Cathepsin S genotypes are associated with Apo-A1 and HDL-cholesterol in lean and obese French populations.

Cathepsin S (CTSS) is a cysteine protease that has a central role in remodeling the extracellular matrix and, as such, has been implicated in the etiology of cardiovascular disease. This study used five tag single nucleotide polymorphisms (tSNPs) to screen the CTSS gene in healthy lean (n = 1891) and obese French populations (n = 477) for their association with various phenotypes: body mass index, waist-to-hip ratio, glycemia, total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (Apo-A1) and apolipoprotein B. Significant associations were identified between rs11576175 tSNP (A/G) and Apo-A1 and HDL-C plasma levels in a sex-specific manner. Lean female subjects homozygous for the minor A-allele had higher levels of circulating Apo-A1 (p = 0.0003), while lean male A/A carriers had higher levels of HDL-C (p = 0.007) compared with the other genotypes. In the obese cohort, associations were found between three tSNPs and Apo-A1 levels in adult female subjects: rs10888390 (G/A), p = 0.01; rs10888394 (T/C), p = 0.03; and rs1136774 (C/T), p = 0.02; however, only rs10888390 remained significant in a combined model (p = 0.03). These results provide the first evidence that CTSS sequence variations are associated with two human metabolic risk factors for cardiovascular diseases: plasma Apo-A1 and HDL-C concentrations.

Promoter adiponectin polymorphisms and waist/hip ratio variation in a prospective French adults study.

BACKGROUND: Adiponectin expression and plasma concentrations are decreased in human and animal models of obesity. Several single nucleotide polymorphisms (SNPs) in the adiponectin gene are known to influence the plasmatic concentration of the encoded protein. Some of these adiponectin polymorphisms have been associated with BMI in cross-sectional studies. OBJECTIVE: The aim of our study was to examine the longitudinal relationships between adiponectin gene polymorphisms and anthropometric indices. DESIGN: Two adiponectin gene (ADIPOQ) SNPs, -11391G>A and -11377C>G, were genotyped in 837 French Caucasian subjects from the SUpplémentation en VItamines et Minéraux Anti-oXydants (SU.VI.MAX) cohort. Anthropometric scores were measured at three clinical examinations over a 7-year period. RESULTS: For -11391G>A as well as for -11377C>G, we detected no association between the variant allele and anthropometric measurements at baseline. Considering longitudinal effects, we detected moderately higher waist-to-hip ratio (WHR) changes for the carriers of the -11391A (P=0.02) and -11377C (P=0.03) allele over the follow-up of the study. -11391G>A and -11377C>G define haplotypes associated also with WHR measurements and their changes over the follow-up of the study. Diploid configurations that combine -11391A and -11377C were associated with significantly higher WHR changes (DeltaCE: P=0.02) compared to other haplotypes. In addition, higher adiponectin levels were observed in AC/AC diplotypes compared to GG/GG carriers (P<0.0001). CONCLUSION: In the SU.VI.MAX study, genetic variations in the adiponectin gene affect abdominal fat gain over life span.

Estimating haplotype relative risks in complex disease from unphased SNPs data in families using a likelihood adjusted for ascertainment.

The understanding of complex diseases and insights to improve their medical management may be achieved through the deduction of how specific haplotypes may play a joint effect to change relative risk information. In this paper we describe an ascertainment adjusted likelihood-based method to estimate haplotype relative risks using pooled family data coming from association and/or linkage studies that were used to identify specific haplotypes. Haplotype-based analysis tends to require a large amount of parameters to capture all the information that leads to efficiency problems. An adaptation of the Stochastic Expectation Maximization algorithm is used for haplotypes inference from genotypic data and to reduce the number of nuisance parameters for risk estimation. Using different simulations, we show that this method provides unbiased relative risk estimates even in case of departure from Hardy-Weinberg equilibrium.

Haplotypes in the gene encoding protein kinase c-beta (PRKCB1) on chromosome 16 are associated with autism.

Autism is a developmental disorder characterized by impairments in social interaction and communication associated with repetitive patterns of interest or behavior. Autism is highly influenced by genetic factors. Genome-wide linkage and candidate gene association approaches have been used to try and identify autism genes. A few loci have repeatedly been reported linked to autism. Several groups reported evidence for linkage to a region on chromosome 16p. We have applied a direct physical identity-by-descent (IBD) mapping approach to perform a high-density (0.85 megabases) genome-wide linkage scan in 116 families from the AGRE collection. Our results confirm linkage to a region on chromosome 16p with autism. High-resolution single-nucleotide polymorphism (SNP) genotyping and analysis of this region show that haplotypes in the protein kinase c-beta gene are strongly associated with autism. An independent replication of the association in a second set of 167 trio families with autism confirmed our initial findings. Overall, our data provide evidence that the PRKCB1 gene on chromosome 16p may be involved in the etiology of autism.

The art of pedigree drawing: algorithmic aspects.

MOTIVATION: Giving a meaningful representation of a pedigree is not obvious when it includes consanguinity loops, individuals with multiple mates or several related families. RESULTS: We show that finding a perfectly meaningful representation of a pedigree is equivalent to the interval graph sandwich problem and we propose an algorithm for drawing pedigrees.

Sib-pair linkage analysis of alcohol dependence taking into account covariates and age-of-onset variability: evaluation of the residual approach.

The construction of residuals allowed us to consider a phenotype related to alcohol dependence (ALDX1) adjusted for age, gender and current smoking status. Using the Haseman and Elston regression test, we compared genome scan results for detection of loci for the unadjusted and adjusted ALDX1 phenotypes in the Collaborative Study on the Genetics of Alcoholism (COGA) data. More markers were significant at the 1% level for the binary than for the residual analyses. Overall, our residual analyses do not show substantial improvement in their ability to detect linkage for alcohol dependence in the COGA data. This may be due to the relatively small sample size of discordant sib pairs.