phenotype was estimated glomerular filtration rate (eGRF) reflecting chronic kidney disease. In Paper II, epidemiological and genetic analysis was performed using clustering, Cox regression models and GRS to compare GADA negative individuals with diabetes of Iraqi (n=286) and Swedish origin (n=10641) with respect to new diabetes subclassification and complications. In Paper IV, the proteomic profiles of the subtypes were studied using 1161 biomarkers measured on Olink panels. Machine learning algorithms were applied to prioritize biomarkers, followed by Menedelian Randomization. RESULTS: In Paper I, the HLA rs9273368 variant was significantly associated with SAID (OR=2.89,P=6.5x10-40), the TCF7L2 rs7903146 variant was significantly associated with SIDD (OR=1.56, P=8.6x10-15), MOD (OR=1.40, P=3.1x10-10) and MARD (OR=1.42,P=6.1x10-16). The rs10824307 variant near the LRMDA gene was uniquely associated with MOD (OR=1.35, P=1.3×10-09). GRS for fasting insulin showed a unique association with SIRD (OR=1.855, P=5.91x10-09). GRSs for BMI were associated with SIDD, SIRD and MOD but not MARD (OR=1.046, P=0.099). Paper II concluded thar individuals with diabetes from Iraq present with a more insulin-deficient subtype than native Swedes. They have a higher risk of coronary events but a lower risk of CKD. In Paper III, in ANDIS, eGFR was strongly associated with the A allele of rs77924615 in the well-established PDILT-UMOD locus (beta=0.126, p=6.61x10-13) in all T2D; MARD and SIDD but not in MOD or SIRD (p>0.05). In the SIRD subtype, eGFR was associated with the C allele of rs3770382 in the CTNNA2 gene at near genomewide significance (beta=-0.219, p=5.5x10- 08), but was not associated in any of the other subtypes. In DIREVA, the PDILTUMOD locus replicated in T2D, MARD, and SIDD, and was also associated in SIRD (beta=0.24, p=0.001) but not in MOD (beta=0.076, p=0.109). The CTNNA2 locus did not replicate in DIREVA. Paper IV, the diabetes subtypes were shown to have different proteomic profiles and a list of prioritized biomarkers was generated for future follow-up. CONCLUSION: The newly defined subtypes are partially distinct with genetically different backgrounds and SIRD is suggested to have more beta-cell independent pathogenesis. There is some suggestive support for different genetic backgrounds of DKD in diabetes subtypes. Biomarkers could be valuable for better discrimination of subtypes and cross cohort comparisons in larger datasets. The diabetes subclassification approach paves the way for individualized patient management and the development of new therapeutic targets.
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8.
  • Mansour Aly, Dina, et al. (author)
  • Genome-wide association analyses highlight etiological differences underlying newly defined subtypes of diabetes
  • 2021
  • In: Nature Genetics. - : Springer Science and Business Media LLC. - 1546-1718 .- 1061-4036. ; 53, s. 1534-1542
  • Journal article (peer-reviewed)abstract
    • Type 2 diabetes has been reproducibly clustered into five subtypes with different disease progression and risk of complications; however, etiological differences are unknown. We used genome-wide association and genetic risk score (GRS) analysis to compare the underlying genetic drivers. Individuals from the Swedish ANDIS (All New Diabetics In Scania) study were compared to individuals without diabetes; the Finnish DIREVA (Diabetes register in Vasa) and Botnia studies were used for replication. We show that subtypes differ with regard to family history of diabetes and association with GRS for diabetes-related traits. The severe insulin-resistant subtype was uniquely associated with GRS for fasting insulin but not with variants in the TCF7L2 locus or GRS reflecting insulin secretion. Further, an SNP (rs10824307) near LRMDA was uniquely associated with mild obesity-related diabetes. Therefore, we conclude that the subtypes have partially distinct genetic backgrounds indicating etiological differences.
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9.
  • Simonsen, Johan R, et al. (author)
  • Genetic factors affect the susceptibility to bacterial infections in diabetes
  • 2021
  • In: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 11
  • Journal article (peer-reviewed)abstract
    • Diabetes increases the risk of bacterial infections. We investigated whether common genetic variants associate with infection susceptibility in Finnish diabetic individuals. We performed genome-wide association studies and pathway analysis for bacterial infection frequency in Finnish adult diabetic individuals (FinnDiane Study; N = 5092, Diabetes Registry Vaasa; N = 4247) using national register data on antibiotic prescription purchases. Replication analyses were performed in a Swedish diabetic population (ANDIS; N = 9602) and in a Finnish non-diabetic population (FinnGen; N = 159,166). Genome-wide data indicated moderate but significant narrow-sense heritability for infection susceptibility (h2 = 16%, P = 0.02). Variants on chromosome 2 were associated with reduced infection susceptibility (rs62192851, P = 2.23 × 10-7). Homozygotic carriers of the rs62192851 effect allele (N = 44) had a 37% lower median annual antibiotic purchase rate, compared to homozygotic carriers of the reference allele (N = 4231): 0.38 [IQR 0.22-0.90] and 0.60 [0.30-1.20] respectively, P = 0.01). Variants rs6727834 and rs10188087, in linkage disequilibrium with rs62192851, replicated in the FinnGen-cohort (P < 0.05), but no variants replicated in the ANDIS-cohort. Pathway analysis suggested the IRAK1 mediated NF-κB activation through IKK complex recruitment-pathway to be a mediator of the phenotype. Common genetic variants on chromosome 2 may associate with reduced risk of bacterial infections in Finnish individuals with diabetes.
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10.
  • Slieker, Roderick C, et al. (author)
  • Distinct Molecular Signatures of Clinical Clusters in People with Type 2 Diabetes : an IMIRHAPSODY Study
  • 2021
  • In: Diabetes. - : American Diabetes Association. - 1939-327X .- 0012-1797. ; 70:11, s. 2683-2693
  • Journal article (peer-reviewed)abstract
    • Type 2 diabetes is a multifactorial disease with multiple underlying aetiologies. To address this heterogeneity a previous study clustered people with diabetes into five diabetes subtypes. The aim of the current study is to investigate the aetiology of these clusters by comparing their molecular signatures. In three independent cohorts, in total 15,940 individuals were clustered based on five clinical characteristics. In a subset, genetic- (N=12828), metabolomic- (N=2945), lipidomic- (N=2593) and proteomic (N=1170) data were obtained in plasma. In each datatype each cluster was compared with the other four clusters as the reference. The insulin resistant cluster showed the most distinct molecular signature, with higher BCAAs, DAG and TAG levels and aberrant protein levels in plasma enriched for proteins in the intracellular PI3K/Akt pathway. The obese cluster showed higher cytokines. A subset of the mild diabetes cluster with high HDL showed the most beneficial molecular profile with opposite effects to those seen in the insulin resistant cluster. This study showed that clustering people with type 2 diabetes can identify underlying molecular mechanisms related to pancreatic islets, liver, and adipose tissue metabolism. This provides novel biological insights into the diverse aetiological processes that would not be evident when type 2 diabetes is viewed as a homogeneous disease.
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11.
  • Slieker, Roderick C, et al. (author)
  • Identification of biomarkers for glycaemic deterioration in type 2 diabetes
  • 2023
  • In: Nature Communications. - 2041-1723. ; 14, s. 1-18
  • Journal article (peer-reviewed)abstract
    • We identify biomarkers for disease progression in three type 2 diabetes cohorts encompassing 2,973 individuals across three molecular classes, metabolites, lipids and proteins. Homocitrulline, isoleucine and 2-aminoadipic acid, eight triacylglycerol species, and lowered sphingomyelin 42:2;2 levels are predictive of faster progression towards insulin requirement. Of ~1,300 proteins examined in two cohorts, levels of GDF15/MIC-1, IL-18Ra, CRELD1, NogoR, FAS, and ENPP7 are associated with faster progression, whilst SMAC/DIABLO, SPOCK1 and HEMK2 predict lower progression rates. In an external replication, proteins and lipids are associated with diabetes incidence and prevalence. NogoR/RTN4R injection improved glucose tolerance in high fat-fed male mice but impaired it in male db/db mice. High NogoR levels led to islet cell apoptosis, and IL-18R antagonised inflammatory IL-18 signalling towards nuclear factor kappa-B in vitro. This comprehensive, multi-disciplinary approach thus identifies biomarkers with potential prognostic utility, provides evidence for possible disease mechanisms, and identifies potential therapeutic avenues to slow diabetes progression.
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12.
  • Slieker, Roderick C, et al. (author)
  • Replication and cross-validation of type 2 diabetes subtypes based on clinical variables : an IMI-RHAPSODY study
  • 2021
  • In: Diabetologia. - : Springer Science and Business Media LLC. - 0012-186X .- 1432-0428. ; 64:9, s. 1982-1989
  • Journal article (peer-reviewed)abstract
    • Aims/hypothesis: Five clusters based on clinical characteristics have been suggested as diabetes subtypes: one autoimmune and four subtypes of type 2 diabetes. In the current study we replicate and cross-validate these type 2 diabetes clusters in three large cohorts using variables readily measured in the clinic. Methods: In three independent cohorts, in total 15,940 individuals were clustered based on age, BMI, HbA1c, random or fasting C-peptide, and HDL-cholesterol. Clusters were cross-validated against the original clusters based on HOMA measures. In addition, between cohorts, clusters were cross-validated by re-assigning people based on each cohort’s cluster centres. Finally, we compared the time to insulin requirement for each cluster. Results: Five distinct type 2 diabetes clusters were identified and mapped back to the original four All New Diabetics in Scania (ANDIS) clusters. Using C-peptide and HDL-cholesterol instead of HOMA2-B and HOMA2-IR, three of the clusters mapped with high sensitivity (80.6–90.7%) to the previously identified severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD) and mild obesity-related diabetes (MOD) clusters. The previously described ANDIS mild age-related diabetes (MARD) cluster could be mapped to the two milder groups in our study: one characterised by high HDL-cholesterol (mild diabetes with high HDL-cholesterol [MDH] cluster), and the other not having any extreme characteristic (mild diabetes [MD]). When these two milder groups were combined, they mapped well to the previously labelled MARD cluster (sensitivity 79.1%). In the cross-validation between cohorts, particularly the SIDD and MDH clusters cross-validated well, with sensitivities ranging from 73.3% to 97.1%. SIRD and MD showed a lower sensitivity, ranging from 36.1% to 92.3%, where individuals shifted from SIRD to MD and vice versa. People belonging to the SIDD cluster showed the fastest progression towards insulin requirement, while the MDH cluster showed the slowest progression. Conclusions/interpretation: Clusters based on C-peptide instead of HOMA2 measures resemble those based on HOMA2 measures, especially for SIDD, SIRD and MOD. By adding HDL-cholesterol, the MARD cluster based upon HOMA2 measures resulted in the current clustering into two clusters, with one cluster having high HDL levels. Cross-validation between cohorts showed generally a good resemblance between cohorts. Together, our results show that the clustering based on clinical variables readily measured in the clinic (age, HbA1c, HDL-cholesterol, BMI and C-peptide) results in informative clusters that are representative of the original ANDIS clusters and stable across cohorts. Adding HDL-cholesterol to the clustering resulted in the identification of a cluster with very slow glycaemic deterioration. Graphical abstract: [Figure not available: see fulltext.]
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13.
  • Strausz, Satu, et al. (author)
  • Genetic analysis of obstructive sleep apnoea discovers a strong association with cardiometabolic health
  • 2021
  • In: European Respiratory Journal. - : European Respiratory Society (ERS). - 0903-1936 .- 1399-3003. ; 57:5, s. 1-17
  • Journal article (peer-reviewed)abstract
    • There is currently limited understanding of the genetic aetiology of obstructive sleep apnoea (OSA). We aimed to identify genetic loci associated with OSA risk, and to test if OSA and its comorbidities share a common genetic background. We conducted the first large-scale genome-wide association study of OSA using the FinnGen study (217 955 individuals) with 16 761 OSA patients identified using nationwide health registries. We estimated 0.08 (95% CI 0.06.0.11) heritability and identified five loci associated with OSA (p<5.0×10-8): rs4837016 near GAPVD1 (GTPase activating protein and VPS9 domains 1), rs10928560 near CXCR4 (C-X-C motif chemokine receptor type 4), rs185932673 near CAMK1D (calcium/calmodulindependent protein kinase ID) and rs9937053 near FTO (fat mass and obesity-associated protein; a variant previously associated with body mass index (BMI)). In a BMI-adjusted analysis, an association was observed for rs10507084 near RMST/NEDD1 (rhabdomyosarcoma 2 associated transcript/NEDD1 γ-tubulin ring complex targeting factor). We found high genetic correlations between OSA and BMI (rg=0.72 (95% CI 0.62-0.83)), and with comorbidities including hypertension, type 2 diabetes, coronary heart disease, stroke, depression, hypothyroidism, asthma and inflammatory rheumatic disease (rg>0.30). The polygenic risk score for BMI showed 1.98-fold increased OSA risk between the highest and the lowest quintile, and Mendelian randomisation supported a causal relationship between BMI and OSA. Our findings support the causal link between obesity and OSA, and the joint genetic basis between OSA and comorbidities.
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14.
  • Wu, Chuanyan, et al. (author)
  • Elevated circulating follistatin associates with an increased risk of type 2 diabetes
  • 2021
  • In: Nature Communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 12, s. 1-10
  • Journal article (peer-reviewed)abstract
    • The hepatokine follistatin is elevated in patients with type 2 diabetes (T2D) and promotes hyperglycemia in mice. Here we explore the relationship of plasma follistatin levels with incident T2D and mechanisms involved. Adjusted hazard ratio (HR) per standard deviation (SD) increase in follistatin levels for T2D is 1.24 (CI: 1.04-1.47, p < 0.05) during 19-year follow-up (n = 4060, Sweden); and 1.31 (CI: 1.09-1.58, p < 0.01) during 4-year follow-up (n = 883, Finland). High circulating follistatin associates with adipose tissue insulin resistance and non-alcoholic fatty liver disease (n = 210, Germany). In human adipocytes, follistatin dose-dependently increases free fatty acid release. In genome-wide association study (GWAS), variation in the glucokinase regulatory protein gene (GCKR) associates with plasma follistatin levels (n = 4239, Sweden; n = 885, UK, Italy and Sweden) and GCKR regulates follistatin secretion in hepatocytes in vitro. Our findings suggest that GCKR regulates follistatin secretion and that elevated circulating follistatin associates with an increased risk of T2D by inducing adipose tissue insulin resistance.
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15.
  • Zhao, Yelin, et al. (author)
  • Transcript and protein signatures derived from shared molecular interactions across cancers are associated with mortality
  • 2024
  • In: Journal of Translational Medicine. - : BMC. - 1479-5876. ; 22:1
  • Journal article (peer-reviewed)abstract
    • Background Characterization of shared cancer mechanisms have been proposed to improve therapy strategies and prognosis. Here, we aimed to identify shared cell-cell interactions (CCIs) within the tumor microenvironment across multiple solid cancers and assess their association with cancer mortality.Methods CCIs of each cancer were identified by NicheNet analysis of single-cell RNA sequencing data from breast, colon, liver, lung, and ovarian cancers. These CCIs were used to construct a shared multi-cellular tumor model (shared-MCTM) representing common CCIs across cancers. A gene signature was identified from the shared-MCTM and tested on the mRNA and protein level in two large independent cohorts: The Cancer Genome Atlas (TCGA, 9185 tumor samples and 727 controls across 22 cancers) and UK biobank (UKBB, 10,384 cancer patients and 5063 controls with proteomics data across 17 cancers). Cox proportional hazards models were used to evaluate the association of the signature with 10-year all-cause mortality, including sex-specific analysis.Results A shared-MCTM was derived from five individual cancers. A shared gene signature was extracted from this shared-MCTM and the most prominent regulatory cell type, matrix cancer-associated fibroblast (mCAF). The signature exhibited significant expression changes in multiple cancers compared to controls at both mRNA and protein levels in two independent cohorts. Importantly, it was significantly associated with mortality in cancer patients in both cohorts. The highest hazard ratios were observed for brain cancer in TCGA (HR [95%CI] = 6.90[4.64-10.25]) and ovarian cancer in UKBB (5.53[2.08-8.80]). Sex-specific analysis revealed distinct risks, with a higher mortality risk associated with the protein signature score in males (2.41[1.97-2.96]) compared to females (1.84[1.44-2.37]).Conclusion We identified a gene signature from a comprehensive shared-MCTM representing common CCIs across different cancers and revealed the regulatory role of mCAF in the tumor microenvironment. The pathogenic relevance of the gene signature was supported by differential expression and association with mortality on both mRNA and protein levels in two independent cohorts.
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