ORCID Profile
0000-0003-0672-554X
Current Organisations
University of Helsinki
,
Folkhälsan Research Center
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Publisher: American Diabetes Association
Date: 12-01-2022
DOI: 10.2337/DC21-0974
Abstract: In iduals with type 1 diabetes are at a high lifetime risk of coronary artery disease (CAD), calling for early interventions. This study explores the use of a genetic risk score (GRS) for CAD risk prediction, compares it to established clinical markers, and investigates its performance according to the age and pharmacological treatment. This study in 3,295 in iduals with type 1 diabetes from the Finnish Diabetic Nephropathy Study (467 incident CAD, 14.8 years follow-up) used three risk scores: a GRS, a validated clinical score, and their combined score. Hazard ratios (HR) were calculated with Cox regression, and model performances were compared with the Harrell C-index (C-index). A HR of 6.7 for CAD was observed between the highest and the lowest 5th percentile of the GRS (P = 1.8 × 10−6). The performance of GRS (C-index = 0.562) was similar to HbA1c (C-index = 0.563, P = 0.96 for difference), HDL (C-index = 0.571, P = 0.6), and total cholesterol (C-index = 0.594, P = 0.1). The GRS was not correlated with the clinical score (r = −0.013, P = 0.5). The combined score outperformed the clinical score (C-index = 0.813 vs. C-index = 0.820, P = 0.003). The GRS performed better in in iduals below the median age (38.6 years) compared with those above (C-index = 0.637 vs. C-index = 0.546). A GRS identified in iduals at high risk of CAD and worked better in younger in iduals. GRS was also an independent risk factor for CAD, with a predictive power comparable to that of HbA1c and HDL and total cholesterol, and when incorporated into a clinical model, modestly improved the predictions. The GRS promises early risk stratification in clinical practice by enhancing the prediction of CAD.
Publisher: Ovid Technologies (Wolters Kluwer Health)
Date: 19-09-2019
Abstract: Although studies show that diabetic kidney disease has a heritable component, searches for the genetic determinants of this complication of diabetes have had limited success. In this study, a new international genomics consortium, the JDRF funded Diabetic Nephropathy Collaborative Research Initiative, assembled nearly 20,000 s les from participants with type 1 diabetes, with and without kidney disease. The authors found 16 new diabetic kidney disease–associated loci at genome-wide significance. The strongest signal centers on a protective missense coding variant at COL4A3 , a gene that encodes a component of the glomerular basement membrane that, when mutated, causes the progressive inherited nephropathy Alport syndrome. These GWAS-identified risk loci may provide insights into the pathogenesis of diabetic kidney disease and help identify potential biologic targets for prevention and treatment. Although diabetic kidney disease demonstrates both familial clustering and single nucleotide polymorphism heritability, the specific genetic factors influencing risk remain largely unknown. To identify genetic variants predisposing to diabetic kidney disease, we performed genome-wide association study (GWAS) analyses. Through collaboration with the Diabetes Nephropathy Collaborative Research Initiative, we assembled a large collection of type 1 diabetes cohorts with harmonized diabetic kidney disease phenotypes. We used a spectrum of ten diabetic kidney disease definitions based on albuminuria and renal function. Our GWAS meta-analysis included association results for up to 19,406 in iduals of European descent with type 1 diabetes. We identified 16 genome-wide significant risk loci. The variant with the strongest association (rs55703767) is a common missense mutation in the collagen type IV alpha 3 chain ( COL4A3) gene, which encodes a major structural component of the glomerular basement membrane (GBM). Mutations in COL4A3 are implicated in heritable nephropathies, including the progressive inherited nephropathy Alport syndrome. The rs55703767 minor allele (Asp326Tyr) is protective against several definitions of diabetic kidney disease, including albuminuria and ESKD, and demonstrated a significant association with GBM width protective allele carriers had thinner GBM before any signs of kidney disease, and its effect was dependent on glycemia. Three other loci are in or near genes with known or suggestive involvement in this condition ( BMP7) or renal biology ( COLEC11 and DDR1 ). The 16 diabetic kidney disease–associated loci may provide novel insights into the pathogenesis of this condition and help identify potential biologic targets for prevention and treatment.
Publisher: Cold Spring Harbor Laboratory
Date: 19-12-2018
DOI: 10.1101/499616
Abstract: Diabetic kidney disease (DKD) is a heritable but poorly understood complication of diabetes. To identify genetic variants predisposing to DKD, we performed genome-wide association analyses in 19,406 in iduals with type 1 diabetes (T1D) using a spectrum of DKD definitions basedon albuminuria and renal function. We identified 16 genome-wide significant loci. The variant with the strongest association (rs55703767) is a common missense mutation in the collagen type IV alpha 3 chain (COL4A3) gene, which encodes a major structural component of the glomerular basement membrane (GBM) implicated in heritable nephropathies. The rs55703767 minor allele (Asp326Tyr) is protective against several definitions of DKD, including albuminuria and end-stage renal disease. Three other loci are in or near genes with known or suggestive involvement in DKD (BMP7) or renal biology ( COLEC11 and DDR1 ). The 16 DKD-associated loci provide novel insights into the pathogenesis of DKD, identifying potential biological targets for prevention and treatment.
Publisher: Elsevier BV
Date: 03-2012
DOI: 10.1016/J.MOLCEL.2012.01.029
Abstract: Aberrant ErbB2 receptor tyrosine kinase activation in breast cancer is strongly linked to an invasive disease. The molecular basis of ErbB2-driven invasion is largely unknown. We show that cysteine cathepsins B and L are elevated in ErbB2 positive primary human breast cancer and function as effectors of ErbB2-induced invasion in vitro. We identify Cdc42-binding protein kinase beta, extracellular regulated kinase 2, p21-activated protein kinase 4, and protein kinase C alpha as essential mediators of ErbB2-induced cysteine cathepsin expression and breast cancer cell invasiveness. The identified signaling network activates the transcription of cathepsin B gene (CTSB) via myeloid zinc finger-1 transcription factor that binds to an ErbB2-responsive enhancer element in the first intron of CTSB. This work provides a model system for ErbB2-induced breast cancer cell invasiveness, reveals a signaling network that is crucial for invasion in vitro, and defines a specific role and targets for the identified serine-threonine kinases.
Publisher: Springer Science and Business Media LLC
Date: 28-06-2022
DOI: 10.1007/S00125-022-05735-0
Abstract: Diabetic kidney disease (DKD) is the leading cause of kidney failure and has a substantial genetic component. Our aim was to identify novel genetic factors and genes contributing to DKD by performing meta-analysis of previous genome-wide association studies (GWAS) on DKD and by integrating the results with renal transcriptomics datasets. We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 in iduals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular ( N =119) and tubular ( N =121) s les to perform transcriptome-wide association study. We also performed gene aggregate tests to jointly test all available common genetic markers within a gene, and combined the results with various kidney omics datasets. The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR ml/min per 1.73 m 2 ) and DKD (microalbuminuria or worse) phenotype ( p =9.8×10 −9 although not withstanding correction for multiple testing, p .3×10 −9 ). Gene-level analysis identified ten genes associated with DKD ( COL20A1 , DCLK1 , EIF4E , PTPRN–RESP18 , GPR158 , INIP–SNX30 , LSM14A and MFF p .7×10 −6 ). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in in iduals with vs without DKD ( p =1.1×10 −6 ). The lead SNPs within six loci significantly altered DNA methylation of a nearby CpG site in kidneys ( p .5×10 −11 ). Expression of lead genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes (e.g. TENM2 expression correlated positively with eGFR [ p =1.6×10 −8 ] and negatively with tubulointerstitial fibrosis [ p =2.0×10 −9 ], tubular DCLK1 expression correlated positively with fibrosis [ p =7.4×10 −16 ], and SNX30 expression correlated positively with eGFR [ p =5.8×10 −14 ] and negatively with fibrosis [ p .0×10 −16 ]). Altogether, the results point to novel genes contributing to the pathogenesis of DKD. The GWAS meta-analysis results can be accessed via the type 1 and type 2 diabetes (T1D and T2D, respectively) and Common Metabolic Diseases (CMD) Knowledge Portals, and downloaded on their respective download pages ( ownloads.html ownloads.html ownloads.html ).
Publisher: American Diabetes Association
Date: 27-04-2018
DOI: 10.2337/DB17-0914
Abstract: Identification of sequence variants robustly associated with predisposition to diabetic kidney disease (DKD) has the potential to provide insights into the pathophysiological mechanisms responsible. We conducted a genome-wide association study (GWAS) of DKD in type 2 diabetes (T2D) using eight complementary dichotomous and quantitative DKD phenotypes: the principal dichotomous analysis involved 5,717 T2D subjects, 3,345 with DKD. Promising association signals were evaluated in up to 26,827 subjects with T2D (12,710 with DKD). A combined T1D+T2D GWAS was performed using complementary data available for subjects with T1D, which, with replication s les, involved up to 40,340 subjects with diabetes (18,582 with DKD). Analysis of specific DKD phenotypes identified a novel signal near GABRR1 (rs9942471, P = 4.5 × 10−8) associated with microalbuminuria in European T2D case subjects. However, no replication of this signal was observed in Asian subjects with T2D or in the equivalent T1D analysis. There was only limited support, in this substantially enlarged analysis, for association at previously reported DKD signals, except for those at UMOD and PRKAG2, both associated with estimated glomerular filtration rate. We conclude that, despite challenges in addressing phenotypic heterogeneity, access to increased s le sizes will continue to provide more robust inference regarding risk variant discovery for DKD.
Publisher: American Diabetes Association
Date: 06-2020
DOI: 10.2337/DB20-516-P
Abstract: People living with type 1 diabetes have increased risk to develop diabetic nephropathy. No targeted cure exists, but the progression can be slowed down if detected early. We tested whether metabolic biomarkers measured in urine could predict progression of diabetic nephropathy (DN) in the Finnish nationwide FinnDiane Study. At baseline, 18 urine metabolites were measured with nuclear magnetic resonance metabolomics and scaled relative to urine creatinine. In iduals were followed for DN status for 9.0 years (± 5.1 years) until they progressed to their most severe DN status (334 events) or the latest known DN status for non-progressors. A Bonferroni-corrected P& .003 was considered significant. Five out of 18 urine metabolites were robustly associated with risk for DN progression in Cox regression models adjusted for sex, year of diabetes diagnosis as well as baseline age, DN status, BMI and eGFR. In iduals with elevated urinary levels of alanine (Hazard Ratio (HR) = 1.49 [1.26, 1.77] per 1-SD creatinine-scaled metabolite concentration, , P=3×10-6), valine (HR = 1.34 [1.22, 1.48], P=4×10-9), 2–hydroxyisobutyrate (HR = 1.48 [1.30, 1.67], P=1×10-9), cis-Aconitate (HR = 1.17 [1.06, 1.28], P=9×10-4) and pseudouridine (HR = 1.45 [1.24, 1.69], P=4×10-6) showed higher DN progression rate. We conclude that urinary biomarkers are indicative of kidney disease progression in type 1 diabetes, independently of baseline microalbuminuria and eGFR. The urinary biomarkers span multiple metabolic pathways, including microbial metabolism, citric acid cycle, and amino acids reflecting adiposity and dietary quality. S. Mutter: None. E.A. Valo: None. V. Aittomäki: Employee Self Nightingale Health Ltd. Other Relationship Self Nightingale Health Ltd. C. Forsblom: None. P. Groop: Advisory Panel Self Boehringer Ingelheim International GmbH, Sanofi, Sanofi. Speaker’s Bureau Self Astellas Pharma Inc., AstraZeneca, Boehringer Ingelheim International GmbH, Eli Lilly and Company, Medscape, Merck Sharp & Dohme Corp., Mundipharma International. P. Wurtz: Employee Self Nightingale Health Ltd. Stock/Shareholder Self Nightingale Health Ltd. Folkhälsan Finland Novo Nordisk Foundation Academy of Finland
Publisher: Cold Spring Harbor Laboratory
Date: 25-10-2020
DOI: 10.1101/2020.10.21.20215921
Abstract: This study examines associations between 51 urinary metabolites and risk of progression of diabetic nephropathy in in iduals with type 1 diabetes by employing an automated nuclear magnetic resonance (NMR) metabolomics technique suitable for large-scale urine s le collections. For 2,670 in iduals with type 1 diabetes from the FinnDiane Study, we collected 24-hour urine s les and measured metabolite concentrations by NMR. In iduals were followed for 9.0 ± 5.0 years until their first sign of progression of diabetic nephropathy, end-stage kidney disease or study end. Cox regression analyses were performed on the entire study population (overall progression), on 1,999 in iduals with normoalbuminuria and 347 in iduals with macroalbuminuria at baseline. Seven urinary metabolites were associated with overall progression after adjustment for baseline albuminuria and chronic kidney disease stage (p 8 × 10 -4 ): Leucine (hazard ratio 1.47, 95% confidence interval [1.30, 1.66] per 1-SD creatinine-scaled metabolite concentration), valine (1.38 [1.22, 1.56]), isoleucine (1.33 [1.18, 1.50]), pseudouridine (1.25 [1.11, 1.42]), threonine (1.27 [1.11, 1.46]) and citrate (0.84 [0.75, 0.93]). 2-hydroxyisobutyrate was associated with overall (1.30 [1.16, 1.45]) and also progression from normoalbuminuria (1.56 [1.25, 1.95]). Six amino acids and pyroglutamate were associated with progression from macroalbuminuria. Branched-amino acids and other urinary metabolites were associated with the progression of diabetic nephropathy on top of baseline albuminuria and chronic kidney disease. We found differences in associations for overall progression and progression from normo- and macroalbuminuria. These novel biomarker discoveries illustrate the utility of analysing urinary metabolites in entire population cohorts. In iduals with type 1 diabetes are vulnerable to diabetic nephropathy and would benefit from earlier detection of disease progression. Urinary metabolites as a direct read-out of kidney function are potential progression markers. However, analytical tools to quantify a broad panel of urinary metabolites at large scale and low cost are lacking. Recent developments in nuclear magnetic resonance address this need. This study in 2,670 in iduals with type 1 diabetes identified ten urinary metabolites associated with progression of diabetic nephropathy. Importantly, different albuminuria categories had different urinary profiles: 2-hydroxyisobutyrate was associated with progression from normoalbuminuria and branched-chain amino acids with progression from macroalbuminuria. These results provide new potential biomarkers and highlight the potential of analysing urinary metabolites on a larger scale.
Publisher: Springer Science and Business Media LLC
Date: 19-10-2023
Publisher: Springer Science and Business Media LLC
Date: 22-10-2021
DOI: 10.1007/S00125-021-05584-3
Abstract: This prospective, observational study examines associations between 51 urinary metabolites and risk of progression of diabetic nephropathy in in iduals with type 1 diabetes by employing an automated NMR metabolomics technique suitable for large-scale urine s le collections. We collected 24-h urine s les for 2670 in iduals with type 1 diabetes from the Finnish Diabetic Nephropathy study and measured metabolite concentrations by NMR. In iduals were followed up for 9.0 ± 5.0 years until their first sign of progression of diabetic nephropathy, end-stage kidney disease or study end. Cox regressions were performed on the entire study population (overall progression), on 1999 in iduals with normoalbuminuria and 347 in iduals with macroalbuminuria at baseline. Seven urinary metabolites were associated with overall progression after adjustment for baseline albuminuria and chronic kidney disease stage ( p 8 × 10 −4 ): leucine (HR 1.47 [95% CI 1.30, 1.66] per 1-SD creatinine-scaled metabolite concentration), valine (1.38 [1.22, 1.56]), isoleucine (1.33 [1.18, 1.50]), pseudouridine (1.25 [1.11, 1.42]), threonine (1.27 [1.11, 1.46]) and citrate (0.84 [0.75, 0.93]). 2-Hydroxyisobutyrate was associated with overall progression (1.30 [1.16, 1.45]) and also progression from normoalbuminuria (1.56 [1.25, 1.95]). Six amino acids and pyroglutamate were associated with progression from macroalbuminuria. Branched-chain amino acids and other urinary metabolites were associated with the progression of diabetic nephropathy on top of baseline albuminuria and chronic kidney disease. We found differences in associations for overall progression and progression from normo- and macroalbuminuria. These novel discoveries illustrate the utility of analysing urinary metabolites in entire population cohorts.
Publisher: Springer Science and Business Media LLC
Date: 27-06-2011
DOI: 10.1038/ONC.2011.230
Abstract: Ras is one of the most frequently activated oncogenes in cancer. Two mitogen-activated protein kinases (MAPKs) are important for ras transformation: extracellular signal-regulated kinase (ERK) and c-Jun N-terminal kinase 2 (JNK2). Here we present a downstream signal lification cascade that is critical for ras transformation in murine embryonic fibroblasts. This cascade is coordinated by ERK and JNK2 MAPKs, whose Ras-mediated activation leads to the enhanced levels of three oncogenic transcription factors, namely, c-Myc, activating transcription factor 2 (ATF2) and ATF3, all of which are essential for ras transformation. Previous studies show that ERK-mediated serine 62 phosphorylation protects c-Myc from proteasomal degradation. ERK is, however, not alone sufficient to stabilize c-Myc but requires the cooperation of cancerous inhibitor of protein phosphatase 2A (CIP2A), an oncogene that counteracts protein phosphatase 2A-mediated dephosphorylation of c-Myc. Here we show that JNK2 regulates Cip2a transcription via ATF2. ATF2 and c-Myc cooperate to activate the transcription of ATF3. Remarkably, not only ectopic JNK2, but also ectopic ATF2, CIP2A, c-Myc and ATF3 are sufficient to rescue the defective ras transformation of JNK2-deficient cells. Thus, these data identify the key signal converging point of JNK2 and ERK pathways and underline the central role of CIP2A in ras transformation.
Publisher: Springer Science and Business Media LLC
Date: 09-2021
No related grants have been discovered for Erkka Valo.