NOBO Medicine Inc.

Accurate risk assessment of bone marrow failure syndrome (BMFS) is crucial for early diagnosis and intervention. Interpreting complete blood count (CBC) data is challenging without hematological expertise. To support primary physicians, we developed a predictive model using basic demographics and CBC data collected retrospectively from two major hospitals in South Korea. Binary classifiers for aplastic anemia and myelodysplastic syndrome were created and combined to form a BMFS classifier. The model demonstrated high performance in distinguishing BMFS, with consistent results across different CBC feature sets, confirmed by external validation. This algorithm provides a practical guide for primary physicians to identify BMFS based on initial CBC data, aiding in effective triage, timely referrals, and improved patient care.

Clonal hematopoiesis of indeterminate potential (CHIP), a premalignant expansion of mutated hematopoietic stem cells, is linked to immune alterations. Given the role of neuroinflammation and immune dysfunction in Parkinson's disease (PD), we hypothesized a connection between CHIP and PD. We analyzed peripheral blood DNA from 341 PD, 92 isolated REM sleep behavior disorder (iRBD) patients, and 5003 controls using targeted sequencing of 24 genes associated with hematologic neoplasms. PD cases were classified by clinical progression mode: fast, slow, and typical. Using multivariable logistic regression models, CHIP prevalence was assessed against controls with a 1.0% variant allele fraction threshold. CHIP with TET2 mutations was more prevalent in PD than controls (aOR 1.75, 95% CI 1.11-2.77, p = 0.017), particularly in the fast motor progression subgroup (aOR 3.19, p = 0.004). No distinct associations were observed with iRBD. PD is linked to increased odds of CHIP with TET2 mutations, suggesting immune dysregulation in PD pathophysiology.

Metabolic syndrome (MetS) is a major risk factor for cardiovascular and chronic diseases. This study evaluated how genetic predisposition and lifestyle factors contribute to MetS risk. We analysed data from 4,987 Koreans aged ≥ 40 years with at least one ASCVD risk factor (2014-2017). A polygenic risk score for metabolic disease (PRS_MetS) using eight metabolic phenotypes was used to categorise participants into high and low PRS_MetS groups (top 7% vs. bottom 93%). Lifestyle factors, including obesity, physical activity, smoking, diet, and alcohol consumption, were assessed with a healthy lifestyle score. The associations of PRS_MetS and lifestyle factors with MetS risk were evaluated. High PRS_MetS was associated with a 1.31-fold higher risk of MetS (adjusted odds ratio [aOR], 1.31; 95% confidence interval [CI], 1.03-1.66). MetS prevalence increased stepwise with worsening lifestyle in both low and high PRS_MetS groups. Compared to the 'low PRS_MetS and ideal lifestyle' group, MetS risk was significantly higher in all other lifestyle groups, with the highest risk observed in the 'high PRS_MetS and poor lifestyle' (aOR, 9.35; 95% CI, 4.41-19.83) group. Both genetic predisposition and lifestyle factors significantly influenced MetS risk. Maintaining healthy lifestyle habits mitigates MetS risk, even in individuals with high genetic susceptibility.