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Haplotype Association Analysis (haplotype + association_analysis)

Distribution by Scientific Domains

Life Sciences	75%

Selected Abstracts

Haplotype association analysis for late onset diseases using nuclear family data

GENETIC EPIDEMIOLOGY, Issue 3 2006
Chun Li
Abstract In haplotype-based association studies for late onset diseases, one attractive design is to use available unaffected spouses as controls (Valle et al. [1998] Diab. Care 21:949,958). Given cases and spouses only, the standard expectation-maximization (EM) algorithm (Dempster et al. [1977] J. R. Stat. Soc. B 39:1,38) for case-control data can be used to estimate haplotype frequencies. But often we will have offspring for at least some of the spouse pairs, and offspring genotypes provide additional information about the haplotypes of the parents. Existing methods may either ignore the offspring information, or reconstruct haplotypes for the subjects using offspring information and discard data from those whose haplotypes cannot be reconstructed with high confidence. Neither of these approaches is efficient, and the latter approach may also be biased. For case-control data with some subjects forming spouse pairs and offspring genotypes available for some spouse pairs or individuals, we propose a unified, likelihood-based method of haplotype inference. The method makes use of available offspring genotype information to apportion ambiguous haplotypes for the subjects. For subjects without offspring genotype information, haplotypes are apportioned as in the standard EM algorithm for case-control data. Our method enables efficient haplotype frequency estimation using an EM algorithm and supports probabilistic haplotype reconstruction with the probability calculated based on the whole sample. We describe likelihood ratio and permutation tests to test for disease-haplotype association, and describe three test statistics that are potentially useful for detecting such an association. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. [source]

Association evidence of schizophrenia with distal genomic region of NOTCH4 in Taiwanese families

GENES, BRAIN AND BEHAVIOR, Issue 6 2007
C.-M. Liu
Evidence for association with schizophrenia has been reported for NOTCH4, although results have been inconsistent. Previous studies have focused on polymorphisms in the 5, promoter region and first exon of NOTCH4. Our aim was to test the association of the entire genomic region of NOTCH4 in 218 families with at least two siblings affected by schizophrenia in Taiwan. We genotyped seven single nucleotide polymorphisms (SNPs) of this gene, with average intermarker distances of 5.3 kb. Intermarker linkage disequilibrium (LD) was calculated using gold software, and single-locus and haplotype association analyses were performed using transmit software. We found that the T allele of SNP rs2071285 (P= 0.035) and the G allele of SNP rs204993 (P= 0.0097) were significantly preferentially transmitted to the affected individuals in the single-locus association analysis. The two SNPs were in high LD (D, > 0.8). Trend for overtransmission was shown for the T-G haplotype of the two SNPs to affected individuals (P= 0.053), with the A-A haplotype significantly undertransmitted (P= 0.034). The associated region distributed across the distal portion of the NOTCH4 gene and overlapped with the genomic region of the G-protein signaling modulator 3 and pre-B-cell leukemia transcription factor 2. In summary, we found modest association evidence between schizophrenia and the distal genomic region of NOTCH4 in this Taiwanese family sample. Further replication for association with the distal genomic region of NOTCH4 is warranted. [source]

Haplotype analysis in the presence of informatively missing genotype data

GENETIC EPIDEMIOLOGY, Issue 4 2006
Nianjun Liu
Abstract It is common to have missing genotypes in practical genetic studies, but the exact underlying missing data mechanism is generally unknown to the investigators. Although some statistical methods can handle missing data, they usually assume that genotypes are missing at random, that is, at a given marker, different genotypes and different alleles are missing with the same probability. These include those methods on haplotype frequency estimation and haplotype association analysis. However, it is likely that this simple assumption does not hold in practice, yet few studies to date have examined the magnitude of the effects when this simplifying assumption is violated. In this study, we demonstrate that the violation of this assumption may lead to serious bias in haplotype frequency estimates, and haplotype association analysis based on this assumption can induce both false-positive and false-negative evidence of association. To address this limitation in the current methods, we propose a general missing data model to characterize missing data patterns across a set of two or more markers simultaneously. We prove that haplotype frequencies and missing data probabilities are identifiable if and only if there is linkage disequilibrium between these markers under our general missing data model. Simulation studies on the analysis of haplotypes consisting of two single nucleotide polymorphisms illustrate that our proposed model can reduce the bias both for haplotype frequency estimates and association analysis due to incorrect assumption on the missing data mechanism. Finally, we illustrate the utilities of our method through its application to a real data set. Genet. Epidemiol. 2006. © 2006 Wiley-Liss, Inc. [source]

Interleukin-1 gene cluster variants with innate cytokine production profiles and osteoarthritis in subjects from the Genetics, Osteoarthritis and Progression Study

ARTHRITIS & RHEUMATISM, Issue 4 2010
Ingrid Meulenbelt
Objective To assess whether genetic variation in the interleukin-1 (IL-1) gene cluster contributes to familial osteoarthritis (OA) by influencing innate ex vivo production of IL-1, or IL-1 receptor antagonist (IL-1Ra). Methods Innate ex vivo IL-1, and IL-1Ra production upon lipopolysaccharide (LPS) stimulation of whole blood cells was measured in subjects from the Genetics, Osteoarthritis and Progression (GARP) Study, which includes sibling pairs in which at least one sibling has symptomatic OA at multiple sites. Radiographic OA (ROA) was assessed by Kellgren/Lawrence score. Subjects from the GARP Study and controls from the Rotterdam Study were genotyped for 7 single-nucleotide polymorphisms (SNPs) encompassing the IL-1 gene cluster on chromosome 2q13. Linkage disequilibrium analysis and genotype and haplotype association analysis were performed to assess the relationship between the IL-1 gene cluster SNPs, innate ex vivo cytokine production, and OA. Results Among subjects in the GARP Study, the haplotype variable-number tandem repeat in intron 2/T+8006C/T+11100C 2/2/1 of the IL1RN gene was significantly associated with reduced innate ex vivo bioavailability of IL-1, upon LPS stimulation (P = 0.026) and with ROA at the highest number of joint locations. Conclusion These results show that genetic variation at the IL-1 gene cluster is associated with lower IL-1, bioavailability and with OA at a large number of joint locations. The data further indicate that, among subjects with OA affecting the highest number of joints, the innate immune system may be activated, thereby obscuring possible underlying mechanisms. [source]