Diagnosis of Kawasaki Disease Using a Minimal Whole-Blood Gene Expression Signature

Abstract

Key Points Question Can Kawasaki disease be accurately diagnosed on the basis of the pattern of host gene expression in whole blood? Findings In this case-control study of 606 children (404 in the discovery cohort; 202 in the validation cohort), a 13-transcript signature was identified that accurately discriminated Kawasaki disease from comparator febrile diseases in discovery and validation cohorts. Meaning A diagnostic blood test based on measurement of small numbers of host gene transcripts might enable early discrimination of Kawasaki disease from other infectious and inflammatory conditions.

Handheld flow meter improves COPD detectability regardless of using a conventional questionnaire: A split‐sample validation study

“…Nonetheless, this may have led to an underestimation of the prevalence of COPD in this study. Sensitivity and specificity do not depend on prevalence, as they are calculated in many case–control studies in which an accurate estimate of the prevalence of disease cannot be obtained from the data. Conversely, the decision curve depends on prevalence.…”

Kawasaki Disease: Global Burden and Genetic Background

“…According to the current guidelines [4,18], the diagnosis of KD relies on clinical features that are usually similar to other infectious or inflammatory diseases, leading to delayed or missed diagnosis and treatment in many cases with an increased liability to complications. In a study performed by Wright et al [50], they presented a rapid diagnostic blood test dependent on the measurement of small numbers of host gene transcripts, which would help an early diagnosis of KD and definite differentiation from other infectious or inflammatory diseases. They recognized a 13-transcript gene expression signature with high sensitivity and specificity for KD that included eight genes (CACNA1E, DDIAS, KLHL2, PYROXD2, SMOX, ZNF185, LINC02035, and CLIC3) with an increased expression in KD relative to other conditions, and five other genes (S100P, IFI27, HS.553068, CD163, and RTN1) that showed a decreased expression in KD.…”

A Meta-Analysis of Multiple Whole Blood Gene Expression Data Unveils a Diagnostic Host-Response Transcript Signature for Respiratory Syncytial Virus

“…PReMS explores different logistic regression models constructed from optimal subsets of the candidate genes while increasing the model size iteratively. PReMS [64] was chosen instead of other methods because it tends to select signatures with fewer genes without sacrificing model accuracy, which would facilitate its future translation into a clinical test [17]. The bio-signature was searched among the top 100 DEG between RSV and non-RSV categories.…”

“…In the era of personalized medicine and molecular diagnostics, the study of host transcriptomics during infection is becoming an important tool not only for the study of the host-pathogen interaction but also for the diagnosis and prognosis of diseases. In the last few years, some host expression signatures related to both infectious [12][13][14][15][16] and non-infectious diseases [17,18] have been reported. However, most of the studies are focused only on particular cohorts from a certain ethnicity or population group and restricted geographic areas, from a specific age group and the same epidemic period.…”