Human leukocyte antigen typing using a knowledge base coupled with a high-throughput oligonucleotide probe array analysis

• Published in: Frontiers in immunology 2014-11, Vol.5, p.597-597
• Main Authors: Zhang, Guang Lan, Keskin, Derin B, Lin, Hsin-Nan, Lin, Hong Huang, DeLuca, David S, Leppanen, Scott, Milford, Edgar L, Reinherz, Ellis L, Brusic, Vladimir
• Format: Article
• Language: English
• Subjects: High-Throughput Screening Assays; HLA disease association; HLA typing; Immunology; machine learning; population typing
• ISSN: 1664-3224; 1664-3224
• DOI: 10.3389/fimmu.2014.00597

Human leukocyte antigens (HLA) are important biomarkers because multiple diseases, drug toxicity, and vaccine responses reveal strong HLA associations. Current clinical HLA typing is an elimination process requiring serial testing. We present an alternative in situ synthesized DNA-based microarray method that contains hundreds of thousands of probes representing a complete overlapping set covering 1,610 clinically relevant HLA class I alleles accompanied by computational tools for assigning HLA type to 4-digit resolution. Our proof-of-concept experiment included 21 blood samples, 18 cell lines, and multiple controls. The method is accurate, robust, and amenable to automation. Typing errors were restricted to homozygous samples or those with very closely related alleles from the same locus, but readily resolved by targeted DNA sequencing validation of flagged samples. High-throughput HLA typing technologies that are effective, yet inexpensive, can be used to analyze the world's populations, benefiting both global public health and personalized health care.