Evaluation of HLA-DRB1 imputation using a Finnish dataset.

Owing to the vast amount of alleles, high-resolution human leukocyte antigen (HLA) typing is expensive and time-consuming. Scientists have attempted to develop computational approaches to define HLA alleles with high confidence. We tested the reliability of HLA*IMP and SNP2HLA for imputing HLA-DRB1 alleles in a Finnish material (n=161). The per-individual success rates varied between 16.68% and 25.4% using both softwares. One of the most prominent example was HLA-DRB1*01:01 allele showing approximately a 30% success rate while being the most common wrongly imputed allele. In Finland, isolation and migration history have shaped the gene pool narrower showing HLA haplotype frequencies typical to the Finnish population when compared to Europeans. The imputation success for HLA-DRB1 alleles was very low pointing to the importance of population-specific reference material.

[1]  D. Monos,et al.  16th IHIW: Global distribution of extended HLA haplotypes , 2013, International journal of immunogenetics.

[2]  Katja T. Eronen,et al.  Diversity of Extended HLA-DRB1 Haplotypes in the Finnish Population , 2013, PloS one.

[3]  Buhm Han,et al.  Imputing Amino Acid Polymorphisms in Human Leukocyte Antigens , 2013, PloS one.

[4]  T. Jaatinen,et al.  HLA antigen, allele and haplotype frequencies and their use in virtual panel reactive antigen calculations in the Finnish population. , 2013, Tissue antigens.

[5]  Tao Jiang,et al.  Accurate HLA type inference using a weighted similarity graph , 2010, BMC Bioinformatics.

[6]  K. Roeder,et al.  Amino Acid Position 11 of HLA-DRβ1 is a Major Determinant of Chromosome 6p Association with Ulcerative Colitis , 2011, Genes and Immunity.

[7]  Sue Povey,et al.  Gene map of the extended human MHC , 2004, Nature Reviews Genetics.

[8]  C. Wijmenga,et al.  Identification of multiple independent susceptibility loci in the HLA region in Behçet's disease , 2013, Nature Genetics.

[9]  M. Carrington,et al.  Recombination within the human MHC , 1999, Immunological reviews.

[10]  Alexander T. Dilthey,et al.  HLA*IMP - an integrated framework for imputing classical HLA alleles from SNP genotypes , 2011, Bioinform..

[11]  E. Petersdorf The major histocompatibility complex: a model for understanding graft-versus-host disease. , 2013, Blood.

[12]  M. Nieminen,et al.  Proinflammatory HLA-DRB1*01-haplotype predisposes to ST-elevation myocardial infarction. , 2012, Atherosclerosis.

[13]  E. Vartiainen,et al.  Cardiovascular risk factor changes in Finland, 1972-1997. , 2000, International journal of epidemiology.

[14]  Michael Inouye,et al.  A genotype calling algorithm for the Illumina BeadArray platform , 2007, Bioinform..

[15]  L. Excoffier,et al.  Arlequin suite ver 3.5: a new series of programs to perform population genetics analyses under Linux and Windows , 2010, Molecular ecology resources.

[16]  Pardis C Sabeti,et al.  A high-resolution HLA and SNP haplotype map for disease association studies in the extended human MHC , 2006, Nature Genetics.

[17]  Manuel A. R. Ferreira,et al.  PLINK: a tool set for whole-genome association and population-based linkage analyses. , 2007, American journal of human genetics.

[18]  Jack T Stapleton,et al.  The Major Genetic Determinants of HIV-1 Control Affect HLA Class I Peptide Presentation , 2010, Science.

[19]  Alexander T. Dilthey,et al.  Multi-Population Classical HLA Type Imputation , 2013, PLoS Comput. Biol..

[20]  E. Thorsby,et al.  HLA associated genetic predisposition to autoimmune diseases: Genes involved and possible mechanisms. , 2005, Transplant immunology.

[21]  Alexander Gusev,et al.  HLA Type Inference via Haplotypes Identical by Descent , 2010, RECOMB.

[22]  Harriet Noreen,et al.  High-resolution donor-recipient HLA matching contributes to the success of unrelated donor marrow transplantation. , 2007, Blood.

[23]  P. Gregersen,et al.  Immunochip analyses identify a novel risk locus for primary biliary cirrhosis at 13q14, multiple independent associations at four established risk loci and epistasis between 1p31 and 7q32 risk variants. , 2012, Human molecular genetics.

[24]  J. Traherne,et al.  Review Article doi: 10.1111/j.1744-313X.2008.00765.x Blackwell , 2022 .

[25]  Peter Donnelly,et al.  A statistical method for predicting classical HLA alleles from SNP data. , 2008, American journal of human genetics.

[26]  M. Lokki,et al.  Unique HLA antigen frequencies in the Finnish population. , 1996, Tissue antigens.

[27]  G. Abecasis,et al.  MaCH: using sequence and genotype data to estimate haplotypes and unobserved genotypes , 2010, Genetic epidemiology.

[28]  M. Stephens,et al.  Modeling linkage disequilibrium and identifying recombination hotspots using single-nucleotide polymorphism data. , 2003, Genetics.

[29]  Nilesh J Samani,et al.  A Genome-Wide Association Study for Coronary Artery Disease Identifies a Novel Susceptibility Locus in the Major Histocompatibility Complex , 2012, Circulation. Cardiovascular genetics.

[30]  Christophe Tzourio,et al.  Association between Parkinson's disease and the HLA‐DRB1 locus , 2012, Movement disorders : official journal of the Movement Disorder Society.

[31]  B. Gersh,et al.  Thirty-five-year trends in cardiovascular risk factors in Finland , 2011 .

[32]  M. Lokki,et al.  HLA-DRB1 allele frequencies and C4 copy number variation in Finnish sarcoidosis patients and associations with disease prognosis. , 2012, Human immunology.

[33]  A. Jeffreys,et al.  Recombination hotspots rather than population history dominate linkage disequilibrium in the MHC class II region. , 2003, Human molecular genetics.