TY  - JOUR
AU  - Ionita-Laza, Iuliana
AU  - Buxbaum, Joseph D
AU  - Laird, Nan M
AU  - Lange, Christoph
TI  - A new testing strategy to identify rare variants with either risk or protective effect on disease.
JO  - PLoS Genetics
VL  - 7
IS  - 2
SN  - 1553-7404
CY  - San Francisco, Calif.
PB  - Public Library of Science
M1  - DZNE-2020-02504
SP  - e1001289
PY  - 2011
AB  - Rapid advances in sequencing technologies set the stage for the large-scale medical sequencing efforts to be performed in the near future, with the goal of assessing the importance of rare variants in complex diseases. The discovery of new disease susceptibility genes requires powerful statistical methods for rare variant analysis. The low frequency and the expected large number of such variants pose great difficulties for the analysis of these data. We propose here a robust and powerful testing strategy to study the role rare variants may play in affecting susceptibility to complex traits. The strategy is based on assessing whether rare variants in a genetic region collectively occur at significantly higher frequencies in cases compared with controls (or vice versa). A main feature of the proposed methodology is that, although it is an overall test assessing a possibly large number of rare variants simultaneously, the disease variants can be both protective and risk variants, with moderate decreases in statistical power when both types of variants are present. Using simulations, we show that this approach can be powerful under complex and general disease models, as well as in larger genetic regions where the proportion of disease susceptibility variants may be small. Comparisons with previously published tests on simulated data show that the proposed approach can have better power than the existing methods. An application to a recently published study on Type-1 Diabetes finds rare variants in gene IFIH1 to be protective against Type-1 Diabetes.
KW  - Algorithms
KW  - Computer Simulation
KW  - DEAD-box RNA Helicases: genetics
KW  - Data Interpretation, Statistical
KW  - Diabetes Mellitus, Type 1: genetics
KW  - Genetic Predisposition to Disease
KW  - Genetic Testing: statistics & numerical data
KW  - Genetic Variation
KW  - Genome-Wide Association Study: statistics & numerical data
KW  - Haplotypes: genetics
KW  - Humans
KW  - Interferon-Induced Helicase, IFIH1
KW  - Risk Factors
KW  - Sequence Analysis, DNA
KW  - IFIH1 protein, human (NLM Chemicals)
KW  - DEAD-box RNA Helicases (NLM Chemicals)
KW  - Interferon-Induced Helicase, IFIH1 (NLM Chemicals)
LB  - PUB:(DE-HGF)16
C6  - pmid:21304886
C2  - pmc:PMC3033379
DO  - DOI:10.1371/journal.pgen.1001289
UR  - https://pub.dzne.de/record/136182
ER  -