Unraveling multiple MHC gene associations with systemic lupus erythematosus: model choice indicates a role for HLA alleles and non-HLA genes in Europeans.

We have performed a meta-analysis of the major-histocompatibility-complex (MHC) region in systemic lupus erythematosus (SLE) to determine the association with both SNPs and classical human-leukocyte-antigen (HLA) alleles. More specifically, we combined results from six studies and well-known out-of-study control data sets, providing us with 3,701 independent SLE cases and 12,110 independent controls of European ancestry. This study used genotypes for 7,199 SNPs within the MHC region and for classical HLA alleles (typed and imputed).

European population substructure is associated with mucocutaneous manifestations and autoantibody production in systemic lupus erythematosus.

Objective: To determine whether genetic substructure in European-derived populations is associated with specific manifestations of systemic lupus erythematosus (SLE), including mucocutaneous phenotypes, autoantibody production, and renal disease.

Methods: SLE patients of European descent (n=1,754) from 8 case collections were genotyped for >1,400 ancestry informative markers that define a north-south gradient of European substructure. Using the Structure program, each SLE patient was characterized in terms of percent Northern (versus percent Southern) European ancestry based on these genetic markers.

Replication of the association between the C8orf13-BLK region and systemic lupus erythematosus in a Japanese population.

Objective: Recent genome-wide association studies identified an association between single-nucleotide polymorphisms (SNPs) in the C8orf13 region of BLK, the B lymphoid tyrosine kinase gene, with systemic lupus erythematosus (SLE) in Caucasians. The purpose of this study was to evaluate the significance of this region in the genetic background of Japanese patients with SLE.

Methods: Fourteen tag SNPs in the C8orf13-BLK region were genotyped in 327 Japanese patients with SLE and 322 healthy Japanese controls.

Role of STAT4 polymorphisms in systemic lupus erythematosus in a Japanese population: a case-control association study of the STAT1-STAT4 region.

Introduction: Recent studies identified STAT4 (signal transducers and activators of transcription-4) as a susceptibility gene for systemic lupus erythematosus (SLE). STAT1 is encoded adjacently to STAT4 on 2q32.2-q32.

Specificity of the STAT4 genetic association for severe disease manifestations of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is a genetically complex disease with heterogeneous clinical manifestations. A polymorphism in the STAT4 gene has recently been established as a risk factor for SLE, but the relationship with specific SLE subphenotypes has not been studied. We studied 137 SNPs in the STAT4 region genotyped in 4 independent SLE case series (total n = 1398) and 2560 healthy controls, along with clinical data for the cases.

Association of systemic lupus erythematosus with C8orf13-BLK and ITGAM-ITGAX.

Background: Systemic lupus erythematosus (SLE) is a clinically heterogeneous disease in which the risk of disease is influenced by complex genetic and environmental contributions. Alleles of HLA-DRB1, IRF5, and STAT4 are established susceptibility genes; there is strong evidence for the existence of additional risk loci.

Methods: We genotyped more than 500,000 single-nucleotide polymorphisms (SNPs) in DNA samples from 1311 case subjects with SLE and 1783 control subjects; all subjects were North Americans of European descent.

STAT4 and the risk of rheumatoid arthritis and systemic lupus erythematosus.

Background: Rheumatoid arthritis is a chronic inflammatory disease with a substantial genetic component. Susceptibility to disease has been linked with a region on chromosome 2q.

Methods: We tested single-nucleotide polymorphisms (SNPs) in and around 13 candidate genes within the previously linked chromosome 2q region for association with rheumatoid arthritis.

Full-sequence computational design and solution structure of a thermostable protein variant.

Computational protein design procedures were applied to the redesign of the entire sequence of a 51 amino acid residue protein, Drosophila melanogaster engrailed homeodomain. Various sequence optimization algorithms were compared and two resulting designed sequences were experimentally evaluated. The two sequences differ by 11 mutations and share 22% and 24% sequence identity with the wild-type protein.

Three functional variants of IFN regulatory factor 5 (IRF5) define risk and protective haplotypes for human lupus.

Systematic genome-wide studies to map genomic regions associated with human diseases are becoming more practical. Increasingly, efforts will be focused on the identification of the specific functional variants responsible for the disease. The challenges of identifying causal variants include the need for complete ascertainment of genetic variants and the need to consider the possibility of multiple causal alleles.

A search algorithm for fixed-composition protein design.

We present a computational protein design algorithm for finding low-energy sequences of fixed amino acid composition. The search algorithms used in protein design typically do not restrict amino acid composition. However, the random energy model of Shakhnovich suggests that the use of fixed-composition sequences may circumvent defects in the modeling of the denatured state.

Dioxane contributes to the altered conformation and oligomerization state of a designed engrailed homeodomain variant.

Our goal was to compute a stable, full-sequence design of the Drosophila melanogaster engrailed homeodomain. Thermal and chemical denaturation data indicated the design was significantly more stable than was the wild-type protein. The data were also nearly identical to those for a similar, later full-sequence design, which was shown by NMR to adopt the homeodomain fold: a three-helix, globular monomer.

Preprocessing of rotamers for protein design calculations.

We have developed a process that significantly reduces the number of rotamers in computational protein design calculations. This process, which we call Vegas, results in dramatic computational performance increases when used with algorithms based on the dead-end elimination (DEE) theorem. Vegas estimates the energy of each rotamer at each position by fixing each rotamer in turn and utilizing various search algorithms to optimize the remaining positions.

Exact rotamer optimization for protein design.

Computational methods play a central role in the rational design of novel proteins. The present work describes a new hybrid exact rotamer optimization (HERO) method that builds on previous dead-end elimination algorithms to yield dramatic performance enhancements. Measured on experimentally validated physical models, these improvements make it possible to perform previously intractable designs of entire protein core, surface, or boundary regions.