Integrating Mendelian randomization, machine learning and retrospective clinical data: an exploratory analysis of the cross-disease association between CHB and PD, with a focus on eosinophil alterations - Scorecard - MDSpire

Integrating Mendelian randomization, machine learning and retrospective clinical data: an exploratory analysis of the cross-disease association between CHB and PD, with a focus on eosinophil alterations

  • By

  • Yao Ge

  • Hongbin Cai

  • Yike Li

  • YaTing Li

  • HuiFang Liu

  • Guilin Zeng

  • Kui Yang

  • Yang Luo

  • July 9, 2026

  • 0 min

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Clinical Scorecard: Combining Mendelian Randomization, Machine Learning, and Retrospective Clinical Insights: An Investigative Study on the Interrelationship Between Chronic Hepatitis B and Parkinson's Disease, Emphasizing Eosinophil Changes

At a Glance

CategoryDetail
ConditionChronic Hepatitis B and Parkinson's Disease
Key MechanismsGenetic susceptibility, immune cell changes, phenylalanine metabolism
Target PopulationPatients with chronic hepatitis B and Parkinson's disease
Care SettingMulticenter clinical validation

Key Highlights

  • MR analysis indicates an inverse association between susceptibility to CHB and PD risk (OR = 0.82–0.94, p < 0.05).
  • RTN3 and MAP4K3 identified as priority cross-disease genes linking CHB and PD.
  • Phenylalanine metabolism shows dysregulated patterns between CHB and PD.
  • Eosinophil levels decline in CHB but rise in PD, suggesting a potential link to disease susceptibility.

Guideline-Based Recommendations

Diagnosis

  • Utilize Mendelian randomization to explore genetic associations.

Management

  • Consider the impact of NUC therapy on PD risk in CHB patients.

Monitoring & Follow-up

  • Monitor eosinophil levels as potential biomarkers in CHB and PD.

Risks

  • Be aware of confounding factors such as hepatic encephalopathy and cirrhosis in assessing PD risk.

Patient & Prescribing Data

Individuals with chronic hepatitis B and Parkinson's disease.

NUC therapy may influence PD risk over time.

Clinical Best Practices

  • Integrate multi-omics data for comprehensive patient assessment.
  • Employ machine learning for gene screening in chronic diseases.

Related Resources & Content

Original Source(s)

Integrating Mendelian randomization, machine learning and retrospective clinical data: an exploratory analysis of the cross-disease association between CHB and PD, with a focus on eosinophil alterations

  • by Yao Ge, Hongbin Cai, Yike Li, YaTing Li, HuiFang Liu, Guilin Zeng, Kui Yang, Yang Luo

  • July 9, 2026

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