A Strategy analysis for genetic association studies with known inbreeding

Background: Association studies consist in identifying the genetic variants which are related to a specific disease through the use of statistical multiple hypothesis testing or segregation analysis in pedigrees. This type of studies has been very successful in the case of Mendelian monogenic disorders while it has been less successful in identifying genetic variants related to complex diseases where the insurgence depends on the interactions between different genes and the environment. The current technology allows to genotype more than a million of markers and this number has been rapidly increasing in the last years with the imputation based on templates sets and whole genome sequencing. This type of data introduces a great amount of noise in the statistical analysis and usually requires a great number of samples. Current methods seldom take into account gene-gene and gene-environment interactions which are fundamental especially in complex diseases. In this paper we propose to use a non-parametric additive model to detect the genetic variants related to diseases which accounts for interactions of unknown order. Although this is not new to the current literature, we show that in an isolated population, where the most related subjects share also most of their genetic code, the use of additive models may be improved if the available genealogical tree is taken into account. Specifically, we form a sample of cases and controls with the highest inbreeding by means of the Hungarian method, and estimate the set of genes/environmental variables, associated with the disease, by means of Random Forest. Results: We have evidence, from statistical theory, simulations and two applications, that we build a suitable procedure to eliminate stratification between cases and controls and that it also has enough precision in identifying genetic variants responsible for a disease. This procedure has been successfully used for the betathalassemia, which is a well known Mendelian disease, and also to the common asthma where we have identified candidate genes that underlie to the susceptibility of the asthma. Some of such candidate genes have been also found related to common asthma in the current literature. Conclusions: The data analysis approach, based on selecting the most related cases and controls along with the Random Forest model, is a powerful tool for detecting genetic variants associated to a disease in isolated populations. Moreover, this method provides also a prediction model that has accuracy in estimating the unknown disease status and that can be generally used to build kit tests for a wide class of Mendelian diseases

Methylenetetrahydrofolate Reductase Gene Polymorphisms in Burkina Faso: Impact on Plasma Fasting Homocysteine and after Methionine Loading Test

SUMMARY In Burkina Faso the levels of plasma homocysteine (Hcy) are lower and the methionine loading tests suggest a more effective Hcy metabolism. The polymorphisms of methylenetetrahydrofolate reductase (MTHFR) showed a relevant difference in the allele frequencies of T MTHFR-677 in young and in old subjects, while the allele frequency of C MTHFR-1298C was comparable in young and old subjects. The aim of this paper was to study the impact of the MTHFR polymorphisms on plasma fasting Hcy and after methionine loading in Burkina Faso. The young subjects with CC MTHFR-677 genotype had levels of Hcy significantly lower than CT and TT subjects. The level of Hcy in subjects who had AA, AC and CC MTHFR-1298 genotypes were comparable. The levels of Hcy after the methionine loading test were significantly higher in CT and TT MTHFR-677 genotype. These results suggest that the genetic situation in Burkina Faso is different from that of other Western countries and this guarantees the maintenance of lower plasma levels of Hcy in young and old Africans. The elevated levels of plasma Hcy in old subjects compared to young subjects, against the low prevalence of the T allele in elderly subjects is discussed. (Clin. Lab. 2007;53:XXX-XXX) KEY WORDS Burkina Faso, homocysteine, methionine loading test, MTHFR, C677T, A1298

Microsatellites and SNPs linkage analysis in a Sardinian genetic isolate confirms several essential hypertension loci previously identified in different populations

Background. A multiplicity of study designs such as gene candidate analysis, genome wide search (GWS) and, recently, whole genome association studies have been employed for the identification of the genetic components of essential hypertension (EH). Several genome-wide linkage studies of EH and blood pressure-related phenotypes demonstrate that there is no single locus with a major effect while several genomic regions likely to contain EH-susceptibility loci were validated by multiple studies. Methods. We carried out the clinical assessment of the entire adult population in a Sardinian village (Talana) and we analyzed 16 selected families with 62 hypertensive subjects out of 267 individuals. We carried out a double GWS using a set of 902 uniformly spaced microsatellites and a high-density SNPs map on the same group of families. Results. Three loci were identified by both microsatellites and SNP scans and the obtained linkage results showed a remarkable degree of similarity. These loci were identified on chromosome 2q24, 11q23.1–25 and 13q14.11–21.33. Further support to these findings is their broad description present in literature associated to EH or related phenotypes. Bioinformatic investigation of these loci shows several potential EH candidate genes, several of whom already associated to blood pressure regulation pathways. Conclusion. Our search for major susceptibility EH genetic factors evidences that EH in the genetic isolate of Talana is due to the contribution of several genes contained in loci identified and replicated by earlier findings in different human populations

Exome sequencing in Crisponi/CISS-like individuals reveals unpredicted alternative diagnoses

Crisponi/cold‐induced sweating syndrome (CS/CISS) is a rare autosomal recessive disorder characterized by a complex phenotype (hyperthermia and feeding difficulties in the neonatal period, followed by scoliosis and paradoxical sweating induced by cold since early childhood) and a high neonatal lethality. CS/CISS is a genetically heterogeneous disorder caused by mutations in CRLF1 (CS/CISS1), CLCF1 (CS/CISS2) and KLHL7 (CS/CISS‐like). Here, a whole exome sequencing approach in individuals with CS/CISS‐like phenotype with unknown molecular defect revealed unpredicted alternative diagnoses. This approach identified putative pathogenic variations in NALCN, MAGEL2 and SCN2A. They were already found implicated in the pathogenesis of other syndromes, respectively the congenital contractures of the limbs and face, hypotonia, and developmental delay syndrome, the Schaaf‐Yang syndrome, and the early infantile epileptic encephalopathy‐11 syndrome. These results suggest a high neonatal phenotypic overlap among these disorders and will be very helpful for clinicians. Genetic analysis of these genes should be considered for those cases with a suspected CS/CISS during neonatal period who were tested as mutation negative in the known CS/CISS genes, because an expedited and corrected diagnosis can improve patient management and can provide a specific clinical follow‐up

Application of a new method for GWAS in a related case/control sample with known pedigree structure: identification of new loci for nephrolithiasis

In contrast to large GWA studies based on thousands of individuals and large meta-analyses combining GWAS results, we analyzed a small case/control sample for uric acid nephrolithiasis. Our cohort of closely related individuals is derived from a small, genetically isolated village in Sardinia, with well-characterized genealogical data linking the extant population up to the 16(th) century. It is expected that the number of risk alleles involved in complex disorders is smaller in isolated founder populations than in more diverse populations, and the power to detect association with complex traits may be increased when related, homogeneous affected individuals are selected, as they are more likely to be enriched with and share specific risk variants than are unrelated, affected individuals from the general population. When related individuals are included in an association study, correlations among relatives must be accurately taken into account to ensure validity of the results. A recently proposed association method uses an empirical genotypic covariance matrix estimated from genome-screen data to allow for additional population structure and cryptic relatedness that may not be captured by the genealogical data. We apply the method to our data, and we also investigate the properties of the method, as well as other association methods, in our highly inbred population, as previous applications were to outbred samples. The more promising regions identified in our initial study in the genetic isolate were then further investigated in an independent sample collected from the Italian population. Among the loci that showed association in this study, we observed evidence of a possible involvement of the region encompassing the gene LRRC16A, already associated to serum uric acid levels in a large meta-analysis of 14 GWAS, suggesting that this locus might lead a pathway for uric acid metabolism that may be involved in gout as well as in nephrolithiasis

High Differentiation among Eight Villages in a Secluded Area of Sardinia Revealed by Genome-Wide High Density SNPs Analysis

To better design association studies for complex traits in isolated populations it's important to understand how history and isolation moulded the genetic features of different communities. Population isolates should not “a priori” be considered homogeneous, even if the communities are not distant and part of a small region. We studied a particular area of Sardinia called Ogliastra, characterized by the presence of several distinct villages that display different history, immigration events and population size. Cultural and geographic isolation characterized the history of these communities. We determined LD parameters in 8 villages and defined population structure through high density SNPs (about 360 K) on 360 unrelated people (45 selected samples from each village). These isolates showed differences in LD values and LD map length. Five of these villages show high LD values probably due to their reduced population size and extreme isolation. High genetic differentiation among villages was detected. Moreover population structure analysis revealed a high correlation between genetic and geographic distances. Our study indicates that history, geography and biodemography have influenced the genetic features of Ogliastra communities producing differences in LD and population structure. All these data demonstrate that we can consider each village an isolate with specific characteristics. We suggest that, in order to optimize the study design of complex traits, a thorough characterization of genetic features is useful to identify the presence of sub-populations and stratification within genetic isolates

A Genomewide Search Using an Original Pairwise Sampling Approach for Large Genealogies Identifies a New Locus for Total and Low-Density Lipoprotein Cholesterol in Two Genetically Differentiated Isolates of Sardinia

A powerful approach to mapping the genes for complex traits is to study isolated founder populations, in which genetic heterogeneity and environmental noise are likely to be reduced and in which extended genealogical data are often available. Using graph theory, we applied an approach that involved sampling from the large number of pairwise relationships present in an extended genealogy to reconstruct sets of subpedigrees that maximize the useful information for linkage mapping while minimizing calculation burden. We investigated, through simulation, the properties of the different sets in terms of bias in identity-by-descent (IBD) estimation and power decrease under various genetic models. We applied this approach to a small isolated population from Sardinia, the village of Talana, consisting of a unique large and complex pedigree, and performed a genomewide search through variance-components linkage analysis for serum lipid levels. We identified a region of significant linkage on chromosome 2 for total serum cholesterol and low-density lipoprotein (LDL) cholesterol. Through higher-density mapping, we obtained an increased linkage for both traits on 2q21.2-q24.1, with a LOD score of 4.3 for total serum cholesterol and of 3.9 for LDL cholesterol. A replication study was performed in an independent and larger set from a genetically differentiated isolated population of the same region of Sardinia, the village of Perdasdefogu. We obtained consistent linkage to the region for total serum cholesterol (LOD score 1.4) and LDL cholesterol (LOD score 2.2), with a level of concordance uncommon for complex traits, and refined the location of the quantitative-trait locus. Interestingly, the 2q21.1-22 region has also been linked to premature coronary heart disease in Finns, and, in the adjacent 2q14 region, significant linkage with triglycerides has been reported in Hutterites