Bootstrap aggregating of alternating decision trees to detect sets of SNPs that associate with disease.

Complex genetic disorders are a result of a combination of genetic and nongenetic factors, all potentially interacting. Machine learning methods hold the potential to identify multilocus and environmental associations thought to drive complex genetic traits. Decision trees, a popular machine learning technique, offer a computationally low complexity algorithm capable of detecting associated sets of single nucleotide polymorphisms (SNPs) of arbitrary size, including modern genome-wide SNP scans. However, interpretation of the importance of an individual SNP within these trees can present challenges. We present a new decision tree algorithm denoted as Bagged Alternating Decision Trees (BADTrees) that is based on identifying common structural elements in a bootstrapped set of Alternating Decision Trees (ADTrees). The algorithm is order nk(2), where n is the number of SNPs considered and k is the number of SNPs in the tree constructed. Our simulation study suggests that BADTrees have higher power and lower type I error rates than ADTrees alone and comparable power with lower type I error rates compared to logistic regression. We illustrate the application of these data using simulated data as well as from the Lupus Large Association Study 1 (7,822 SNPs in 3,548 individuals). Our results suggest that BADTrees hold promise as a low computational order algorithm for detecting complex combinations of SNP and environmental factors associated with disease.

Comparative analysis of methods for detecting interacting loci.

BACKGROUND: Interactions among genetic loci are believed to play an important role in disease risk. While many methods have been proposed for detecting such interactions, their relative performance remains largely unclear, mainly because different data sources, detection performance criteria, and experimental protocols were used in the papers introducing these methods and in subsequent studies. Moreover, there have been very few studies strictly focused on comparison of existing methods. Given the importance of detecting gene-gene and gene-environment interactions, a rigorous, comprehensive comparison of performance and limitations of available interaction detection methods is warranted. RESULTS: We report a comparison of eight representative methods, of which seven were specifically designed to detect interactions among single nucleotide polymorphisms (SNPs), with the last a popular main-effect testing method used as a baseline for performance evaluation. The selected methods, multifactor dimensionality reduction (MDR), full interaction model (FIM), information gain (IG), Bayesian epistasis association mapping (BEAM), SNP harvester (SH), maximum entropy conditional probability modeling (MECPM), logistic regression with an interaction term (LRIT), and logistic regression (LR) were compared on a large number of simulated data sets, each, consistent with complex disease models, embedding multiple sets of interacting SNPs, under different interaction models. The assessment criteria included several relevant detection power measures, family-wise type I error rate, and computational complexity. There are several important results from this study. First, while some SNPs in interactions with strong effects are successfully detected, most of the methods miss many interacting SNPs at an acceptable rate of false positives. In this study, the best-performing method was MECPM. Second, the statistical significance assessment criteria, used by some of the methods to control the type I error rate, are quite conservative, thereby limiting their power and making it difficult to fairly compare them. Third, as expected, power varies for different models and as a function of penetrance, minor allele frequency, linkage disequilibrium and marginal effects. Fourth, the analytical relationships between power and these factors are derived, aiding in the interpretation of the study results. Fifth, for these methods the magnitude of the main effect influences the power of the tests. Sixth, most methods can detect some ground-truth SNPs but have modest power to detect the whole set of interacting SNPs. CONCLUSION: This comparison study provides new insights into the strengths and limitations of current methods for detecting interacting loci. This study, along with freely available simulation tools we provide, should help support development of improved methods. The simulation tools are available at: http://code.google.com/p/simulation-tool-bmc-ms9169818735220977/downloads/list.

Genetic analyses of interferon pathway-related genes reveal multiple new loci associated with systemic lupus erythematosus.

OBJECTIVE: The overexpression of interferon (IFN)-inducible genes is a prominent feature of systemic lupus erythematosus (SLE); it serves as a marker for active and more severe disease, and is also observed in other autoimmune and inflammatory conditions. This study was undertaken to investigate the genetic variations responsible for sustained activation of IFN-responsive genes in SLE. METHODS: We systematically evaluated association of SLE with a total of 1,754 IFN pathway-related genes, including IFN-inducible genes known to be differentially expressed in SLE patients and their direct regulators. We used a 3-stage study design in which 2 cohorts (total of 939 SLE cases and 3,398 controls) were analyzed independently and jointly for association with SLE, and the results were adjusted for the number of comparisons. RESULTS: A total of 15,166 single-nucleotide polymorphisms (SNPs) passed all quality control filters; 305 of these SNPs demonstrated replicated association with SLE in both cohorts. Nine variants were further genotyped for confirmation in an average of 1,316 independent SLE cases and 3,215 independent controls. Association with SLE was confirmed for several genes, including those for the transmembrane receptor CD44 (CD44 [rs507230]; P = 3.98 × 10⁻¹²), the cytokine pleiotrophin (PTN [rs919581]; P = 5.38 × 10⁻4), the heat-shock protein DnaJ (DNAJA1 [rs10971259]; P = 6.31 × 10⁻³), and the nuclear import protein karyopherin α1 (KPNA [rs6810306]; P = 4.91 × 10⁻²). CONCLUSION: This study expands the number of candidate genes that have been shown to be associated with SLE and highlights potential of pathway-based approaches for gene discovery. Identification of the causal alleles will help elucidate the molecular mechanisms responsible for activation of the IFN system in SLE.

Quantitative microarray analysis of intact glycolipid-CD1d interaction and correlation with cell-based cytokine production.

The protein CD1d binds self and foreign glycolipids for presentation to CD1-restricted T cells by means of TCR recognition and activates T(H)1 and T(H)2 chemokine release. In this study, a variety of glycolipid ligands were attached to a microarray surface and their binding with dimeric CD1d was investigated. An alpha-galactosyl ceramide (alpha-GalCer) bearing a carbamate group at the 6'-OH position was tethered to the surface, and the dissociation constant on surface with CD1d was determined to reflect the multivalent interaction. Competition assays were then used to determine the dissociation constants (Ki) of new and intact glycolipids in solution. The 4-fluorophenyloctanoyl-modified alpha-GalCer (18) was found to bind most strongly with CD1d (Ki 0.21 microM), 2 orders of magnitude stronger than alpha-GalCer and more than three times more selective than alpha-GalCer for IFN-gamma release from NKT cells. Various alpha-GalCer analogues were analyzed, and the results showed that the binding affinity of glycolipids to CD1d correlates well with IFN-gamma production but poorly with IL-4 secretion by NKT cells, suggesting that tighter binding ligands could bias cytokine release through the T(H)1 pathway.

Solid-phase synthesis of peptide and glycopeptide thioesters through side-chain-anchoring strategies.

An efficient new strategy for the synthesis of peptide and glycopeptide thioesters is described. The method relies on the side-chain immobilization of a variety of Fmoc-amino acids, protected at their C-termini, on solid supports. Once anchored, peptides were constructed using solid-phase peptide synthesis according to the Fmoc protocol. After unmasking the C-terminal carboxylate, either thiols or amino acid thioesters were coupled to afford, after cleavage, peptide and glycopeptide thioesters in high yields. Using this method a significant proportion of the proteinogenic amino acids could be incorporated as C-terminal amino acid residues, therefore providing access to a large number of potential targets that can serve as acyl donors in subsequent ligation reactions. The utility of this methodology was exemplified in the synthesis of a 28 amino acid glycopeptide thioester, which was further elaborated to an N-terminal fragment of the glycoprotein erythropoietin (EPO) by native chemical ligation.

Michael, Michael-aldol and Michael-Michael reactions of enolate equivalents of butane-2,3-diacetal protected glycolic acid derivatives.

Consecutive coupling reactions of butane-2,3-diacetal protected glycolic acid derivatives with Michael acceptors and aldehydes are reported. An enantiopure sample of this building block was used to kinetically resolve a chiral Michael acceptor present as a racemic mixture of enantiomers.

Studies on the generation of enolate anions from butane-2,3-diacetal protected glycolic acid derivatives and subsequent highly diastereoselective coupling reactions with aldehydes and acid chlorides.

Highly diastereoselective coupling reactions of enolates derived from butane-2,3-diacetal protected glycolic acids 1 and 2 and their alkylated derivatives with aldehydes are reported together with their efficient acid-catalysed deprotection to yield enantiopure anti-2,3-dihydroxyesters. A procedure to provide the corresponding syn-2,3-dihydroxyesters is also described in two cases, proceeding via an acylation-reduction sequence. An usual double addition reaction of butane-2,3-diacetal protected glycolic acid to small aliphatic acid chlorides provides a synthetically useful, densely-functionalised lactone after acidic deprotection.

Preparation of enantiopure butane-2,3-diacetals of glycolic acid and alkylation reactions leading to alpha-hydroxyacid and amide derivatives.

The preparation of butane-2,3-diacetal protected glycolic acid and related systems is described together with highly selective alkylation reactions of (R,R) and (S,S) butanediacetal protected glycolic acid. These compounds are readily deprotected to give enantiopure alpha-hydroxyacids, alpha-hydroxyesters or alpha-hydroxyamides by suitable choice of conditions.