Pattern interaction effect.
Ontology highlight
ABSTRACT:
SUBMITTER: Floryan JM
PROVIDER: S-EPMC8285401 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:BackgroundInteractions of single nucleotide polymorphisms (SNPs) and environmental factors play an important role in understanding complex diseases' pathogenesis. A growing number of SNP-environment studies have been conducted in the past decade; however, the statistical methods for evaluating SNP-environment interactions are still underdeveloped. The conventional statistical approach with a full interaction model with an additive SNP mode tests one specific interaction type, so the full interaction model approach tends to lead to false-negative findings. To increase detection accuracy, developing a statistical tool to effectively detect various SNP-environment interaction patterns is necessary.ResultsSNPxE, a SNP-environment interaction pattern identifier, tests multiple interaction patterns associated with a phenotype for each SNP-environment pair. SNPxE evaluates 27 interaction patterns for an ordinal environment factor and 18 patterns for a categorical environment factor. For detecting SNP-environment interactions, SNPxE considers three major components: (1) model structure, (2) SNP's inheritance mode, and (3) risk direction. Among the multiple testing patterns, the best interaction pattern will be identified based on the Bayesian information criterion or the smallest p-value of the interaction. Furthermore, the risk sub-groups based on the SNPs and environmental factors can be identified. SNPxE can be applied to both numeric and binary phenotypes. For better results interpretation, a heat-table of the outcome proportions can be generated for the sub-groups of a SNP-environment pair.ConclusionsSNPxE is a valuable tool for intensively evaluate SNP-environment interactions, and the SNPxE findings can provide insights for solving the missing heritability issue. The R function of SNPxE is freely available for download at GitHub ( https://github.com/LinHuiyi/SIPI ).
| S-EPMC8425112 | biostudies-literature
Project description:The endoplasmic reticulum (ER) chaperone protein, calreticulin (CRT), is essential for proper glycoprotein folding and maintaining cellular calcium homeostasis. During ER stress, CRT is overexpressed as part of the unfolded protein response (UPR). In addition, CRT can be released as a damage-associated molecular pattern (DAMP) molecule that may interact with pathogen-associated molecular patterns (PAMPs) during the innate immune response. One such PAMP is lipopolysaccharide (LPS), a component of the gram-negative bacterial cell wall. In this report, we show that recombinant and native human placental CRT strongly interacts with LPS in solution, solid phase, and the surface of gram-negative and gram-positive bacteria. Furthermore, LPS induces oilgomerization of CRT with a disappearance of the monomeric form. The application of recombinant CRT (rCRT) to size exclusion and anion exchange chromatography shows an atypical heterogeneous elution profile, indicating that LPS affects the conformation and ionic charge of CRT. Interestingly, LPS bound to CRT is detected in sera of bronchiectasis patients with chronic bacterial infections. By ELISA, rCRT dose-dependently bound to solid phase LPS via the N- and C-domain globular head region of CRT and the C-domain alone. The specific interaction of CRT with LPS may be important in PAMP innate immunity.
| S-EPMC6359024 | biostudies-literature
Project description:Motivation:Testing SNP-SNP interactions is considered as a key for overcoming bottlenecks of genetic association studies. However, related statistical methods for testing SNP-SNP interactions are underdeveloped. Results:We propose the SNP Interaction Pattern Identifier (SIPI), which tests 45 biologically meaningful interaction patterns for a binary outcome. SIPI takes non-hierarchical models, inheritance modes and mode coding direction into consideration. The simulation results show that SIPI has higher power than MDR (Multifactor Dimensionality Reduction), AA_Full, Geno_Full (full interaction model with additive or genotypic mode) and SNPassoc in detecting interactions. Applying SIPI to the prostate cancer PRACTICAL consortium data with approximately 21 000 patients, the four SNP pairs in EGFR-EGFR , EGFR-MMP16 and EGFR-CSF1 were found to be associated with prostate cancer aggressiveness with the exact or similar pattern in the discovery and validation sets. A similar match for external validation of SNP-SNP interaction studies is suggested. We demonstrated that SIPI not only searches for more meaningful interaction patterns but can also overcome the unstable nature of interaction patterns. Availability and Implementation:The SIPI software is freely available at http://publichealth.lsuhsc.edu/LinSoftware/ . Contact:hlin1@lsuhsc.edu. Supplementary information:Supplementary data are available at Bioinformatics online.
| S-EPMC5860469 | biostudies-literature
Project description:The aim of this study was to identify the highly expressed genes in terms of interaction concept in Prolactinoma. The study was conducted by additional analysis of the available data from the GEO database. The online tool, GEO2R, was used to analyze the gene expression profile of GSE36314 dataset using the GPL8300 platform. Consequently, a PPI network of up-regulated and down-regulated genes was constructed and examined to introduce the possible targets with possible therapeutic values. A number of 46 genes were dysregulated in Prolactinoma and their network indicated 15 essential genes via topological analysis. Moreover, the present study found that the highlighted genes of prolactinoma are involved in two major biological processes including growth regulation and metabolic function. Thus, the determined genes may be valuable for diagnosis, treatment, and patient follow-up. However, further studies are essential to validate this conclusion.
| S-EPMC6216114 | biostudies-literature
Project description:Proteins of the SOCS (suppressors of cytokine signalling) family are characterized by a conserved modular structure with pre-SH2 (Src homology 2), SH2 and SOCS-box domains. Several members, including CIS (cytokine-inducible SH2 protein), SOCS1 and SOCS3, are induced rapidly upon cytokine receptor activation and function in a negative-feedback loop, attenuating signalling at the receptor level. We used a recently developed mammalian two-hybrid system [MAPPIT (mammalian protein-protein interaction trap)] to analyse SOCS protein-interaction patterns in intact cells, allowing direct comparison with biological function. We find that, besides the SH2 domain, the C-terminal part of the CIS SOCS-box is required for functional interaction with the cytokine receptor motifs examined, but not with the N-terminal death domain of the TLR (Toll-like receptor) adaptor MyD88. Mutagenesis revealed that one single tyrosine residue at position 253 is a critical binding determinant. In contrast, substrate binding by the highly related SOCS2 protein, and also by SOCS1 and SOCS3, does not require their SOCS-box.
| S-EPMC1698688 | biostudies-literature
Project description:Factors influencing crossmodal interactions are manifold and operate in a stimulus-driven, bottom-up fashion, as well as via top-down control. Here, we evaluate the interplay of stimulus congruence and attention in a visual-tactile task. To this end, we used a matching paradigm requiring the identification of spatial patterns that were concurrently presented visually on a computer screen and haptically to the fingertips by means of a Braille stimulator. Stimulation in our paradigm was always bimodal with only the allocation of attention being manipulated between conditions. In separate blocks of the experiment, participants were instructed to (a) focus on a single modality to detect a specific target pattern, (b) pay attention to both modalities to detect a specific target pattern, or (c) to explicitly evaluate if the patterns in both modalities were congruent or not. For visual as well as tactile targets, congruent stimulus pairs led to quicker and more accurate detection compared to incongruent stimulation. This congruence facilitation effect was more prominent under divided attention. Incongruent stimulation led to behavioral decrements under divided attention as compared to selectively attending a single sensory channel. Additionally, when participants were asked to evaluate congruence explicitly, congruent stimulation was associated with better performance than incongruent stimulation. Our results extend previous findings from audiovisual studies, showing that stimulus congruence also resulted in behavioral improvements in visuotactile pattern matching. The interplay of stimulus processing and attentional control seems to be organized in a highly flexible fashion, with the integration of signals depending on both bottom-up and top-down factors, rather than occurring in an 'all-or-nothing' manner.
| S-EPMC4159283 | biostudies-literature
Project description:Over the last two decades, many approaches have been developed in bioinformatics that aim at one of the most promising, yet unsolved problems in modern life sciences--prediction of structural features of a protein. Such tasks addressed to transmembrane protein structures provide valuable knowledge about their three-dimensional structure. For this reason, the analysis of membrane proteins is essential in genomic and proteomic-wide investigations. Thus, many in-silico approaches have been utilized extensively to gain crucial advances in understanding membrane protein structures and functions.It turned out that amino acid covariation within interacting sequence parts, extracted from a evolutionary sequence record of ?-helical membrane proteins, can be used for structure prediction. In a recent study we discussed the significance of short membrane sequence motifs widely present in nature that act as stabilizing 'building blocks' during protein folding and in retaining the three-dimensional fold. In this work, we used motif data to define evolutionary interaction pattern pairs. These were obtained from different pattern alignments and were used to evaluate which coupling mechanisms the evolution provides. It can be shown that short interaction patterns of homologous sequence records are membrane protein family-specific signatures. These signatures can provide valuable information for structure prediction and protein classification. The results indicate a good agreement with recent studies.Generally, it can be shown how the evolution contributes to realize covariation within discriminative interaction patterns to maintain structure and function. This points to their general importance for ?-helical membrane protein structure formation and interaction mediation. In the process, no fundamentally energetic approaches of previous published works are considered. The low-cost rapid computational methods postulated in this work provides valuable information to classify unknown ?-helical transmembrane proteins and to determine their structural similarity.
| S-EPMC4379700 | biostudies-literature
Project description:Based on the conformationally constrained D-Trp-Phe-D-Trp (wFw) core of the prototype inverse agonist [D-Arg(1),D-Phe(5),D-Trp(7,9),Leu(11)]substance P, a series of novel, small, peptide-mimetic agonists for the ghrelin receptor were generated. By using various simple, ring-constrained spacers connecting the D-Trp-Phe-D-Trp motif with the important C-terminal carboxyamide group, 40 nm agonism potency was obtained and also in one case (wFw-Isn-NH(2), where Isn is isonipecotic acid) ~80% efficacy. However, in contrast to all previously reported ghrelin receptor agonists, the piperidine-constrained wFw-Isn-NH(2) was found to be a functionally biased agonist. Thus, wFw-Isn-NH(2) mediated potent and efficacious signaling through the G?(q) and ERK1/2 signaling pathways, but in contrast to all previous ghrelin receptor agonists it did not signal through the serum response element, conceivably the G?(12/13) pathway. The recognition pattern of wFw-Isn-NH(2) with the ghrelin receptor also differed significantly from that of all previously characterized unbiased agonists. Most importantly, wFw-Isn-NH(2) was not dependent on GluIII:09 (Glu3.33), which otherwise is an obligatory TM III anchor point residue for ghrelin agonists. Molecular modeling and docking experiments indicated that wFw-Isn-NH(2) binds in the classical agonist binding site between the extracellular segments of TMs III, VI, and VII, interacting closely with the aromatic cluster between TMs VI and VII, but that it does so in an opposite orientation as compared with, for example, the wFw peptide agonists. It is concluded that the novel peptide-mimetic ligand wFw-Isn-NH(2) is a biased ghrelin receptor agonist and that the selective signaling pattern presumably is due to its unique receptor recognition pattern lacking interaction with key residues especially in TM III.
| S-EPMC3121491 | biostudies-literature
Project description:Gene-diet interaction using a multifactorial approach is preferred to study the multiple risk factors of cardiovascular disease (CVD). This study examined the association and gene-diet interaction effects of the angiotensin II type 1 receptor (AGTR1) gene (rs5186), and type 2 receptor (AGTR2) gene (rs1403543) polymorphisms on metabolic risk factors of CVD in Malaysian adults. CVD parameters (BMI, blood pressure, glycated hemoglobin, total cholesterol (TC), triglycerides, low-density lipoprotein cholesterol, high-density lipoprotein cholesterol (HDL-C), and TC/HDL-C ratio), and constructed dietary patterns "vegetables, fruits, and soy diet" (VFSD), and "rice, egg, and fish diet" (REFD) were obtained from previous studies. Genotyping analysis was performed by real-time PCR using Taqman probes. The subjects were 507 adults (151 Malays; 179 Chinese; and 177 Indians). Significant genetic associations were obtained on blood lipids for rs5186 in Malays and Chinese, and rs1403543 in Chinese females. The significant gene-diet interaction effects after adjusting for potential confounders were: rs5186 × VFSD on blood pressure in Malays (p = 0.016), and in Chinese on blood lipids for rs5186 × REFD (p = 0.009-0.023), and rs1403543 × VFSD in female subjects (p = 0.001-0.011). Malays and Chinese showed higher risk for blood pressure and/or lipids involving rs5186 and rs1403543 SNPs together with gene-diet interactions, but not Indians.
| S-EPMC5579646 | biostudies-literature
Project description:Motivation:The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions. Results:We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies. Availability and implementation:The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/. Supplementary information:Supplementary data are available at Bioinformatics online.
| S-EPMC6289141 | biostudies-literature