Maija Parkkonen

New susceptibility loci associated with kidney disease in Type 1 diabetes

Diabetic kidney disease, or diabetic nephropathy (DN), is a major complication of diabetes and the leading cause of end-stage renal disease (ESRD) that requires dialysis treatment or kidney transplantation. In addition to the decrease in the quality of life, DN accounts for a large proportion of the excess mortality associated with type 1 diabetes (T1D). Whereas the degree of glycemia plays a pivotal role in DN, a subset of individuals with poorly controlled T1D do not develop DN. Furthermore, strong familial aggregation supports genetic susceptibility to DN. However, the genes and the molecular mechanisms behind the disease remain poorly understood, and current therapeutic strategies rarely result in reversal of DN. In the GEnetics of Nephropathy: an International Effort (GENIE) consortium, we have undertaken a meta-analysis of genome-wide association studies (GWAS) of T1D DN comprising ∼2.4 million single nucleotide polymorphisms (SNPs) imputed in 6,691 individuals. After additional genotyping of 41 top ranked SNPs representing 24 independent signals in 5,873 individuals, combined meta-analysis revealed association of two SNPs with ESRD: rs7583877 in the AFF3 gene (P = 1.2×10−8) and an intergenic SNP on chromosome 15q26 between the genes RGMA and MCTP2, rs12437854 (P = 2.0×10−9). Functional data suggest that AFF3 influences renal tubule fibrosis via the transforming growth factor-beta (TGF-β1) pathway. The strongest association with DN as a primary phenotype was seen for an intronic SNP in the ERBB4 gene (rs7588550, P = 2.1×10−7), a gene with type 2 diabetes DN differential expression and in the same intron as a variant with cis-eQTL expression of ERBB4. All these detected associations represent new signals in the pathogenesis of DN.

Genomewide Scan for Familial Combined Hyperlipidemia Genes in Finnish Families, Suggesting Multiple Susceptibility Loci Influencing Triglyceride, Cholesterol, and Apolipoprotein B Levels

Familial combined hyperlipidemia (FCHL) is a common dyslipidemia predisposing to premature coronary heart disease (CHD). The disease is characterized by increased levels of serum total cholesterol (TC), triglycerides (TGs), or both. We recently localized the first locus for FCHL, on chromosome 1q21-q23. In the present study, a genomewide screen for additional FCHL loci was performed. In stage 1, we genotyped 368 polymorphic markers in 35 carefully characterized Finnish FCHL families. We identified six chromosomal regions with markers showing LOD score (Z) values >1.0, by using a dominant mode of inheritance for the FCHL trait. In addition, two more regions emerged showing Z>2.0 with a TG trait. In stage 2, we genotyped 26 more markers and seven additional FCHL families for these interesting regions. Two chromosomal regions revealed Z>2.0 in the linkage analysis: 10p11.2, Z=3.20 (theta=.00), with the TG trait; and 21q21, Z=2.24 (theta=.10), with the apoB trait. Furthermore, two more chromosomal regions produced Z>2.0 in the affected-sib-pair analysis: 10q11.2-10qter produced Z=2.59 with the TC trait and Z=2.29 with FCHL, and 2q31 produced Z=2.25 with the TG trait. Our results suggest additional putative loci influencing FCHL in Finnish families, some potentially affecting TG levels and some potentially affecting TC or apoB levels.

1H NMR metabonomics approach to the disease continuum of diabetic complications and premature death

Subtle metabolic changes precede and accompany chronic vascular complications, which are the primary causes of premature death in diabetes. To obtain a multimetabolite characterization of these high‐risk individuals, we measured proton nuclear magnetic resonance (1H NMR) data from the serum of 613 patients with type I diabetes and a diverse spread of complications. We developed a new metabonomics framework to visualize and interpret the data and to link the metabolic profiles to the underlying diagnostic and biochemical variables. Our results indicate complex interactions between diabetic kidney disease, insulin resistance and the metabolic syndrome. We illustrate how a single 1H NMR protocol is able to identify the polydiagnostic metabolite manifold of type I diabetes and how its alterations translate to clinical phenotypes, clustering of micro‐ and macrovascular complications, and mortality during several years of follow‐up. This work demonstrates the diffuse nature of complex vascular diseases and the limitations of single diagnostic biomarkers. However, it also promises cost‐effective solutions through high‐throughput analytics and advanced computational methods, as applied here in a case that is representative of the real clinical situation.

Metabolic Phenotypes, Vascular Complications and Premature Deaths in a Population of 4,197 Patients with Type 1 Diabetes

OBJECTIVE—Poor glycemic control, elevated triglycerides, and albuminuria are associated with vascular complications in diabetes. However, few studies have investigated combined associations between metabolic markers, diabetic kidney disease, retinopathy, hypertension, obesity, and mortality. Here, the goal was to reveal previously undetected association patterns between clinical diagnoses and biochemistry in the FinnDiane dataset. RESEARCH DESIGN AND METHODS—At baseline, clinical records, serum, and 24-h urine samples of 2,173 men and 2,024 women with type 1 diabetes were collected. The data were analyzed by the self-organizing map, which is an unsupervised pattern recognition algorithm that produces a two-dimensional layout of the patients based on their multivariate biochemical profiles. At follow-up, the results were compared against all-cause mortality during 6.5 years (295 deaths). RESULTS—The highest mortality was associated with advanced kidney disease. Other risk factors included 1) a profile of insulin resistance, abdominal obesity, high cholesterol, triglycerides, and low HDL2 cholesterol, and 2) high adiponectin and high LDL cholesterol for older patients. The highest population-adjusted risk of death was 10.1-fold (95% CI 7.3–13.1) for men and 10.7-fold (7.9–13.7) for women. Nonsignificant risk was observed for a profile with good glycemic control and high HDL2 cholesterol and for a low cholesterol profile with a short diabetes duration. CONCLUSIONS—The self-organizing map analysis enabled detailed risk estimates, described the associations between known risk factors and complications, and uncovered statistical patterns difficult to detect by classical methods. The results also suggest that diabetes per se, without an adverse metabolic phenotype, does not contribute to increased mortality.

Association Testing of Previously Reported Variants in a Large Case–Control Meta-Analysis of Diabetic Nephropathy

We formed the GEnetics of Nephropathy–an International Effort (GENIE) consortium to examine previously reported genetic associations with diabetic nephropathy (DN) in type 1 diabetes. GENIE consists of 6,366 similarly ascertained participants of European ancestry with type 1 diabetes, with and without DN, from the All Ireland-Warren 3-Genetics of Kidneys in Diabetes U.K. and Republic of Ireland (U.K.-R.O.I.) collection and the Finnish Diabetic Nephropathy Study (FinnDiane), combined with reanalyzed data from the Genetics of Kidneys in Diabetes U.S. Study (U.S. GoKinD). We found little evidence for the association of the EPO promoter polymorphism, rs161740, with the combined phenotype of proliferative retinopathy and end-stage renal disease in U.K.-R.O.I. (odds ratio [OR] 1.14, P = 0.19) or FinnDiane (OR 1.06, P = 0.60). However, a fixed-effects meta-analysis that included the previously reported cohorts retained a genome-wide significant association with that phenotype (OR 1.31, P = 2 × 10−9). An expanded investigation of the ELMO1 locus and genetic regions reported to be associated with DN in the U.S. GoKinD yielded only nominal statistical significance for these loci. Finally, top candidates identified in a recent meta-analysis failed to reach genome-wide significance. In conclusion, we were unable to replicate most of the previously reported genetic associations for DN, and significance for the EPO promoter association was attenuated.

Acute hyperglycaemia induces an inflammatory response in young patients with type 1 diabetes.

Background. Patients with type 1 diabetes (T1D) are at a substantially increased risk of cardiovascular disease. Stress-induced hyperglycaemia in turn is shown to worsen the prognosis of patients suffering from an acute myocardial infarction. However, the mechanisms behind these findings are incompletely known. Aim. To investigate whether markers of chronic inflammation, and oxidative stress respond to acute hyperglycaemia in patients with T1D. Methods. The plasma glucose concentration was rapidly raised from 5 to 15 mmol/L in 35 males (22 men with T1D and 13 age-matched non-diabetic volunteers) and maintained for 2 h. All participants were young non-smokers without any signs of diabetic or other complications. Markers of chronic inflammation, and oxidative stress were analysed in serum/plasma samples drawn at base-line and after 120 min of hyperglycaemia. Results. Compared to normoglycaemia, acute hyperglycaemia increased the interleukin (IL)-6 concentrations by 39% in patients with T1D (P<0.01) and 26% in healthy volunteers (P<0.05). During hyperglycaemia the superoxide dismutase concentration was increased by 17% in the healthy volunteers (P<0.01) and 5% in the patients with type 1 diabetes (P=NS). The increase in tumour necrosis factor (TNF)-α was larger in patients with type 1 diabetes than in non-diabetic volunteers (35% versus −10%, P<0.05). Conclusions. This study shows that acute hyperglycaemia induces an inflammatory response in patients with type 1 diabetes.

High-throughput pedigree drawing

Family trees have long been a valuable visual tool for geneticists in identifying clusters of inherited traits and genotypes. As more data are collected, drawing the graphs by hand becomes impractical and, for this reason, we have developed the pedigree software CraneFoot. It can process any family graph with minimal computational cost by making a pedigree transformation that enables the use of a linear node positioning algorithm. The program is designed for automated drawing to printed media and efficient visual classification of genetically interesting families from large data sets. It also incorporates a robust pedigree topology check with detailed error messages.

The effect of (steroid) immunosuppression on skeletal muscle glycogen metabolism in patients after kidney transplantation.

To examine the mechanisms by which immunosuppression by steroids impairs glycogen synthesis in human skeletal muscle, we measured glycogen synthase protein content and activity in muscle samples from 14 patients receiving corticosteroid therapy after kidney transplantation and in 20 healthy control subjects. A percutaneous muscle sample was taken before and at the end of a euglycemic hyperinsulinemic insulin clamp. Insulin-stimulated glucose disposal was reduced by 33% in kidney transplant patients compared with healthy controls (33.8 +/- 4.2 vs. 50.5 +/- 2.7 mumol (kg LBM)-1 min-1; P<0.01), primarily due to a decrease in nonoxidative glucose metabolism (14.2 +/- 3.3 vs. 32.3 +/- 2.7 mumol (kg LBM)-1 min-1; P<0.001). Glycogen synthase activity measured at both 0.1 mmol/L (17.6 +/- 2.6 vs. 24.0 +/- 2.2 nmol min-1 mg protein-1; P<0.05), and at 10 mmol/L glucose 6-phosphate (24.1 +/- 3.5 vs. 33.7 +- 2.4 nmol min-1 mg protein-1; P<0.05) and glycogen synthase protein concentrations (8.8 +/- 1.8 vs. 18.9 +/- 1.9 relative units per ng DNA; P<0.01) were lower in kidney transplant patients compared with controls. Glycogen synthase protein correlated with nonoxidative glucose metabolism (r=0.42; P=0.04). Alpha-actinin (used as a control of general protein degradation) was lower in kidney transplant patients compared with controls (4.4 +/- 0.8 vs. 9.6 +/- 1.1 cpm/ng DNA; P<0.01). In conclusion, corticosteroids cause insulin resistance, which correlates with impaired activation of glycogen synthase and decreased enzyme protein content. The decrease in glycogen synthase protein may reflect increased degradation rather than a defect in translation.

Association analysis of the AIRE and insulin genes in Finnish type 1 diabetic patients

Mutations in the autoimmune regulator (AIRE) gene cause a recessive Mendelian disorder autoimmune polyendocrinopathy syndrome type 1 (APS-1 or autoimmune polyendocrinopathy-candidiasis-ectodermal dystrophy). APS-1 patients develop multiorgan autoimmune diseases including type 1 diabetes (prevalence 12%). The AIRE protein controls the central tolerance induction in the thymus by regulating the expression levels of tissue-specific peripheral antigens, such as insulin. We hypothesized that the insulin gene (INS) polymorphisms together with the AIRE variations may predispose individuals to diabetes. The role of the AIRE gene was tested both independently and on the condition of the INS risk genotype in the Finnish type 1 diabetes sample. A total of 733 type 1 diabetic cases and 735 age- and sex-matched healthy controls were used in the analysis. Five common single nucleotide polymorphisms (SNPs) in the AIRE gene were selected from the public database (dbSNP). The −23HphI polymorphism was used as a surrogate marker for the INS gene promoter repeat. The five genotyped SNPs in the AIRE gene showed no evidence of association with type 1 diabetes. As expected, the INS gene polymorphism −23HphI was significantly associated with susceptibility to type 1 diabetes (P=6.8×10−12, χ2 test). When the subclass of patients carrying the homozygote genotype of the INS gene was used in the analysis, the AIRE polymorphisms showed no association with the disease. In conclusion, the AIRE gene does not seem to contribute to disease susceptibility in Finnish type 1 diabetic patients, whereas the insulin gene represents a notable risk factor for disease in this population.

Polymorphisms in the gene encoding angiotensin I converting enzyme 2 and diabetic nephropathy

Aims/hypothesisSubstantial evidence exists for the involvement of the renin–angiotensin system (RAS) in diabetic nephropathy. Angiotensin I converting enzyme 2 (ACE2), a new component of the RAS, has been implicated in kidney disease, hypertension and cardiac function. Based on this, the aim of the present study was to evaluate whether variations in ACE2 are associated with diabetic nephropathy.Materials and methodsWe used a cross-sectional, case–control study design to investigate 823 Finnish type 1 diabetic patients (365 with and 458 without nephropathy). Five single-nucleotide polymorphisms (SNPs) were genotyped using TaqMan technology. Haplotypes were estimated using PHASE software, and haplotype frequency differences were analysed using a χ2-test-based tool.ResultsNone of the ACE2 polymorphisms was associated with diabetic nephropathy, and this finding was supported by the haplotype analysis. The ACE2 polymorphisms were not associated with blood pressure, BMI or HbA1c.Conclusions/interpretationIn Finnish type 1 diabetic patients, ACE2 polymorphisms are not associated with diabetic nephropathy or any studied risk factor for this complication. Further studies are necessary to assess a minor effect of ACE2.