Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

The case for allele‐specific recognition by the TCR

There is a sharp difference in how one views TCR structure–function–behaviour dependent on whether its recognition of major histocompatibility complex‐encoded restriction elements (R) is germline selected or somatically generated. The generally accepted or Standard model is built on the assumption that recognition of R is by the V regions of the αβ TCR, which is not driven by allele specificity, whereas the competing model posits that recognition of R is allele‐specific. The establishing of allele‐specific recognition of R by the TCR would rule out the Standard model and clear the road to a consideration of a competing construct, the Tritope model. Here, the case for allele‐specific recognition (germline selected) is detailed making it obvious that the Standard model is untenable.     

Generalized,severe epidermolysis bullosa simplex caused by a Keratin 5 p.E477K mutation

Epidermolysis bullosa simplex (EBS) is a skin fragility disorder resulting from mutations of structural proteins in the epidermis. We provide a brief report of long‐term survival and reproduction in a mother with EBS due to keratin 5 (KRT5) c.1429G > A (p.E477K) mutation, which causes a particularly severe form of the disease.