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Diabetic kidney disease (DKD) represents a major global health problem. Accelerated ageing is a key feature of DKD and, therefore, characteristics of accelerated ageing may provide useful biomarkers or therapeutic targets. Harnessing multi-omics, features affecting telomere biology and any associated methylome dysregulation in DKD were explored. Genotype data for nuclear genome polymorphisms in telomere-related genes were extracted from genome-wide case–control association data (n = 823 DKD/903 controls; n = 247 end-stage kidney disease (ESKD)/1479 controls). Telomere length was established using quantitative polymerase chain reaction. Quantitative methylation values for 1091 CpG sites in telomere-related genes were extracted from epigenome-wide case–control association data (n = 150 DKD/100 controls). Telomere length was significantly shorter in older age groups (p = 7.6 × 10−6). Telomere length was also significantly reduced (p = 6.6 × 10−5) in DKD versus control individuals, with significance remaining after covariate adjustment (p = 0.028). DKD and ESKD were nominally associated with telomere-related genetic variation, with Mendelian randomisation highlighting no significant association between genetically predicted telomere length and kidney disease. A total of 496 CpG sites in 212 genes reached epigenome-wide significance (p ≤ 10−8) for DKD association, and 412 CpG sites in 193 genes for ESKD. Functional prediction revealed differentially methylated genes were enriched for Wnt signalling involvement. Harnessing previously published RNA-sequencing datasets, potential targets where epigenetic dysregulation may result in altered gene expression were revealed, useful as potential diagnostic and therapeutic targets for intervention.

OBJECTIVE Understanding mechanisms underlying rapid estimated glomerular filtration rate (eGFR) decline is important to predict and treat kidney disease in type 1 diabetes (T1D). RESEARCH DESIGN AND METHODS We performed a case-control study nested within four T1D cohorts to identify urinary proteins associated with rapid eGFR decline. Case and control subjects were categorized based on eGFR decline ≥3 and RESULTS The cohort study included 1,270 participants followed a median 8 years. In the discovery set, only cathepsin D peptide and protein were significant on full adjustment for clinical and laboratory variables. In the validation set, associations of cathepsin D with eGFR decline were replicated in minimally adjusted models but lost significance with adjustment for albuminuria. In a meta-analysis with combination of discovery and validation sets, the odds ratio for the association of cathepsin D with rapid eGFR decline was 1.29 per SD (95% CI 1.07–1.55). In complementary human cohorts, urine cathepsin D was associated with tubulointerstitial injury and tubulointerstitial cathepsin D expression was associated with increased cortical interstitial fractional volume. In mouse proximal tubular epithelial cell cultures, advanced glycation end product–BSA increased cathepsin D activity and inflammatory and tubular injury markers, which were further increased with cathepsin D siRNA. CONCLUSIONS Urine cathepsin D is associated with rapid eGFR decline in T1D and reflects kidney tubulointerstitial injury.

AimsIndividuals with type 1 diabetes (T1D) carry a markedly increased risk of stroke, with distinct clinical and neuroimaging characteristics as compared to those without diabetes. Using whole-genome sequencing (WGS) and whole-exome sequencing (WES), we aimed to find rare and low-frequency genomic variants associated with stroke in T1D. The lead findings were followed up in various datasets to replicate the findings and to assess their specificity to diabetes.Methods and ResultsWe studied stroke genetics in 1,051 individuals with T1D using WGS or WES. We analysed the genome with single-variant analyses, gene aggregate analyses, and aggregate analyses on genomic windows, enhancers and promoters. Furthermore, we attempted replication in T1D using a genome-wide association study (N=3,945) and direct genotyping (N=3,600), and in the general population from the FinnGen project and UK Biobank summary statistics. We identified a rare missense mutation onSREBF1associated with hemorrhagic stroke (rs114001633, p.Pro227Leu,p-value=8.96×10-9), which further replicated in T1D. Using gene aggregate analysis with protein altering or protein truncating variants, we identified exome-wide significant genes:ANK1andLRRN1displayed replication evidence in T1D, whileLRRN1,HAS1andUACAreplicated in the general population (UK Biobank). Furthermore, we performed sliding-window analyses and identified 14 genome-wide significant windows for stroke on 4q33-34.1, of which two replicated in T1D, and a suggestive genomic window onLINC01500, which replicated in T1D. Finally, with the regulatory region aggregate analyses, we identified a stroke-associatedTRPM2-ASpromoter (p-value=5.78×10-6), which we validated with an in vitro cell-based assay.TRPM2has been previously linked to ischemic stroke.ConclusionsHere, we report the first genome-wide analysis on stroke in individuals with diabetes. We identified multiple stroke risk loci with evidence of replication: 4q33-34.1,SREBF1, andANK1for stroke in T1D; andHAS1,UACA,LRRN1,LINC01500, andTRPM2-ASpromoter for stroke potentially generalizable to the non-diabetic population.

Aims/hypothesis This prospective, observational study examines associations between 51 urinary metabolites and risk of progression of diabetic nephropathy in individuals with type 1 diabetes by employing an automated NMR metabolomics technique suitable for large-scale urine sample collections. Methods We collected 24-h urine samples for 2670 individuals with type 1 diabetes from the Finnish Diabetic Nephropathy study and measured metabolite concentrations by NMR. Individuals 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 individuals with normoalbuminuria and 347 individuals with macroalbuminuria at baseline. Results Seven urinary metabolites were associated with overall progression after adjustment for baseline albuminuria and chronic kidney disease stage (p −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. Conclusions/interpretation 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. Graphical abstract

The exon copy number variant in the haptoglobin gene is associated with cardiovascular and kidney disease. For stroke, previous research is inconclusive. We aimed to study the relationship between haptoglobin Hp1/2 genotype and stroke in individuals with type 1 diabetes from the Finnish Diabetic Nephropathy Study. We included two partially overlapping cohorts: one with haptoglobin genotypes determined using genotyping for 179 stroke cases and 517 matched controls, and the other using haptoglobin genotype imputation for a larger cohort of 500 stroke cases and 3,806 controls. We observed no difference in the Hp1-1, Hp2-1, and Hp2-2 genotype frequencies between the stroke cases and controls, neither in the genotyping nor the imputation cohorts. Haptoglobin genotypes were also not associated with the ischemic or hemorrhagic stroke subtypes. In our imputed haptoglobin cohort, 61% of individuals with stroke died during follow-up. However, the risk of death was not related to the haptoglobin genotype. Diabetic kidney disease and cardiovascular events were common in the cohort, but the haptoglobin genotypes were not associated with stroke when stratified by these complications. To conclude, the Hp1/2 genotypes did not affect the risk of stroke or survival after stroke in our type 1 diabetes cohort.

Fatty-acid binding protein 4 (FABP4) is implicated in the pathogenesis of cardiometabolic disorders. Pharmacological inhibition or genetic deletion of FABP4 improves cardiometabolic health and protects against atherosclerosis in preclinical models. As cardiovascular disease (CVD) is common in type 1 diabetes, we examined the role of FABP4 for the development of complications in type 1 diabetes, focusing on a functional, low-expression, variant (rs77878271) in the promoter of the FABP4 gene. For this, we assessed the risk of CVD, stroke, coronary artery disease (CAD), end-stage kidney disease (ESKD), and mortality using Cox proportional-hazard models for the FABP4 rs77878271 in 5,077 Finnish individuals with type 1 diabetes. The low-expression G-allele of rs77878271 increased the risk of CVD, independently of confounders. Findings were tested for replication in 852 Danish and 3,678 Finnish individuals with type 1 diabetes. In the meta-analysis, each G-allele increased the risk of stroke by 26% (p=0.04), CAD by 26% (p=0.006), and CVD by 17% (p=0.003). In Mendelian Randomization, a decrease in FABP4 increased CAD 2.4-fold. Hence, in contrast to the general population, the low-expression G-allele of rs77878271 increased CVD risk in type 1 diabetes, suggesting that genetically low FABP4 levels may be detrimental in the context of type 1 diabetes.

Aims/hypothesis 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. Methods We performed GWAS meta-analyses using ten phenotypic definitions of DKD, including nearly 27,000 individuals with diabetes. Meta-analysis results were integrated with estimated quantitative trait locus data from human glomerular (N=119) and tubular (N=121) samples 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. Results The meta-analysis identified a novel intronic variant (rs72831309) in the TENM2 gene associated with a lower risk of the combined chronic kidney disease (eGFR2) and DKD (microalbuminuria or worse) phenotype (p=9.8×10−9; although not withstanding correction for multiple testing, p>9.3×10−9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN–RESP18, GPR158, INIP–SNX30, LSM14A and MFF; p−6). Integration of GWAS with human glomerular and tubular expression data demonstrated higher tubular AKIRIN2 gene expression in individuals 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−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−16]). Conclusions/interpretation Altogether, the results point to novel genes contributing to the pathogenesis of DKD. Data availability 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 (https://t1d.hugeamp.org/downloads.html; https://t2d.hugeamp.org/downloads.html; https://hugeamp.org/downloads.html). Graphical abstract

Background We aimed to assess whether remnant cholesterol concentration and variability predict the progression of diabetic nephropathy (DN) and severe diabetic retinopathy (SDR) in type 1 diabetes. Methods This observational prospective study covered 5150 FinnDiane Study participants. Remnant cholesterol was calculated as total cholesterol - LDL cholesterol - HDL cholesterol and variability as the coefficient of variation. DN category was based on consensus albuminuria reference limits and the progression status was confirmed from medical files. SDR was defined as retinal laser treatment. For 1338 individuals, the severity of diabetic retinopathy (DR) was graded using the ETDRS classification protocol. Median (IQR) follow-up time was 8.0 (4.9-13.7) years for DN and 14.3 (10.4-16.3) for SDR. Results Remnant cholesterol (mmol L-1) was higher with increasing baseline DN category (P < 0.001). A difference was also seen comparing non-progressors (0.41 [0.32-0.55]) with progressors (0.55 [0.40-0.85]), P < 0.001. In a Cox regression analysis, remnant cholesterol predicted DN progression, independently of diabetes duration, sex, HbA(1c), systolic blood pressure, smoking, BMI, estimated glucose disposal rate and estimated glomerular filtration rate (HR: 1.51 [1.27-1.79]). Remnant cholesterol was also higher in those who developed SDR (0.47 [0.36-0.66]) than those who did not (0.40 [0.32-0.53]), P < 0.001, and the concentration increased stepwise with increasing DR severity (P < 0.001). Regarding SDR, the HR for remnant cholesterol was 1.52 (1.26-1.83) with the most stringent adjustment. However, remnant cholesterol variability was not independently associated with the outcomes. Conclusions Remnant cholesterol concentration, but not variability, predicts DN progression and development of SDR. However, it remains to be elucidated whether the associations are causal or not.

Objective: Understanding mechanisms underlying rapid estimated glomerular filtration rate (eGFR) decline is important to predict and treat kidney disease in type 1 diabetes (T1D). Research Design and Methods: We performed a case-control study nested within four T1D cohorts to identify urinary proteins associated with rapid eGFR decline. Cases and controls were defined by eGFR decline >3 and 2/year, respectively. We used targeted liquid chromatography-tandem mass spectrometry to measure 38 peptides from 20 proteins implicated in diabetic kidney disease. Significant proteins were investigated in complementary human cohorts and in mouse proximal tubular epithelial cell cultures. Results: The cohort study included 1270 participants followed a median 8 years. In the discovery set, only cathepsin D peptide and protein were significant on full adjustment for clinical and laboratory variables. In the validation set, associations of cathepsin D with eGFR decline were replicated in minimally-adjusted models but lost significance with adjustment for albuminuria. In a meta-analysis combining discovery and validation sets, the odds ratio for the association of cathepsin D with rapid eGFR decline was 1.29 per SD (95%CI 1.07-1.55). In complementary human cohorts, urine cathepsin D was associated with tubulointerstitial injury, and tubulointerstitial cathepsin D expression was associated with increased cortical interstitial fractional volume. In mouse proximal tubular epithelial cell cultures, advanced glycation end product-bovine serum albumin increased cathepsin D activity and inflammatory and tubular injury markers, which were further increased with cathepsin D siRNA. Conclusion: Urine cathepsin D is associated with rapid eGFR decline in T1D and reflects kidney tubulointerstitial injury.

Background Type 1 diabetes (T1D) is an autoimmune disease affecting individuals in the early years of life. Although previous studies have identified genetic loci influencing T1D diagnosis age, these studies did not investigate the genome with high resolution. Objective and methods We performed a genome-wide meta-analysis for age at diagnosis with cohorts from Finland (Finnish Diabetic Nephropathy Study), the United Kingdom (UK Genetic Resource Investigating Diabetes) and Sardinia. Through SNP associations, transcriptome-wide association analysis linked T1D diagnosis age and gene expression. Results We identified two chromosomal regions associated with T1D diagnosis age: multiple independent variants in the HLA region on chromosome 6 and a locus on chromosome 17q12. We performed gene-level association tests with transcriptome prediction models from two whole blood datasets, lymphocyte cell line, spleen, pancreas and small intestine tissues. Of the non-HLA genes, lower PNMT expression in whole blood, and higher IKZF3 and ZPBP2, and lower ORMDL3 and GSDMB transcription levels in multiple tissues were associated with lower T1D diagnosis age (FDR = 0.05). These genes lie on chr17q12 which is associated with T1D, other autoimmune diseases, and childhood asthma. Additionally, higher expression of PHF20L1, a gene not previously implicated in T1D, was associated with lower diagnosis age in lymphocytes, pancreas, and spleen. Altogether, the non-HLA associations were enriched in open chromatin in various blood cells, blood vessel tissues and foetal thymus tissue. Conclusion Multiple genes on chr17q12 and PHF20L1 on chr8 were associated with T1D diagnosis age and only further studies may elucidate the role of these genes for immunity and T1D onset.

Aims/hypothesis Lipid abnormalities are associated with diabetic kidney disease and CHD, although their exact role has not yet been fully explained. Sphingomyelin, the predominant sphingolipid in humans, is crucial for intact glomerular and endothelial function. Therefore, the objective of our study was to investigate whether sphingomyelin impacts kidney disease and CHD progression in individuals with type 1 diabetes. Methods Individuals (n = 1087) from the Finnish Diabetic Nephropathy (FinnDiane) prospective cohort study with serum sphingomyelin measured using a proton NMR metabolomics platform were included. Kidney disease progression was defined as change in eGFR or albuminuria stratum. Data on incident end-stage renal disease (ESRD) and CHD were retrieved from national registries. HRs from Cox regression models and regression coefficients from the logistic or linear regression analyses were reported per 1 SD increase in sphingomyelin level. In addition, receiver operating curves were used to assess whether sphingomyelin improves eGFR decline prediction compared with albuminuria. Results During a median (IQR) 10.7 (6.4, 13.5) years of follow-up, sphingomyelin was independently associated with the fastest eGFR decline (lowest 25%; median [IQR] for eGFR change: −1 [1.73 m−2] year−1), even after adjustment for classical lipid variables such as HDL-cholesterol and triacylglycerols (OR [95% CI]: 1.36 [1.15, 1.61], p p = 0.001). Moreover, sphingomyelin increased the risk of CHD (HR [95% CI]: 1.24 [1.01, 1.52], p = 0.038). However, sphingomyelin did not perform better than albuminuria in the prediction of eGFR decline. Conclusions/interpretation This study demonstrates for the first time in a prospective setting that sphingomyelin is associated with the fastest eGFR decline and progression to ESRD in type 1 diabetes. In addition, sphingomyelin is a risk factor for CHD. These data suggest that high sphingomyelin level, independently of classical lipid risk factors, may contribute not only to the initiation and progression of kidney disease but also to CHD.

Publisher Copyright: © 2020 John Wiley & Sons, Inc. Diabetic microvascular complications, affecting the kidneys, retina, and the nervous system, are a heavy burden for both the diabetic individual and society. The complications seem to cluster in families suggesting a genetic component in their pathogenesis. However, the actual genetic factors have long remained unknown. During the past few years, major advances have been made with large-scale genetic studies that have identified common genetic risk factors, e.g. in the AFF3 and CNKSR3 gene loci affecting the risk of diabetic kidney disease (DKD) end-stage renal disease. There is increasing evidence that genetic factors affecting kidney disease in non-diabetic individuals also affect the risk in individuals with type 2 diabetes (T2D), while less evidence is found for individuals with type 1 diabetes (T1D). While genetic explorations for diabetic retinopathy remain limited in sample size, a recent genome-wide association study (GWAS) identified variants associated with retinopathy on the GRB2 gene. Nevertheless, the field is still lacking strong validated genetic markers. In the future, better phenotyping, larger studies, and exploration of the rare variation are essential to identify the genetic causes behind diabetic microvascular complications, and to understand the interplay between genes and environment.

AIMS: Diabetes is a known risk factor for coronary artery disease. There is accumulating evidence that coronary artery disease pathogenesis differs for individuals with type 1 diabetes. However, the genetic background has not been extensively studied. We aimed to discover genetic loci increasing coronary artery disease susceptibility especially in type 1 diabetes, to examine the function of these discoveries and to study the role of the known risk loci in type 1 diabetes. METHODS AND RESULTS: We performed the largest genome-wide association study to date for coronary artery disease in type 1 diabetes, comprising 4869 individuals with type 1 diabetes (cases/controls: 941/3928). Two loci reached genome-wide significance, rs1970112 in CDKN2B-AS1 (OR = 1.32, p=1.50 x 10-8), and rs6055069 on DEFB127 promoter (OR = 4.17, p=2.35 x 10-9), with consistent results in survival analysis. The CDKN2B-AS1 variant replicated (p=0.04) when adjusted for diabetic kidney disease in three additional type 1 diabetes cohorts (cases/controls: 434/3123). Furthermore, we explored the function of the lead discoveries with a cardio-phenome-wide analysis. Among the eight suggestive loci (p

The exon copy number variant in the haptoglobin gene is associated with cardiovascular and kidney disease. For stroke, previous research is inconclusive. We aimed to study the relationship between the haptoglobin Hp1/2 genotype and stroke in individuals with type 1 diabetes from the Finnish Diabetic Nephropathy Study. We included two partially overlapping cohorts: one with haptoglobin genotypes determined using genotyping for 179 individuals with stroke and 517 matched control subjects, and the other using haptoglobin genotype imputation for a larger cohort of 500 individuals with stroke and 3,806 individuals without stroke. We observed no difference in the Hp1-1, Hp2-1, and Hp2-2 genotype frequencies between individuals with or without stroke, neither in the genotyping nor the imputation cohorts. Haptoglobin genotypes were also not associated with the ischemic or hemorrhagic stroke subtypes. In our imputed haptoglobin cohort, 61% of individuals with stroke died during follow-up. However, the risk of death was not related to the haptoglobin genotype. Diabetic kidney disease and cardiovascular events were common in the cohort, but the haptoglobin genotypes were not associated with stroke when stratified by these complications. To conclude, the Hp1/2 genotypes did not affect the risk of stroke or survival after stroke in our cohort with type 1 diabetes.

Background Translocation of lipopolysaccharide from gram‐negative bacteria into the systemic circulation results in endotoxemia. In addition to acute infections, endotoxemia is detected in cardiometabolic disorders, such as cardiovascular diseases and obesity. Methods and Results We performed a genome‐wide association study of serum lipopolysaccharide activity in 11 296 individuals from 6 different Finnish study cohorts. Endotoxemia was measured by limulus amebocyte lysate assay in the whole population and by 2 other techniques (Endolisa and high‐performance liquid chromatography/tandem mass spectrometry) in subpopulations. The associations of the composed genetic risk score of endotoxemia and thrombosis‐related clinical end points for 195 170 participants were analyzed in FinnGen. Lipopolysaccharide activity had a genome‐wide significant association with 741 single‐nucleotide polymorphisms in 5 independent loci, which were mainly located at genes affecting the contact activation of the coagulation cascade and lipoprotein metabolism and explained 1.5% to 9.2% of the variability in lipopolysaccharide activity levels. The closest genes included KNG1 , KLKB1 , F12 , SLC34A1 , YPEL4 , CLP1 , ZDHHC5 , SERPING1 , CBX5 , and LIPC . The genetic risk score of endotoxemia was associated with deep vein thrombosis, pulmonary embolism, pulmonary heart disease, and venous thromboembolism. Conclusions The biological activity of lipopolysaccharide in the circulation (ie, endotoxemia) has a small but highly significant genetic component. Endotoxemia is associated with genetic variation in the contact activation pathway, vasoactivity, and lipoprotein metabolism, which play important roles in host defense, lipopolysaccharide neutralization, and thrombosis, and thereby thromboembolism and stroke.

Background Rare variants in gene coding regions likely have a greater impact on disease-related phenotypes than common variants through disruption of their encoded protein. We searched for rare variants associated with onset of end stage kidney disease (ESKD) in individuals with type 1 diabetes at advanced kidney disease stage. Methods Gene-based exome array analysis of 15,449 genes in 5 large incidence cohorts of individuals with type 1 diabetes and proteinuria were analyzed for survival time-to-ESKD, testing the top gene in a 6th cohort (N=2,372/1,115 events all cohorts) and replicating in two retrospective case-control studies (N=1,072 cases, 752 controls). Deep resequencing of the top associated gene in 5 cohorts confirmed the findings. We performed immunohistochemistry and gene expression experiments in human control and diseased cells, and in mouse ischemia reperfusion and aristolochic acid nephropathy models. Results Protein coding variants in the hydroxysteroid 17-beta dehydrogenase 14 gene (HSD17B14), predicted to affect protein structure, had a net protective effect against development of ESKD at exome-wide significance (N=4,196; p-value=3.3x10-7). The HSD17B14 gene and encoded enzyme were robustly expressed in healthy human kidney, maximally in proximal tubular cells. Paradoxically, gene and protein expression were attenuated in human diabetic proximal tubules and in mouse kidney injury models. Expressed HSD17B14 gene and protein levels remained low without recovery after 21 days in a murine ischemic reperfusion injury model. Decreased gene expression was found in other chronic kidney disease-associated renal pathologies. Conclusions HSD17B14 gene is mechanistically involved in diabetic kidney disease. The encoded sex steroid enzyme is a druggable target, potentially opening a new avenue for therapeutic development.

Dyslipidemia is a major risk factor for cardiovascular disease. While common genetic variants are known to modestly affect the serum lipid concentrations, rare genetic mutations can cause monogenic forms of hypercholesteremia and other genetic disorders of lipid metabolism. Aiming to identify low-frequency protein-altering variants (PAVs) affecting lipoprotein and lipid traits, we analyzed whole-exome and whole-genome sequencing data of 481 and 573 individuals with type 1 diabetes, respectively. The phenotypic data consisted of 97 serum lipid, apolipoprotein, or other metabolic phenotypes obtained with clinical laboratory measurements and nuclear magnetic resonance (NMR) technology. Single variant analysis identified a novel association between LIPC p.Thr405Met (rs113298164) and serum apolipoprotein-A1 levels (p=7.8×10−8). In the APOB gene, we identified novel associations at two protein-truncating variants (PTVs) resulting in lower serum apolipoprotein B levels (p=5.6×10−4). The burden of PAVs was significantly associated with lipid phenotypes in LIPC, RBM47, TRMT5, and GTF3C5 (p−6). The RBM47 gene is required for apolipoprotein-B post-translational modifications, and in our data, the association between RBM47 and apolipoprotein C-III levels was led by a rare 21 base pair Ala496-Ala502 deletion; as replication, the burden of rare deleterious variants in RBM47 was associated with TG-to-HDLC ratio in WES of 20,917 individuals (p=0.0093). Two PAVs in GTF3C5 were highly Finnish-enriched and associated with cardiovascular phenotypes in external data, whereby the TRMT5 p.Ser185Cys lead variant was associated with stroke phenotypes. Altogether, we identified both novel variant associations in known lipid genes, as well as novel genes implicated in lipoprotein metabolism.

We recently mapped a genetic susceptibility locus on chromosome 6q22.33 for type 1 diabetes diagnosed below age of 7 years near the gene Protein tyrosine phosphatase receptor type K (PTPRK) and the thymocyte selection associated gene (THEMIS). As the thymus plays a central role in shaping the T cell repertoire, we aimed to identify the most likely causal genetic factors behind the association using thymocyte genomic data. In four thymocyte populations we identified 253 DNA sequence motifs underlying histone modifications. The G insertion allele of rs138300818, associated with protection from diabetes, created thymocyte motifs for multiple histone modifications and thymocyte types. The insertion also disrupted a predicted RFX5/7 transcription factor binding site. RFX7 is abundantly expressed in thymus. Chromatin state and RNA sequencing data suggested strong transcription overlapping rs138300818 in fetal thymus, while eQTL and chromatin conformation data indicated that the rs138300818 insertion is associated with lower THEMIS expression. Taken together, our results support a role for thymic THEMIS gene expression and the rs138300818 variant in promoting the development and diagnosis of type 1 diabetes at an earlier age.

BackgroundDiabetes is the leading cause of kidney disease, and heritability studies demonstrate a substantial, yet poorly understood, contribution of genetics to kidney complications in people with diabetes.MethodsWe performed genome-wide association study (GWAS) meta-analyses using ten different phenotypic definitions of diabetic kidney disease (DKD), including nearly 27,000 individuals with diabetes, and integrated the results with various kidney omics datasets.ResultsThe meta-analysis identified a novel low frequency intronic variant (rs72831309) in the TENM2 gene encoding teneurin transmembrane protein 2 associated with a lower risk of the combined chronic kidney disease (CKD; eGFR2) and DKD (microalbuminuria or worse) phenotype (“CKD-DKD”, odds ratio 2.08, p=9.8×10−9). Gene-level analysis identified ten genes associated with DKD (COL20A1, DCLK1, EIF4E, PTPRN-RESP18, GPR158, INIP-SNX30, LSM14A, and MFF, p−6). Integration of GWAS data with human glomerular and tubular expression data in a transcriptome-wide association study demonstrated higher tubular AKIRIN2 gene expression in DKD versus non-DKD controls (p=1.1×10−6). The lead SNPs within the DCLK1, AKIRIN2, SNX30 and three other gene regions significantly alterated the methylation at this region in kidneys (p−11). Expression of target genes in kidney tubules or glomeruli correlated with relevant pathological phenotypes. For example, tubular TENM2 expression positively correlated with eGFR (p=2.3×10−9) and negatively with tubulointerstitial fibrosis (p=4.7×10−9), tubular DCLK1 expression positively correlated with fibrosis (p=1.6×10−12), and SNX30 level positively correlated with eGFR (p=7.6×10−13) and negatively with fibrosis (p−16).ConclusionsGWAS meta-analysis and integration with renal omics data points to novel genes contributing to pathogenesis of DKD.

Diabetic retinopathy is a common diabetes complication that threatens the eyesight and may eventually lead to acquired visual impairment or blindness. While a substantial heritability has been reported for proliferative diabetic retinopathy (PDR), only a few genetic risk factors have been identified. Using genome-wide sib pair linkage analysis including 361 individuals with type 1 diabetes, we found suggestive evidence of linkage with PDR at chromosome 10p12 overlapping the CACNB2 gene (logarithm of odds = 2.73). Evidence of association between variants in CACNB2 and PDR was also found in association analysis of 4,005 individuals with type 1 diabetes with an odds ratio of 0.83 and P value of 8.6 x 10(-4) for rs11014284. Sequencing of CACNB2 revealed two coding variants, R476C/rs202152674 and S502L/rs137886839. CACNB2 is abundantly expressed in retinal cells and encodes the beta 2 subunit of the L-type calcium channel. Blocking vascular endothelial growth factor (VEGF) by intravitreous anti-VEGF injections is a promising clinical therapy to treat PDR. Our data show that L-type calcium channels regulate VEGF expression and secretion from retinal pigment epithelial cells (ARPE19) and support the role of CACNB2 via regulation of VEGF in the pathogenesis of PDR. However, further genetic and functional studies are necessary to consolidate the findings.

OBJECTIVE Individuals 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. RESEARCH DESIGN AND METHODS This study in 3,295 individuals 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). RESULTS 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 individuals below the median age (38.6 years) compared with those above (C-index = 0.637 vs. C-index = 0.546). CONCLUSIONS A GRS identified individuals at high risk of CAD and worked better in younger individuals. 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.

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 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.

Background A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this exploratory investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing to identify potential blood-based biomarkers. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina’s Infinium MethylationEPIC BeadChip arrays (n = 862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p ≤ × 10–8 and fold change ± 2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM. Results Top-ranked genes within which several dmCpGs were located and supported by functional data with methylation look-ups in other cohorts include: AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9 and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation. Conclusions Epigenetic alterations provide a dynamic link between an individual’s genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.

Fatty acid binding protein 4 (FABP4) is implicated in the pathogenesis of cardiometabolic disorders. Pharmacological inhibition or genetic deletion of FABP4 improves cardiometabolic health and protects against atherosclerosis in preclinical models. As cardiovascular disease (CVD) is common in type 1 diabetes, we examined the role of FABP4 in the development of complications in type 1 diabetes, focusing on a functional, low-expression variant (rs77878271) in the promoter of the

Supplemental Digital Content is available in the text., Background: Peripheral artery disease (PAD) affects >200 million people worldwide and is associated with high mortality and morbidity. We sought to identify genomic variants associated with PAD overall and in the contexts of diabetes and smoking status. Methods: We identified genetic variants associated with PAD and then meta-analyzed with published summary statistics from the Million Veterans Program and UK Biobank to replicate their findings. Next, we ran stratified genome-wide association analysis in ever smokers, never smokers, individuals with diabetes, and individuals with no history of diabetes and corresponding interaction analyses, to identify variants that modify the risk of PAD by diabetic or smoking status. Results: We identified 5 genome-wide significant (Passociation ≤5×10−8) associations with PAD in 449 548 (Ncases=12 086) individuals of European ancestry near LPA (lipoprotein [a]), CDKN2BAS1 (CDKN2B antisense RNA 1), SH2B3 (SH2B adaptor protein 3) - PTPN11 (protein tyrosine phosphatase non-receptor type 11), HDAC9 (histone deacetylase 9), and CHRNA3 (cholinergic receptor nicotinic alpha 3 subunit) loci (which overlapped previously reported associations). Meta-analysis with variants previously associated with PAD showed that 18 of 19 published variants remained genome-wide significant. In individuals with diabetes, rs116405693 at the CCSER1 (coiled-coil serine rich protein 1) locus was associated with PAD (odds ratio [95% CI], 1.51 [1.32–1.74], Pdiabetes=2.5×10−9, Pinteractionwithdiabetes=5.3×10−7). Furthermore, in smokers, rs12910984 at the CHRNA3 locus was associated with PAD (odds ratio [95% CI], 1.15 [1.11–1.19], Psmokers=9.3×10−10, Pinteractionwithsmoking=3.9×10−5). Conclusions: Our analyses confirm the published genetic associations with PAD and identify novel variants that may influence susceptibility to PAD in the context of diabetes or smoking status.

Background Chronic kidney disease (CKD) shows different clinical features in Types1 (T1D) and 2 diabetes (T2D). Metabolomics have recently provided useful contribution to the identification of biomarkers of CKD progression in either form of the disease. However, no studies have so far compared plasma metabolomics between T1D and T2D in order to identify differential signatures of progression of estimated glomerular filtration rate (eGFR) decline. Methods We used two large cohorts of T1D (from Finland) and T2D (from Italy) patients followed up to 7 and 3 years, respectively. In both groups, progression was defined as the top quartile of yearly decline in eGFR. Pooled data from the two groups were analysed by univariate and bivariate random forest (RF), and confirmed by bivariate partial least squares (PLS) analysis, the response variables being type of diabetes and eGFR progression. Results In progressors, yearly eGFR loss was significantly larger in T2D [−5.3 (3.0), median (interquartile range)mL/min/1.73 m2/year] than T1D [−3.7 (3.1) mL/min/1.73 m2/year ; P = 0.018]. Out of several hundreds, bivariate RF extracted 22 metabolites associated with diabetes type (all higher in T1D than T2D except for 5-methylthioadenosine, pyruvate and β-hydroxypyruvate) and 13 molecules associated with eGFR progression (all higher in progressors than non-progressors except for sphyngomyelin). Three of the selected metabolites (histidylphenylalanine, leucylphenylalanine, tryptophylasparagine) showed a significant interaction between disease type and progression. Only eight metabolites were common to both bivariate RF and PLS. Conclusions Identification of metabolomic signatures of CKD progression is partially dependent on the statistical model. Dual analysis identified molecules specifically associated with progressive renal impairment in both T1D and T2D.

AimsThis study examines associations between 51 urinary metabolites and risk of progression of diabetic nephropathy in individuals with type 1 diabetes by employing an automated nuclear magnetic resonance (NMR) metabolomics technique suitable for large-scale urine sample collections.MethodsFor 2,670 individuals with type 1 diabetes from the FinnDiane Study, we collected 24-hour urine samples and measured metabolite concentrations by NMR. Individuals 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 individuals with normoalbuminuria and 347 individuals with macroalbuminuria at baseline.ResultsSeven 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.ConclusionsBranched-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.Significance StatementIndividuals 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 individuals 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.

Rare variants in gene coding regions likely have a greater impact on disease-related phenotypes than common variants through disruption of their encoded protein. We searched for rare variants associated with onset of ESKD in individuals with type 1 diabetes at advanced kidney disease stage.Gene-based exome array analyses of 15,449 genes in five large incidence cohorts of individuals with type 1 diabetes and proteinuria were analyzed for survival time to ESKD, testing the top gene in a sixth cohort (Protein coding variants in the hydroxysteroid 17

A subset of individuals with type 1 diabetes mellitus (T1DM) are predisposed to developing diabetic kidney disease (DKD), which is the most common cause globally of end-stage kidney disease (ESKD). Emerging evidence suggests epigenetic changes in DNA methylation may have a causal role in both T1DM and DKD. The aim of this investigation was to assess differences in blood-derived DNA methylation patterns between individuals with T1DM-ESKD and individuals with long-duration T1DM but no evidence of kidney disease upon repeated testing. Blood-derived DNA from individuals (107 cases, 253 controls and 14 experimental controls) were bisulphite treated before DNA methylation patterns from both groups were generated and analysed using Illumina's Infinium MethylationEPIC BeadChip arrays (n=862,927 sites). Differentially methylated CpG sites (dmCpGs) were identified (false discovery rate adjusted p≤x10-8 and fold change ±2) by comparing methylation levels between ESKD cases and T1DM controls at single site resolution. Gene annotation and functionality was investigated to enrich and rank methylated regions associated with ESKD in T1DM. Top-ranked genes within which several dmCpGs were located and supported by in silico functional data, and replication where possible, include; AFF3, ARID5B, CUX1, ELMO1, FKBP5, HDAC4, ITGAL, LY9, PIM1, RUNX3, SEPTIN9, and UPF3A. Top-ranked enrichment pathways included pathways in cancer, TGF-β signalling and Th17 cell differentiation. Epigenetic alterations provide a dynamic link between an individual's genetic background and their environmental exposures. This robust evaluation of DNA methylation in carefully phenotyped individuals, has identified biomarkers associated with ESKD, revealing several genes and implicated key pathways associated with ESKD in individuals with T1DM.

Background Several genetic susceptibility loci associated with diabetic nephropathy have been documented, but no causative variants implying novel pathogenetic mechanisms have been elucidated. Methods We carried out whole-genome sequencing of a discovery cohort of Finnish siblings with type 1 diabetes who were discordant for the presence (case) or absence (control) of diabetic nephropathy. Controls had diabetes without complications for 15-37 years. We analyzed and annotated variants at genome, gene, and single-nucleotide variant levels. We then replicated the associated variants, genes, and regions in a replication cohort from the Finnish Diabetic Nephropathy study that included 3531 unrelated Finns with type 1 diabetes. Results We observed protein-altering variants and an enrichment of variants in regions associated with the presence or absence of diabetic nephropathy. The replication cohort confirmed variants in both regulatory and protein-coding regions. We also observed that diabetic nephropathy-associated variants, when clustered at the gene level, are enriched in a core protein-interaction network representing proteins essential for podocyte function. These genes include protein kinases (protein kinase C isoforms epsilon and iota and protein tyrosine kinase 2. Conclusions Our comprehensive analysis of a diabetic nephropathy cohort of siblings with type 1 diabetes who were discordant for kidney disease points to variants and genes that are potentially causative or protective for diabetic nephropathy. This includes variants in two isoforms of the protein kinase C family not previously linked to diabetic nephropathy, adding support to previous hypotheses that the protein kinase C family members play a role in diabetic nephropathy and might be attractive therapeutic targets.

Background: Individuals with type 1 diabetes (T1D) demonstrate varied trajectories of estimated glomerular filtration rate (eGFR) decline. The molecular pathways underlying rapid eGFR decline in T1D are poorly understood, and individual-level risk of rapid eGFR decline is difficult to predict. Methods: We designed a case-control study with multiple exposure measurements nested within 4 well-characterized T1D cohorts (FinnDiane, Steno, EDC, and CACTI) to identify biomarkers associated with rapid eGFR decline. Here, we report the rationale for and design of these studies as well as results of models testing associations of clinical characteristics with rapid eGFR decline in the study population, upon which “omics” studies will be built. Cases (n = 535) and controls (n = 895) were defined as having an annual eGFR decline of ≥3 and 2, respectively. Associations of demographic and clinical variables with rapid eGFR decline were tested using logistic regression, and prediction was evaluated using area under the curve (AUC) statistics. Targeted metabolomics, lipidomics, and proteomics are being performed using high-resolution mass-spectrometry techniques. Results: At baseline, the mean age was 43 years, diabetes duration was 27 years, eGFR was 94 mL/min/1.73 m2, and 62% of participants were normoalbuminuric. Over 7.6-year median follow-up, the mean annual change in eGFR in cases and controls was −5.7 and 0.6 mL/min/1.73 m2, respectively. Younger age, longer diabetes duration, and higher baseline HbA1c, urine albumin-creatinine ratio, and eGFR were significantly associated with rapid eGFR decline. The cross-validated AUC for the predictive model incorporating these variables plus sex and mean arterial blood pressure was 0.74 (95% CI: 0.68–0.79; p < 0.001). Conclusion: Known risk factors provide moderate discrimination of rapid eGFR decline. Identification of blood and urine biomarkers associated with rapid eGFR decline in T1D using targeted omics strategies may provide insight into disease mechanisms and improve upon clinical predictive models using traditional risk factors.

To identify genetic variants associated with diabetic retinopathy (DR), we performed a large multiethnic genome-wide association study. Discovery included eight European cohorts (n = 3,246) and seven African American cohorts (n = 2,611). We meta-analyzed across cohorts using inverse-variance weighting, with and without liability threshold modeling of glycemic control and duration of diabetes. Variants with a P value

Diabetic kidney disease and other long-term complications are common in diabetes, and comprise the main cause of co-morbidity and premature mortality in individuals with diabetes. While familial clustering and heritability have been reported for all diabetic complications, the genetic background and the molecular mechanisms remain poorly understood. In recent years, genome-wide association studies have identified a few susceptibility loci for the renal complications as well as for diabetic retinopathy, diabetic cardiovascular disease and mortality. As for many complex diseases, the genetic factors increase the risk of complications in concert with the environment, and certain associations seem specific for particular conditions, for example, SP3-CDCA7 associated with end-stage renal disease only in women, or MGMT and variants on chromosome 5q13 associated with cardiovascular mortality only under tight glycaemic control. The characterization of the phenotypes is one of the main challenges for genetic research on diabetic complications, in addition to an urgent need to increase the number of individuals with diabetes with high quality phenotypic data to be included in future genetic studies.

Aims/hypothesis We aimed to identify a sparse panel of biomarkers for improving the prediction of renal disease progression in type 1 diabetes. Methods We considered 859 individuals recruited from the Scottish Diabetes Research Network Type 1 Bioresource (SDRNT1BIO) and 315 individuals from the Finnish Diabetic Nephropathy (FinnDiane) study. All had an entry eGFR between 30 and 75 ml min−1[1.73 m]−2, with those from FinnDiane being oversampled for albuminuria. A total of 297 circulating biomarkers (30 proteins, 121 metabolites, 146 tryptic peptides) were measured in non-fasting serum samples using the Luminex platform and LC electrospray tandem MS (LC-MS/MS). We investigated associations with final eGFR adjusted for baseline eGFR and with rapid progression (a loss of more than 3 ml min−1[1.73 m]−2 year−1) using linear and logistic regression models. Panels of biomarkers were identified using a penalised Bayesian approach, and their performance was evaluated through 10-fold cross-validation and compared with using clinical record data alone. Results For final eGFR, 16 proteins and 30 metabolites or tryptic peptides showed significant association in SDRNT1BIO, and nine proteins and five metabolites or tryptic peptides in FinnDiane, beyond age, sex, diabetes duration, study day eGFR and length of follow-up (all at p

Summary Common genetic variants predispose to obesity with varying contribution by age. We incorporated known genetic variants into genetic risk scores (GRSs) and investigated their associations with overweight/obesity and central obesity in preadolescents. Furthermore, we compared GRSs with lifestyle factors, and tested if they predict the change in body size and shape in a 4‐year follow‐up. We utilized 1142 subjects from the Finnish Health in Teens (Fin‐HIT) cohort. Overweight and obesity were defined with age‐ and gender‐specific body mass index (BMI) z‐score (BMIz), while central obesity by the waist‐to‐height ratio (WHtR). Background data on parental language, eating habits, leisure‐time physical activity (LTPA) and sleep duration were included. Genotyping was performed with the Metabochip platform. Weighted, standardized GRSs were derived. Of the11‐year‐old children, 25.5% were at least overweight and 90.8% had Finnish speaking background. BMI‐GRS was associated with higher risk for overweight with odds ratio (95% confidence interval) of 1.39 (1.20; 1.60) and obesity 1.41 (1.08; 1.83), but not with central obesity. BMI‐GRS was weakly and inversely associated with the changes in BMIz and WHtR in the 4‐year follow‐up. Waist‐to‐hip ratio‐GRS was not related to any obesity measures at baseline nor in the follow‐up. The effect of BMI‐GRS is similar to that of low LTPA on overweight. An interaction between parental language and BMI‐GRS was noted (P = .019): BMI‐GRS associated more strongly with overweight in Swedish than in Finnish speakers. We further identified two suggestive genetic variants near LOC101926977 and LOC105369677 associated with BMIz in preadolescents which were replicated in the adult population. In preadolescents, known genetic predisposing factors induce a risk for overweight comparable to low LTPA. However, the GRS was poor in predicting short‐term changes in BMI or WHtR.