It is well established that gene interactions influence common human diseases, but to date linkage studies have been constrained to searching for single genes across the genome. We applied a novel approach to uncover significant gene-gene interactions in a systematic two-dimensional (2D) genome-scan of essential hypertension. The study cohort comprised 2076 affected sib-pairs and 66 affected half-sib-pairs of the British Genetics of HyperTension study. Extensive simulations were used to establish significance thresholds in the context of 2D genome-scans. Our analyses found significant and suggestive evidence for loci on chromosomes 5, 9, 11, 15, 16 and 19, which influence hypertension when gene-gene interactions are taken into account (5q13.1 and 11q22.1, two-locus lod score=5.72; 5q13.1 and 19q12, two-locus lod score=5.35; 9q22.3 and 15q12, two-locus lod score=4.80; 16p12.3 and 16q23.1, two-locus lod score=4.50). For each significant and suggestive pairwise interaction, the two-locus genetic model that best fitted the data was determined. Regions that were not detected using single-locus linkage analysis were identified in the 2D scan as contributing significant epistatic effects. This approach has discovered novel loci for hypertension and offers a unique potential to use existing data to uncover novel regions involved in complex human diseases.
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http://dx.doi.org/10.1093/hmg/ddl058 | DOI Listing |
Genetics
April 2016
Department of Biostatistics and Medical Informatics, University of Wisconsin, Madison, Wisconsin 53706
Studies of the genetic loci that contribute to variation in gene expression frequently identify loci with broad effects on gene expression: expression quantitative trait locus hotspots. We describe a set of exploratory graphical methods as well as a formal likelihood-based test for assessing whether a given hotspot is due to one or multiple polymorphisms. We first look at the pattern of effects of the locus on the expression traits that map to the locus: the direction of the effects and the degree of dominance.
View Article and Find Full Text PDFPLoS One
December 2015
Battelle Center for Mathematical Medicine, Nationwide Children's Hospital, Columbus, Ohio, United States of America; Department of Pediatrics, Wexner Medical Center, Ohio State University, Columbus, Ohio, United States of America.
Detecting gene-gene interaction in complex diseases is a major challenge for common disease genetics. Most interaction detection approaches use disease-marker associations and such methods have low power and unknown reliability in real data. We developed and tested a powerful linkage-analysis-based gene-gene interaction detection strategy based on conditioning the family data on a known disease-causing allele or disease-associated marker allele.
View Article and Find Full Text PDFGenes Immun
June 2013
Department of Human Genetics, McGill University, Montreal, Quebec, Canada.
In humans, cerebral malaria is a rare but often lethal complication of infection with Plasmodium parasites, the occurrence of which is influenced by complex genetic factors of the host. We used a mouse model of experimental cerebral malaria (ECM) with Plasmodium berghei ANKA to study genetic factors regulating appearance of neurological symptoms and associated lethality. In a genome-wide screen of N-ethyl-N-nitrosourea-mutagenized mice derived from C57BL/6J (B6) and 129S1/SvImJ (129) mouse strains, we detected a strong interaction between the genetic backgrounds of these strains, which modulates ECM resistance.
View Article and Find Full Text PDFHum Genet
April 2013
National Institute on Deafness and Other Communication Disorders, National Institutes of Health, Bethesda, MD, USA.
We describe a pedigree of 71 individuals from the Republic of Cameroon in which at least 33 individuals have a clinical diagnosis of persistent stuttering. The high concentration of stuttering individuals suggests that the pedigree either contains a single highly penetrant gene variant or that assortative mating led to multiple stuttering-associated variants being transmitted in different parts of the pedigree. No single locus displayed significant linkage to stuttering in initial genome-wide scans with microsatellite and SNP markers.
View Article and Find Full Text PDFHum Hered
January 2013
Centre de recherche de l'institut universitaire en santé mentale de Québec, Université Laval, Québec, Québec, Canada.
Objective: To increase power to detect modifier loci conferring susceptibility to specific phenotypes such as disease diagnoses which are part of a broader disorder spectrum by jointly modeling a modifier and a broad susceptibility gene and to identify modifier loci conferring specific susceptibility to schizophrenia (SZ) or to bipolar disorder (BP) using the approach.
Methods: We implemented a two-locus linkage analysis model where a gene 1 genotype increases the risk of a broad phenotype and a gene 2 genotype modifies the expression of gene 1 by conferring susceptibility to a specific phenotype.
Results: Compared to a single-locus analysis within the broad phenotype, the proposed approach had greater power to detect the modifier gene 2 (0.
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