Risk factors based vessel-specific prediction for stages of coronary artery disease using Bayesian quantile regression machine learning method: Results from the PARADIGM registry.

BACKGROUND AND HYPOTHESIS: The recently introduced Bayesian quantile regression (BQR) machine-learning method enables comprehensive analyzing the relationship among complex clinical variables. We analyzed the relationship between multiple cardiovascular (CV) risk factors and different stages of coronary artery disease (CAD) using the BQR model in a vessel-specific manner. METHODS: From the data of 1,463 patients obtained from the PARADIGM (NCT02803411) registry, we analyzed the lumen diameter stenosis (DS) of the three vessels: left anterior descending (LAD), left circumflex (LCx), and right coronary artery (RCA). Two models for predicting DS and DS changes were developed. Baseline CV risk factors, symptoms, and laboratory test results were used as the inputs. The conditional 10%, 25%, 50%, 75%, and 90% quantile functions of the maximum DS and DS change of the three vessels were estimated using the BQR model. RESULTS: The 90th percentiles of the DS of the three vessels and their maximum DS change were 41%-50% and 5.6%-7.3%, respectively. Typical anginal symptoms were associated with the highest quantile (90%) of DS in the LAD; diabetes with higher quantiles (75% and 90%) of DS in the LCx; dyslipidemia with the highest quantile (90%) of DS in the RCA; and shortness of breath showed some association with the LCx and RCA. Interestingly, High-density lipoprotein cholesterol showed a dynamic association along DS change in the per-patient analysis. CONCLUSIONS: This study demonstrates the clinical utility of the BQR model for evaluating the comprehensive relationship between risk factors and baseline-grade CAD and its progression.

Domain-specific positive selection contributes to the evolution of Arabidopsis leucine-rich repeat receptor-like kinase (LRR RLK) genes.

Leucine-rich repeat receptor-like kinases (LRR RLKs) comprise the largest group within the plant receptor-like kinase (RLK) superfamily, and the Arabidopsis genome alone contains over 200 LRR RLK genes. Although there is clear evidence for diverse roles played by individual LRR RLK genes in Arabidopsis growth and development, the evolutionary mechanism for this functional diversification is currently unclear. In this study, we focused on the LRRII RLK subfamily to investigate the molecular mechanisms that might have led to the functional differentiation of Arabidopsis LRR RLK genes. Phylogenetic analysis of 14 genes in this subfamily revealed three well-supported groups (I, II, and III). RT-PCR analysis did not find many qualitative differences in expression among these 14 genes in various Arabidopsis tissues, suggesting that evolution of regulatory sequences did not play a major role in their functional divergence. We analyzed substitution patterns in the predicted ligand-binding regions of these genes to examine if positive selection has acted to produce novel ligand-binding specificities, using the nonsynonymous/synonymous rate ratio (d (N)/d (S)) as an indicator of selective pressure. Estimates of d (N)/d (S) ratios from multiple methods indicate that nonsynonymous substitutions accumulated during divergence of the three lineages. Positive selection is likely to have occurred along the lineages ancestral to groups II and III. We suggest that positive selection on the ligand-binding sites of LRRII RLKs promoted diversification of ligand-binding specificities and thus contributed to the functional differentiation of Arabidopsis LRRII RLK genes during evolution.

The Arabidopsis CDPK-SnRK superfamily of protein kinases.

The CDPK-SnRK superfamily consists of seven types of serine-threonine protein kinases: calcium-dependent protein kinase (CDPKs), CDPK-related kinases (CRKs), phosphoenolpyruvate carboxylase kinases (PPCKs), PEP carboxylase kinase-related kinases (PEPRKs), calmodulin-dependent protein kinases (CaMKs), calcium and calmodulin-dependent protein kinases (CCaMKs), and SnRKs. Within this superfamily, individual isoforms and subfamilies contain distinct regulatory domains, subcellular targeting information, and substrate specificities. Our analysis of the Arabidopsis genome identified 34 CDPKs, eight CRKs, two PPCKs, two PEPRKs, and 38 SnRKs. No definitive examples were found for a CCaMK similar to those previously identified in lily (Lilium longiflorum) and tobacco (Nicotiana tabacum) or for a CaMK similar to those in animals or yeast. CDPKs are present in plants and a specific subgroup of protists, but CRKs, PPCKs, PEPRKs, and two of the SnRK subgroups have been found only in plants. CDPKs and at least one SnRK have been implicated in decoding calcium signals in Arabidopsis. Analysis of intron placements supports the hypothesis that CDPKs, CRKs, PPCKs and PEPRKs have a common evolutionary origin; however there are no conserved intron positions between these kinases and the SnRK subgroup. CDPKs and SnRKs are found on all five Arabidopsis chromosomes. The presence of closely related kinases in regions of the genome known to have arisen by genome duplication indicates that these kinases probably arose by divergence from common ancestors. The PlantsP database provides a resource of continuously updated information on protein kinases from Arabidopsis and other plants.