Abstract
Systemic Autoimmune Diseases, a group of chronic inflammatory conditions, have variable symptoms and difficult diagnosis. In order to reclassify them based on genetic markers rather than clinical criteria, we performed clustering of Single Nucleotide Polymorphisms. However naive approaches tend to group patients primarily by their geographic origin. To reduce this “ancestry signal”, we developed SNPClust, a method to select large sources of ancestry-independent genetic variations from all variations detected by Principal Component Analysis. Applied to a Systemic Lupus Erythematosus case control dataset, SNPClust successfully reduced the ancestry signal. Results were compared with association studies between the cases and controls without or with reference population stratification correction methods. SNPClust amplified the disease discriminating signal and the ratio of significant associations outside the HLA locus was greater compared to population stratification correction methods. SNPClust will enable the use of ancestry-independent genetic information in the reclassification of Systemic Autoimmune Diseases. SNPClust is available as an R package and demonstrated on the public Human Genome Diversity Project dataset at https://github.com/ThomasChln/snpclust.
Highlights
The PRECISESADS project aims at reclassifying Systemic Autoimmune Diseases (SADs), a group of chronic inflammatory conditions characterized by the presence of unspecific autoantibodies in the serum and serious clinical consequences, based on genetic and molecular biomarkers rather than clinical criteria
The most important non-ancestry-based source of genetic variation in the Principal Component Analysis (PCA) appeared on principal component 3, confirming that the ancestry signal is much stronger than clinically relevant signals in clustering approaches
The ancestry information is contained in many Single Nucleotide Polymorphisms (SNPs) across the genome, and may be present in clinically relevant SNPs, in particular in auto-immune diseases where the HLA locus is involved
Summary
The PRECISESADS project aims at reclassifying Systemic Autoimmune Diseases (SADs), a group of chronic inflammatory conditions characterized by the presence of unspecific autoantibodies in the serum and serious clinical consequences, based on genetic and molecular biomarkers rather than clinical criteria. SADs affect 1% of the global population [1] and have limited treatment options and difficult diagnosis. The diseases studied in PRECISESADS are Systemic Lupus Erythematosus (SLE), Systemic Sclerosis, Rheumatoid Arthritis, Sjögren’s Syndrome, Primary Antiphospholipid Antibody Syndrome, and undifferentiated cases.
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