Publications by authors named "P M A Sleiman"
Objective: Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups.
Results: Precise SNP tracking showed no sample swap errors within the clinical testing laboratories.
Atopic dermatitis (AD) is a common inflammatory skin condition and prior genome-wide association studies (GWAS) have identified 71 associated loci. In the current study we conducted the largest AD GWAS to date (discovery N = 1,086,394, replication N = 3,604,027), combining previously reported cohorts with additional available data. We identified 81 loci (29 novel) in the European-only analysis (which all replicated in a separate European analysis) and 10 additional loci in the multi-ancestry analysis (3 novel).
View Article and Find Full Text PDFObjective: Data from DNA genotyping via a 96-SNP panel in a study of 25,015 clinical samples were utilized for quality control and tracking of sample identity in a clinical sequencing network. The study aimed to demonstrate the value of both the precise SNP tracking and the utility of the panel for predicting the sex-by-genotype of the participants, to identify possible sample mix-ups.
Results: Precise SNP tracking showed no sample swap errors within the clinical testing laboratories.
Background & Aims: Biliary atresia (BA) is poorly understood and leads to liver transplantation (LT), with the requirement for and associated risks of lifelong immunosuppression, in most children. We performed a genome-wide association study (GWAS) to determine the genetic basis of BA.
Methods: We performed a GWAS in 811 European BA cases treated with LT in US, Canadian and UK centers, and 4,654 genetically matched controls.
Article Synopsis
- The project is a partnership between the IHCC and DAC aimed at creating a genomic risk assessment tool for Alzheimer's disease that incorporates data from diverse ethnic backgrounds.
- The GIRA model combines genetic factors, like polygenic risk scores and specific gene haplotypes, with non-genetic data such as age and sex.
- Early findings show the GIRA model can effectively identify individuals at higher risk for Alzheimer's, with implications for future clinical use and research.