scholarly journals Use of principal components to aggregate rare variants in case-control and family-based association studies in the presence of multiple covariates

2011 ◽  
Vol 5 (S9) ◽  
Author(s):  
Rémi Kazma ◽  
Thomas J Hoffmann ◽  
John S Witte
Keyword(s):  
Principal Components ◽  
Rare Variants ◽  
Association Studies ◽  
Case Control ◽  
Multiple Covariates ◽  
Family Based

scholarly journals Demographic history mediates the effect of stratification on polygenic scores

eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
Arslan A Zaidi ◽  
Iain Mathieson
Keyword(s):  
Principal Components ◽  
Population Stratification ◽  
Rare Variants ◽  
Association Studies ◽  
Demographic History ◽  
Hybrid Approach ◽  
Genome Wide Association Studies ◽  
Environmental Structure ◽  
Polygenic Scores ◽  
Family Based

Population stratification continues to bias the results of genome-wide association studies (GWAS). When these results are used to construct polygenic scores, even subtle biases can cumulatively lead to large errors. To study the effect of residual stratification, we simulated GWAS under realistic models of demographic history. We show that when population structure is recent, it cannot be corrected using principal components of common variants because they are uninformative about recent history. Consequently, polygenic scores are biased in that they recapitulate environmental structure. Principal components calculated from rare variants or identity-by-descent segments can correct this stratification for some types of environmental effects. While family-based studies are immune to stratification, the hybrid approach of ascertaining variants in GWAS but reestimating effect sizes in siblings reduces but does not eliminate stratification. We show that the effect of population stratification depends not only on allele frequencies and environmental structure but also on demographic history.

A nonparametric test for association with multiple loci in the retrospective case-control study

2019 ◽  
Vol 29 (2) ◽  
pp. 589-602
Author(s):  
Chan Wang ◽  
Shufang Deng ◽  
Leiming Sun ◽  
Liming Li ◽  
Yue-Qing Hu
Keyword(s):  
Rare Variants ◽  
Association Studies ◽  
Nonparametric Test ◽  
Case Control ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Retrospective Case ◽  
Multiple Loci ◽  
Common Diseases ◽  
The Difference

The genome-wide association studies aim at identifying common or rare variants associated with common diseases and explaining more heritability. It is well known that common diseases are influenced by multiple single nucleotide polymorphisms (SNPs) that are usually correlated in location or function. In order to powerfully detect association signals, it is highly desirable to take account of correlations or linkage disequilibrium (LD) information among multiple SNPs in testing for association. In this article, we propose a test SLIDE that depicts the difference of the average multi-locus genotypes between cases and controls and derive its variance–covariance matrix in the retrospective design. This matrix is composed of the pairwise LD between SNPs. Thus SLIDE can borrow the strength from an external database in the population of interest with a few thousands to hundreds of thousands individuals to improve the power for detecting association. Extensive simulations show that SLIDE has apparent superiority over the existing methods, especially in the situation involving both common and rare variants, both protective and deleterious variants. Furthermore, the efficiency of the proposed method is demonstrated in the application to the data from the Wellcome Trust Case Control Consortium.

Association of HLA Class II Alleles and Haplotypes with Type 1 Diabetes in Tunisian Arabs

2018 ◽  
Vol 127 (10) ◽  
pp. 653-662
Author(s):  
Abdelhafidh Hajjej ◽  
Wassim Y. Almawi ◽  
Mouna Stayoussef ◽  
Lasmar Hattab ◽  
Slama Hmida
Keyword(s):  
Type 1 Diabetes ◽  
Association Studies ◽  
Class Ii ◽  
Correlation Study ◽  
Case Control ◽  
Linkage Study ◽  
Hla Class Ii ◽  
Racial Background ◽  
Family Based

AbstractThe molecular association of HLA class II with type 1 diabetes (T1DM) was investigated in Tunisian Arabs using 3 kinds of analyses. The first was a case-control association study, using Relative Predispositional Effects method, involved 137 T1DM cases and 258 control subjects. The second was family-based association-linkage study, using Transmission Disequilibrium Test, and covering 50 Tunisian families comprising 73 T1DM patients and 100 parents. The third was a wide correlation study between 4 DRB1 alleles (DRB1*03, *04, *11, *15) and T1DM in 52 countries, using Spearman’s Rho. Results from Case-control and family-based association studies showed that DRB1*03 and DRB1*04 alleles predispose to T1DM in Tunisian Arabs. Conversely, only DRB1*11 was protective for T1DM. DRB1*04-DQB1*03 haplotype was consistently associated positively with T1DM; DRB1*03/DRB1*04 genotype had the highest risk of T1DM development. Compared to DRB1*03, HLA-DRB1*04 was associated with higher T1DM incidence. Thus, the contribution of HLA class II to T1DM genetic susceptibility must be evaluated with regards to specific HLA alleles, genotypes, and haplotypes, and also ethnic and racial background.

Is there a phenotypic difference between probands in case-control versus family-based association studies?

2002 ◽  
Vol 118B (1) ◽  
pp. 25-26 ◽  
Author(s):  
Thomas G. Schulze ◽  
Sven Cichon ◽  
Markus M. Nöthen ◽  
Peter Propping ◽  
Wolfgang Maier ◽  
...  
Keyword(s):  
Association Studies ◽  
Case Control ◽  
Phenotypic Difference ◽  
Control Versus ◽  
Family Based

scholarly journals Investigation of candidate genes of non-syndromic cleft lip with or without cleft palate, using both case–control and family-based association studies

Medicine ◽  
2019 ◽  
Vol 98 (26) ◽  
pp. e16170 ◽  
Author(s):  
Xing Ge ◽  
Jia-Wei Hong ◽  
Jun-Yu Shen ◽  
Zheng Li ◽  
Rui Zhang ◽  
...  
Keyword(s):  
Cleft Palate ◽  
Candidate Genes ◽  
Cleft Lip ◽  
Association Studies ◽  
Case Control ◽  
Family Based

(ii) Family-based linkage and case control association studies

2008 ◽  
Vol 22 (4) ◽  
pp. 245-250 ◽  
Author(s):  
Daniel W.H. Ho ◽  
Danny Chan ◽  
Kenneth M.C. Cheung ◽  
Pak Sham ◽  
You-Qiang Song
Keyword(s):  
Association Studies ◽  
Case Control ◽  
Family Based ◽  
Control Association

scholarly journals What Have We Learned From Family-Based Studies About Spondyloarthritis?

2021 ◽  
Vol 12 ◽  
Author(s):  
Félicie Costantino ◽  
Hendrick Mambu Mambueni ◽  
Roula Said-Nahal ◽  
Henri-Jean Garchon ◽  
Maxime Breban
Keyword(s):  
Genetic Susceptibility ◽  
Familial Aggregation ◽  
Association Studies ◽  
Case Control ◽  
Special Focus ◽  
Inflammatory Disorder ◽  
Genome Wide Association Studies ◽  
Chronic Inflammatory Disorder ◽  
Susceptibility Factors ◽  
Family Based

Spondyloarthritis (SpA) is a chronic inflammatory disorder with a high familial aggregation, emphasizing the existence of genetic susceptibility factors. In the last decades, family-based studies have contributed to better understand the genetic background of SpA, in particular by showing that the most likely model of transmission is oligogenic with multiplicative effects. Coexistence of different SpA subtypes within families also highlighted the complex interplay between all subtypes. Several whole-genome linkage analyses using sib-pairs or multiplex families were performed in the 1990s to try to identify genetic susceptibility factors besides HLA-B27. Unfortunately, no consistent results were obtained and family-based studies have been progressively set aside in favor of case-control designs. In particular, case-control genome-wide association studies allowed the identification of more than 40 susceptibility regions. However, all these loci explain only a small fraction of disease predisposition. Several hypotheses have been advanced to account for this unexplained heritability, including rare variants involvement, leading to a renewed interest in family-based designs, which are probably more powerful in the detection of such variants. In this review, our purpose is to summarize what has been learned to date regarding SpA genetics from family-based studies, with a special focus on recent identification of rare associated variants through next-generation sequencing studies.

scholarly journals Deep genotype imputation captures virtually all heritability of autoimmune vitiligo

2020 ◽  
Vol 29 (5) ◽  
pp. 859-863 ◽  
Author(s):  
Genevieve H L Roberts ◽  
Stephanie A Santorico ◽  
Richard A Spritz
Keyword(s):  
Complex Disease ◽  
Rare Variants ◽  
Association Studies ◽  
Genotype Imputation ◽  
Genome Wide Association Studies ◽  
Common Variants ◽  
Genome Wide ◽  
Autoimmune Vitiligo ◽  
Family Based ◽  
Project Data

Abstract Autoimmune vitiligo is a complex disease involving polygenic risk from at least 50 loci previously identified by genome-wide association studies. The objectives of this study were to estimate and compare vitiligo heritability in European-derived patients using both family-based and ‘deep imputation’ genotype-based approaches. We estimated family-based heritability (h2FAM) by vitiligo recurrence among a total 8034 first-degree relatives (3776 siblings, 4258 parents or offspring) of 2122 unrelated vitiligo probands. We estimated genotype-based heritability (h2SNP) by deep imputation to Haplotype Reference Consortium and the 1000 Genomes Project data in unrelated 2812 vitiligo cases and 37 079 controls genotyped genome wide, achieving high-quality imputation from markers with minor allele frequency (MAF) as low as 0.0001. Heritability estimated by both approaches was exceedingly high; h2FAM = 0.75–0.83 and h2SNP = 0.78. These estimates are statistically identical, indicating there is essentially no remaining ‘missing heritability’ for vitiligo. Overall, ~70% of h2SNP is represented by common variants (MAF > 0.01) and 30% by rare variants. These results demonstrate that essentially all vitiligo heritable risk is captured by array-based genotyping and deep imputation. These findings suggest that vitiligo may provide a particularly tractable model for investigation of complex disease genetic architecture and predictive aspects of personalized medicine.

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