Early-onset of ADCK4 glomerulopathy with renal failure: a case report.

BACKGROUND: We present a rare early presentation of a ADCK4-related glomerulopathy. This case is of interest as potentially treatable if genetic results are timely obtained. CASE PRESENTATION: We report the case of a 5-year-old boy who was identified with significant proteinuria by a urinary routine screening program for school children. Physical examination revealed dysplastic ears and abnormal folded pinna. Albumin level was 41 g/L (39-53 g/L), and urine proteins/creatinine ratio was 2.6 g/g. Renal ultrasound showed enlarged kidneys and perimedullary hyperechogenicity. Treatment by angiotensin-converting-enzyme inhibitor was not beneficial. Renal biopsy showed signs of focal segmental glomerulosclerosis. After 4 years of follow-up, he developed a clinical nephrotic syndrome and no response to prednisone and other immunosuppressive agents was obtained. Within 6 months, he was in end-stage-renal-failure (ESRF) and hemodialysis was started. He was transplanted at 10 years with his mother's kidney. Genes known to be responsible in steroid-resistant nephrotic syndromes were tested. Our patient is compound heterozygous for two mutations in the aarF domain-containing-kinase 4 (ADCK4) gene. ADCK4 gene is one of the genes involved in coenzyme Q10 (CoQ10) biosynthesis, is located in chromosome 19q13.2 and expressed in podocytes. ADCK4 mutations show a largely renal-limited phenotype. The nephropathy usually presents during adolescence, fast evolves towards ESRF, and may be treatable by CoQ10 supplementation if started early in the disease. Our patient presented nephrotic range proteinuria at 5 years, and he reached ESRF at 10 years. CONCLUSION: ADCK4-related glomerulopathy is an important novel and potentially treatable cause of isolated nephropathy not only in adolescents, but also in children in their first decade of life. Discovery of important proteinuria in an asymptomatic child should prompt early genetic investigations.

Quantitative trait genetic linkage analysis of body mass index in familial coronary artery disease.

OBJECTIVE: Body mass index (BMI) is one of the most reproducible and commonly used proxies for obesity and is known to be influenced by many environmental causes as well as genetic factors. Identification of susceptibility genes for BMI regulation has been difficult. Reasons for these inconclusive results are both methodological and related to obesity aetiology. A genome-wide linkage analysis was performed to localise Quantitative trait loci influencing BMI in a large cohort collected in the PROCARDIS coronary heart disease study consisting of 1,812 informative families. METHODS: Multipoint linkage analysis for BMI was conducted using both a variance component approach and a model-free regression method, and the resulting LOD scores were compared. RESULTS: The strongest evidence for linkage was detected on chromosomes 13 (LOD 1.6). Other regions showing a LOD score greater than 1 were observed on chromosomes 3, 5, 11, 12 and 15. These results were mainly confirmed by the three different approaches used in the analysis. CONCLUSION: Our study did not find any locus with strongly supporting evidence for linkage to BMI even in such a large sample. Our results confirm the substantial genetic heterogeneity influencing BMI regulation that has emerged from the majority of genome scans so far published.

Multiple QTL influence the serum Lp(a) concentration: a genome-wide linkage screen in the PROCARDIS study.

The serum concentration of lipoprotein Lp (a) is known to be highly heritable and associated with cardiovascular risk. A genome-wide variance component linkage analysis was performed to localise quantitative trait loci (QTLs) influencing Lp(a) levels in a large cohort collected in the PROCARDIS coronary heart disease study. Highly significant linkage was detected at the previously described LP(a) locus on chromosome 6q27 (LOD 108). Taking into account the effect of the locus detected on chromosome 6, a highly significant LOD score was detected on chromosome 13q22-31 (LOD 7.0). Another significant region of linkage was observed on chromosomes 11p14-15 (LOD 3.5). The significant peak at 13q22-31 shows an essential overlap with a locus modulating cholesterol in familial hypercholesterolemia. If the gene underlying these loci is the same, it will be a promising candidate target for manipulating LDL-cholesterol and Lp(a). We also detected linkage at a previously identified locus influencing Lp(a) on chromosome 1q23 (LOD 1.5). Our findings provide new and confirmatory information about genomic regions involved in the quantitative variation of Lp(a) and serve as a basis for further studies of candidate genes in these regions.

Meta-analysis of 4 coronary heart disease genome-wide linkage studies confirms a susceptibility locus on chromosome 3q.

OBJECTIVE: In coronary heart disease (CHD), 4 independent, genome-wide screens have now been published on Finnish, Mauritian, European, and Australian families. Results from these studies are inconclusive. We performed a meta-analysis to identify genetic regions that show evidence for susceptibility genes across studies. METHODS AND RESULTS: The rank-based genome-scan meta-analysis (GSMA) method was applied to the 4 CHD genome-wide linkage studies. The strongest evidence for linkage was found on chromosomes 3q26-27 (P=0.0001) and 2q34-37 (P=0.009). Analysis weighted by study size confirmed linkage in these regions (3q26-27, P=0.0002; 2q34-37, P=0.014). CONCLUSIONS: The genetic regions 3q26-27 and 2q34-37 might contain susceptibility genes for CHD. Linkage to the 3q26-qter region has previously been shown in type 2 diabetes mellitus, metabolic syndrome, cholesterol concentration in LDL size fractions, and renal function in hypertensive subjects. The 2q34-37 region lies close to the type 2 diabetes NIDDM1 locus. Both of these regions harbor several candidate genes involved in the homeostasis of glucose and lipid metabolism. These results are particularly intriguing, given the growing evidence of an association between CHD risk and metabolic abnormalities, such as insulin resistance, type 2 diabetes, abdominal obesity, and dyslipidemia.

Adiponectin gene polymorphisms and their effect on the risk of myocardial infarction and type 2 diabetes: an association study in an Italian population.

OBJECTIVE: While many studies have shown an association between the gene coding for adiponectin (ADIPOQ) and adiponectin levels, much more controversy surrounds its association with metabolic traits such as insulin resistance, obesity and type 2 diabetes. Furthermore, very few studies have looked into the relations between ADIPOQ variants and risk of cardiovascular disease. The present study assessed the influence of four common ADIPOQ Single Nucleotide Polymorphisms (SNPs), rs17300539 (-11391G→A), rs266729 (-11377C→G), rs2241766 (+45T→G) and rs1501299 (+276G→T) on the risk of myocardial infarction and type 2 diabetes. METHODS: and RESULTS: A large genetic association case-control study was conducted in 2008 Italians, including patients with myocardial infarction, type 2 diabetes, or both, and a reference group of healthy controls. Homozygotes TT for the rs1501299 (+276) had half the risk of either myocardial infarction alone or in association with type 2 diabetes when compared to the carriers of the G allele (OR = 0.58, p =0.01, and OR = 0.55, p =0.006 respectively). SNPs rs17300539 (-11391), rs266729 (-11377) and rs2241766 (+45) showed no significant association with any of the three case groups. CONCLUSIONS: These results suggest that homozygotes TT for the adiponectin polymorphism rs1501299 (+276) are protected from the risk of myocardial infarction.

Apolipoprotein E polymorphisms influence effect of pravastatin on survival after myocardial infarction in a Mediterranean population: the GISSI-Prevenzione study.

AIMS: Controversy exists with regard to the influence of APOE polymorphisms on coronary heart disease development and on the efficacy of statin treatment. we investigated the relationship between apoe, mortality and the response to treatment in Mediterranean myocardial infarction (mi) survivors. METHODS AND RESULTS: We analysed 3304 Italian patients with MI randomized to pravastatin or no treatment in the GISSI-Prevenzione study, with a mean follow-up time of 23.0 +/- 6.7 months (median 24.3 months). Mortality curves were calculated using Kaplan-Meier method, and differences in survival were tested using the log-rank test. There were 109 deaths during follow-up. Patients treated with pravastatin showed a significant decrease in mortality compared with non-treated patients (HR 0.67, 95% confidence interval 0.45-0.97, P = 0.038). Among the 3304 patients, 554 (16.8%) were epsilon4 carriers and 2750 (83.2%) were non-epsilon4 carriers. No significant difference in terms of mortality was observed between the epsilon4 and the non-epsilon4 carriers (3.61% vs. 3.24%, P = 0.67). However, although in non-epsilon4 carriers no significant difference in mortality was observed between patients treated with pravastatin and non-treated (2.81% vs. 3.67%, P = 0.21), among the epsilon4 carriers a significant reduction in mortality was observed in patients treated compared with non-treated (1.85% vs. 5.28%, P = 0.023). CONCLUSION: We found that epsilon4 allele is a determinant of pravastatin response in terms of survival. Though in the entire population investigated,we found a beneficial effect of pravastatin in terms of survival, only the epsilon4 carriers seemed to have gained a significant benefit from this treatment. We suggest that the effect of statins is of particular interest in this fraction of the population. Genetic markers can help in identifying patients that benefit more from statin treatment.

Meta-analysis of genome-wide linkage studies in BMI and obesity.

OBJECTIVE: The objective was to provide an overall assessment of genetic linkage data of BMI and BMI-defined obesity using a nonparametric genome scan meta-analysis. RESEARCH METHODS AND PROCEDURES: We identified 37 published studies containing data on over 31,000 individuals from more than >10,000 families and obtained genome-wide logarithm of the odds (LOD) scores, non-parametric linkage (NPL) scores, or maximum likelihood scores (MLS). BMI was analyzed in a pooled set of all studies, as a subgroup of 10 studies that used BMI-defined obesity, and for subgroups ascertained through type 2 diabetes, hypertension, or subjects of European ancestry. RESULTS: Bins at chromosome 13q13.2- q33.1, 12q23-q24.3 achieved suggestive evidence of linkage to BMI in the pooled analysis and samples ascertained for hypertension. Nominal evidence of linkage to these regions and suggestive evidence for 11q13.3-22.3 were also observed for BMI-defined obesity. The FTO obesity gene locus at 16q12.2 also showed nominal evidence for linkage. However, overall distribution of summed rank p values <0.05 is not different from that expected by chance. The strongest evidence was obtained in the families ascertained for hypertension at 9q31.1-qter and 12p11.21-q23 (p < 0.01). CONCLUSION: Despite having substantial statistical power, we did not unequivocally implicate specific loci for BMI or obesity. This may be because genes influencing adiposity are of very small effect, with substantial genetic heterogeneity and variable dependence on environmental factors. However, the observation that the FTO gene maps to one of the highest ranking bins for obesity is interesting and, while not a validation of this approach, indicates that other potential loci identified in this study should be investigated further.