Unknown

Dataset Information

0

Exploring Impact of Rare Variation in Systemic Lupus Erythematosus by a Genome Wide Imputation Approach.


ABSTRACT: The importance of low frequency and rare variation in complex disease genetics is difficult to estimate in patient populations. Genome-wide association studies are therefore, underpowered to detect rare variation. We have used a combined approach of genome-wide-based imputation with a highly stringent sequence kernel association (SKAT) test and a case-control burden test. We identified 98 candidate genes containing rare variation that in aggregate show association with SLE many of which have recognized immunological function, but also function and expression related to relevant tissues such as the joints, skin, blood or central nervous system. In addition we also find that there is a significant enrichment of genes annotated for disease-causing mutations in the OMIM database, suggesting that in complex diseases such as SLE, such mutations may be involved in subtle or combined phenotypes or could accelerate specific organ abnormalities found in the disease. We here provide an important resource of candidate genes for SLE.

SUBMITTER: Martinez-Bueno M 

PROVIDER: S-EPMC6399402 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature

altmetric image

Publications

Exploring Impact of Rare Variation in Systemic Lupus Erythematosus by a Genome Wide Imputation Approach.

Martínez-Bueno Manuel M   Alarcón-Riquelme Marta E ME  

Frontiers in immunology 20190226


The importance of low frequency and rare variation in complex disease genetics is difficult to estimate in patient populations. Genome-wide association studies are therefore, underpowered to detect rare variation. We have used a combined approach of genome-wide-based imputation with a highly stringent sequence kernel association (SKAT) test and a case-control burden test. We identified 98 candidate genes containing rare variation that in aggregate show association with SLE many of which have rec  ...[more]

Similar Datasets

| S-EPMC5551313 | biostudies-other
2014-06-03 | E-GEOD-46923 | biostudies-arrayexpress
2014-06-03 | GSE46923 | GEO
| S-EPMC1440614 | biostudies-literature
| S-EPMC2048842 | biostudies-literature
| S-EPMC6261406 | biostudies-literature
| PRJNA203032 | ENA
| S-EPMC11815458 | biostudies-literature
| S-EPMC4185017 | biostudies-literature
| S-EPMC3042628 | biostudies-other