CUBN is a gene locus for albuminuria.

Identification of genetic risk factors for albuminuria may alter strategies for early prevention of CKD progression, particularly among patients with diabetes. Little is known about the influence of common genetic variants on albuminuria in both general and diabetic populations. We performed a meta-analysis of data from 63,153 individuals of European ancestry with genotype information from genome-wide association studies (CKDGen Consortium) and from a large candidate gene study (CARe Consortium) to identify susceptibility loci for the quantitative trait urinary albumin-to-creatinine ratio (UACR) and the clinical diagnosis microalbuminuria. We identified an association between a missense variant (I2984V) in the CUBN gene, which encodes cubilin, and both UACR (P = 1.1 × 10(-11)) and microalbuminuria (P = 0.001). We observed similar associations among 6981 African Americans in the CARe Consortium. The associations between this variant and both UACR and microalbuminuria were significant in individuals of European ancestry regardless of diabetes status. Finally, this variant associated with a 41% increased risk for the development of persistent microalbuminuria during 20 years of follow-up among 1304 participants with type 1 diabetes in the prospective DCCT/EDIC Study. In summary, we identified a missense CUBN variant that associates with levels of albuminuria in both the general population and in individuals with diabetes.

No evidence for a causal link between uric acid and type 2 diabetes: a Mendelian randomisation approach.

AIMS/HYPOTHESIS: Epidemiological and experimental evidence suggests that uric acid has a role in the aetiology of type 2 diabetes. Using a Mendelian randomisation approach, we investigated whether there is evidence for a causal role of serum uric acid for development of type 2 diabetes. METHODS: We examined the associations of serum-uric-acid-raising alleles of eight common variants recently identified in genome-wide association studies and summarised this in a genetic score with type 2 diabetes in case-control studies including 7,504 diabetes patients and 8,560 non-diabetic controls. We compared the observed effect size to that expected based on: (1) the association between the genetic score and uric acid levels in non-diabetic controls; and (2) the meta-analysed uric acid level to diabetes association. RESULTS: The genetic score showed a linear association with uric acid levels, with a difference of 12.2 μmol/l (95% CI 9.3, 15.1) by score tertile. No significant associations were observed between the genetic score and potential confounders. No association was observed between the genetic score and type 2 diabetes with an OR of 0.99 (95% CI 0.94, 1.04) per score tertile, significantly different (p = 0.046) from that expected (1.04 [95% CI 1.03, 1.05]) based on the observed uric acid difference by score tertile and the uric acid to diabetes association of 1.21 (95% CI 1.14, 1.29) per 60 μmol/l. CONCLUSIONS/INTERPRETATION: Our results do not support a causal role of serum uric acid for the development of type 2 diabetes and limit the expectation that uric-acid-lowering drugs will be effective in the prevention of type 2 diabetes.

Les tests génétiques peuvent-ils être utiles pour la prévention cardiovasculaire? [Are genetic tests useful for cardiovascular prevention?].

Recent progresses in genetics have opened new avenues to further our understanding of the pathophysiological mechanisms underlying cardiovascular disease, raising, new expectations in the field of personalized medicine. Genetic tests may have a high predictive value for rare monogenic diseases. The situation is very different for common polygenic diseases, such as myocardial infarction, type 2 diabetes or stroke. The results from recent genome-wide association studies have provided useful information for research, but have not yet been proven to be clinically useful. It is therefore currently not recommended to conducted genetic testing to guide cardiovascular prevention neither in clinical nor in public health settings.

IL28B expression depends on a novel TT/-G polymorphism which improves HCV clearance prediction.

Approximately 3% of the world population is chronically infected with the hepatitis C virus (HCV), with potential development of cirrhosis and hepatocellular carcinoma. Despite the availability of new antiviral agents, treatment remains suboptimal. Genome-wide association studies (GWAS) identified rs12979860, a polymorphism nearby IL28B, as an important predictor of HCV clearance. We report the identification of a novel TT/-G polymorphism in the CpG region upstream of IL28B, which is a better predictor of HCV clearance than rs12979860. By using peripheral blood mononuclear cells (PBMCs) from individuals carrying different allelic combinations of the TT/-G and rs12979860 polymorphisms, we show that induction of IL28B and IFN-γ-inducible protein 10 (IP-10) mRNA relies on TT/-G, but not rs12979860, making TT/-G the only functional variant identified so far. This novel step in understanding the genetic regulation of IL28B may have important implications for clinical practice, as the use of TT/G genotyping instead of rs12979860 would improve patient management.

Androgenetic alopecia: identification of four genetic risk loci and evidence for the contribution of WNT signaling to its etiology.

The pathogenesis of androgenetic alopecia (AGA, male-pattern baldness) is driven by androgens, and genetic predisposition is the major prerequisite. Candidate gene and genome-wide association studies have reported that single-nucleotide polymorphisms (SNPs) at eight different genomic loci are associated with AGA development. However, a significant fraction of the overall heritable risk still awaits identification. Furthermore, the understanding of the pathophysiology of AGA is incomplete, and each newly associated locus may provide novel insights into contributing biological pathways. The aim of this study was to identify unknown AGA risk loci by replicating SNPs at the 12 genomic loci that showed suggestive association (5 × 10(-8)<P<10(-5)) with AGA in a recent meta-analysis. We analyzed a replication set comprising 2,759 cases and 2,661 controls of European descent to confirm the association with AGA at these loci. Combined analysis of the replication and the meta-analysis data identified four genome-wide significant risk loci for AGA on chromosomes 2q35, 3q25.1, 5q33.3, and 12p12.1. The strongest association signal was obtained for rs7349332 (P=3.55 × 10(-15)) on chr2q35, which is located intronically in WNT10A. Expression studies in human hair follicle tissue suggest that WNT10A has a functional role in AGA etiology. Thus, our study provides genetic evidence supporting an involvement of WNT signaling in AGA development.

New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes.

Genetic testing in patients with obesity.

The obesity epidemic is associated with the recent availability of highly palatable and inexpensive caloric food as well as important changes in lifestyle. Genetic factors, however, play a key role in regulating energy balance and numerous twin studies have estimated the BMI heritability between 40 and 70%. While common variants, identified through genome-wide association studies (GWAS) point toward new pathways, their effect size are too low to be of any use in the clinic. This review therefore concentrates on genes and genomic regions associated with very high risks of human obesity. Although there are no consensus guidelines, we review how the knowledge on these "causal factors" can be translated into the clinic for diagnostic purposes. We propose genetic workups guided by clinical manifestations in patients with severe early-onset obesity. While etiological diagnoses are unequivocal in a minority of patients, new genomic tools such as Comparative Genomic Hybridization (CGH) array, have allowed the identification of novel "causal" loci and next-generation sequencing brings the promise of accelerated pace for discoveries relevant to clinical practice.

Meta-analysis of gene-level associations for rare variants based on single-variant statistics.

Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.

ZNRD1 (zinc ribbon domain-containing 1) is a host cellular factor that influences HIV-1 replication and disease progression.

BACKGROUND: Human immunodeficiency virus (HIV) takes advantage of multiple host proteins to support its own replication. The gene ZNRD1 (zinc ribbon domain-containing 1) has been identified as encoding a potential host factor that influenced disease progression in HIV-positive individuals in a genomewide association study and also significantly affected HIV replication in a large-scale in vitro short interfering RNA (siRNA) screen. Genes and polymorphisms identified by large-scale analysis need to be followed up by means of functional assays and resequencing efforts to more precisely map causal genes. METHODS: Genotyping and ZNRD1 gene resequencing for 208 HIV-positive subjects (119 who experienced long-term nonprogression [LTNP] and 89 who experienced normal disease progression) was done by either TaqMan genotyping assays or direct sequencing. Genetic association analysis was performed with the SNPassoc package and Haploview software. siRNA and short hairpin RNA (shRNA) specifically targeting ZNRD1 were used to transiently or stably down-regulate ZNRD1 expression in both lymphoid and nonlymphoid cells. Cells were infected with X4 and R5 HIV strains, and efficiency of infection was assessed by reporter gene assay or p24 assay. RESULTS: Genetic association analysis found a strong statistically significant correlation with the LTNP phenotype (single-nucleotide polymorphism rs1048412; [Formula: see text]), independently of HLA-A10 influence. siRNA-based functional analysis showed that ZNRD1 down-regulation by siRNA or shRNA impaired HIV-1 replication at the transcription level in both lymphoid and nonlymphoid cells. CONCLUSION: Genetic association analysis unequivocally identified ZNRD1 as an independent marker of LTNP to AIDS. Moreover, in vitro experiments pointed to viral transcription as the inhibited step. Thus, our data strongly suggest that ZNRD1 is a host cellular factor that influences HIV-1 replication and disease progression in HIV-positive individuals.

A genome-wide approach accounting for body mass index identifies genetic variants influencing fasting glycemic traits and insulin resistance.

Recent genome-wide association studies have described many loci implicated in type 2 diabetes (T2D) pathophysiology and β-cell dysfunction but have contributed little to the understanding of the genetic basis of insulin resistance. We hypothesized that genes implicated in insulin resistance pathways might be uncovered by accounting for differences in body mass index (BMI) and potential interactions between BMI and genetic variants. We applied a joint meta-analysis approach to test associations with fasting insulin and glucose on a genome-wide scale. We present six previously unknown loci associated with fasting insulin at P < 5 × 10(-8) in combined discovery and follow-up analyses of 52 studies comprising up to 96,496 non-diabetic individuals. Risk variants were associated with higher triglyceride and lower high-density lipoprotein (HDL) cholesterol levels, suggesting a role for these loci in insulin resistance pathways. The discovery of these loci will aid further characterization of the role of insulin resistance in T2D pathophysiology.

A new highly penetrant form of obesity due to deletions on chromosome 16p11.2.

Obesity has become a major worldwide challenge to public health, owing to an interaction between the Western 'obesogenic' environment and a strong genetic contribution. Recent extensive genome-wide association studies (GWASs) have identified numerous single nucleotide polymorphisms associated with obesity, but these loci together account for only a small fraction of the known heritable component. Thus, the 'common disease, common variant' hypothesis is increasingly coming under challenge. Here we report a highly penetrant form of obesity, initially observed in 31 subjects who were heterozygous for deletions of at least 593 kilobases at 16p11.2 and whose ascertainment included cognitive deficits. Nineteen similar deletions were identified from GWAS data in 16,053 individuals from eight European cohorts. These deletions were absent from healthy non-obese controls and accounted for 0.7% of our morbid obesity cases (body mass index (BMI) >or= 40 kg m(-2) or BMI standard deviation score >or= 4; P = 6.4 x 10(-8), odds ratio 43.0), demonstrating the potential importance in common disease of rare variants with strong effects. This highlights a promising strategy for identifying missing heritability in obesity and other complex traits: cohorts with extreme phenotypes are likely to be enriched for rare variants, thereby improving power for their discovery. Subsequent analysis of the loci so identified may well reveal additional rare variants that further contribute to the missing heritability, as recently reported for SIM1 (ref. 3). The most productive approach may therefore be to combine the 'power of the extreme' in small, well-phenotyped cohorts, with targeted follow-up in case-control and population cohorts.

Genome-Wide Prediction Methods in Highly Diverse and Heterozygous Species: Proof-of-Concept through Simulation in Grapevine.

Nowadays, genome-wide association studies (GWAS) and genomic selection (GS) methods which use genome-wide marker data for phenotype prediction are of much potential interest in plant breeding. However, to our knowledge, no studies have been performed yet on the predictive ability of these methods for structured traits when using training populations with high levels of genetic diversity. Such an example of a highly heterozygous, perennial species is grapevine. The present study compares the accuracy of models based on GWAS or GS alone, or in combination, for predicting simple or complex traits, linked or not with population structure. In order to explore the relevance of these methods in this context, we performed simulations using approx 90,000 SNPs on a population of 3,000 individuals structured into three groups and corresponding to published diversity grapevine data. To estimate the parameters of the prediction models, we defined four training populations of 1,000 individuals, corresponding to these three groups and a core collection. Finally, to estimate the accuracy of the models, we also simulated four breeding populations of 200 individuals. Although prediction accuracy was low when breeding populations were too distant from the training populations, high accuracy levels were obtained using the sole core-collection as training population. The highest prediction accuracy was obtained (up to 0.9) using the combined GWAS-GS model. We thus recommend using the combined prediction model and a core-collection as training population for grapevine breeding or for other important economic crops with the same characteristics.

Genetic aspects of normal and disturbed sleep.

Sleep disorders commonly involve genetic susceptibility, environmental effects, and interactions between these factors. The heritability of sleep patterns has been shown in studies of monozygotic twins, and sleep electroencephalogram patterns offer a unique genetic fingerprint which may assist in the identification of genes involved in the regulation of sleep. Genetic factors are also thought to play a role in sleep disorders; narcolepsy is a disabling sleep condition and research has revealed the complexity of underlying genetic and environmental influences in the development of this disorder. An understanding of sleep regulation at the molecular level is essential in the identification of new targets for the treatment of sleep disorders, and genome-wide association studies for both normal sleep and sleep disorders may shed new light on the molecular architecture of mechanisms regulating these behaviours.

Genetics of Parkinson's disease: the yield.

The discovery of genes implicated in familial forms of Parkinson's disease (PD) has provided new insights into the molecular events leading to neurodegeneration. Clinically, patients with genetically determined PD can be difficult to distinguish from those with sporadic PD. Monogenic causes include autosomal dominantly (SNCA, LRRK2, VPS35, EIF4G1) as well as recessively (PARK2, PINK1, DJ-1) inherited mutations. Additional recessive forms of parkinsonism present with atypical signs, including very early disease onset, dystonia, dementia and pyramidal signs. New techniques in the search for phenotype-associated genes (next-generation sequencing, genome-wide association studies) have expanded the spectrum of both monogenic PD and variants that alter risk to develop PD. Examples of risk genes include the two lysosomal enzyme coding genes GBA and SMPD1, which are associated with a 5-fold and 9-fold increased risk of PD, respectively. It is hoped that further knowledge of the genetic makeup of PD will allow designing treatments that alter the course of the disease.

Gene-Age Interactions in Blood Pressure Regulation: A Large-Scale Investigation with the CHARGE, Global BPgen, and ICBP Consortia.

Although age-dependent effects on blood pressure (BP) have been reported, they have not been systematically investigated in large-scale genome-wide association studies (GWASs). We leveraged the infrastructure of three well-established consortia (CHARGE, GBPgen, and ICBP) and a nonstandard approach (age stratification and metaregression) to conduct a genome-wide search of common variants with age-dependent effects on systolic (SBP), diastolic (DBP), mean arterial (MAP), and pulse (PP) pressure. In a two-staged design using 99,241 individuals of European ancestry, we identified 20 genome-wide significant (p ≤ 5 × 10(-8)) loci by using joint tests of the SNP main effect and SNP-age interaction. Nine of the significant loci demonstrated nominal evidence of age-dependent effects on BP by tests of the interactions alone. Index SNPs in the EHBP1L1 (DBP and MAP), CASZ1 (SBP and MAP), and GOSR2 (PP) loci exhibited the largest age interactions, with opposite directions of effect in the young versus the old. The changes in the genetic effects over time were small but nonnegligible (up to 1.58 mm Hg over 60 years). The EHBP1L1 locus was discovered through gene-age interactions only in whites but had DBP main effects replicated (p = 8.3 × 10(-4)) in 8,682 Asians from Singapore, indicating potential interethnic heterogeneity. A secondary analysis revealed 22 loci with evidence of age-specific effects (e.g., only in 20 to 29-year-olds). Age can be used to select samples with larger genetic effect sizes and more homogenous phenotypes, which may increase statistical power. Age-dependent effects identified through novel statistical approaches can provide insight into the biology and temporal regulation underlying BP associations.