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Precision Medicine and Clinical Care

Chapter 5 | Harrison's 22e · Part 1 – The Profession of Medicine · Chapter 5

Key Clinical Points

  1. Precision medicine integrates genomic context with individual patient preferences to move beyond 'average' patient outcomes.
  2. Evidence-Based Medicine (EBM) provides an "inductive generalization" rather than a finished set of tools; clinical reasoning and experience remain paramount.
  3. The "Arc of Reductionism" describes the historical shift from clinical observation to organ pathology, then to cellular/molecular biology.
  4. Reductionism's limitations: Over-simplified models often fail to account for biological variety (e.g., sickle cell disease has one mutation but many distinct clinical manifestations).
  5. Convergent phenotypes occur when different diseases present with similar symptoms (e.g., heart failure, end-stage kidney disease).
  6. Divergent phenotypes occur when a single underlying pathology results in distinct clinical presentations (e.g., aortic stenosis vs. antiphospholipid syndrome).
  7. Prognostic enrichment reduces heterogeneity in trials; Predictive enrichment identifies specific responders to treatments.
  8. Drug repurposing utilizes network analysis to find "short paths" between disease genes and known drug targets.
  9. Pharmacogenomics (e.g., TPMT, CYP2C19) allows for tailored dosing based on individual metabolic profiles.
  10. The "Reticulotype" represents a patient-specific multiomic network structure used to define unique biological fingerprints.
  11. A "Network of Networks" approach integrates genomics, transcriptomics, proteomics, metabolomics, and environmental factors.

DEFINITION & CLASSIFICATION

• Precision Medicine: An integrative approach that incorporates genomic context and individual patient preferences into clinical care. • Reticulotype:

Definition (Harrison's 22e): Patient-specific genotype-phenotype relationships by multiomic network structures. ◦ These unique biological fingerprints are derived from multiomic analyses (genomics, transcriptomics, metabolomics, etc.) to provide the basis for patient-specific, precision therapies.

ETIOLOGY & PATHOPHYISIOLOGY

• Historical Context of Nosology: ◦ 19th Century: Shift from holistic descriptions to clinicopathologic observation. ◦ Morgagni (1761): Correlated clinical features with over 600 autopsies, establishing an anatomic basis for disease pathophysiology. • Arc of Reductionism: ◦ 18th Century: Clinical Observation (e.g., "Phthisis"). ◦ Early 19th Century: Gross Pathology (Lesions of organs and tissues). ◦ Late 19th Century: Cellular Pathology (Lesions of cells). ◦ Modern Era: Molecular biology and genomics. • Limitations of Reductionism: ◦ Over-simplified reductionism often fails to account for the extensive biological variety and complexity of diseases. ◦ Example: A single mutation in the globin β chain causes sickle cell disease, but this single molecular cause does not predict the diverse clinical manifestations (stroke, hemolytic crisis, etc.). ◦ Conclusion: The field is moving toward an integrative approach that considers multi-gene (monogenic, oligogenic, polygenic) and environmental influences (epigenetics).

CLINICAL FEATURES

• Phenotypic Diversity: ◦ Convergent Phenotypes: Different diseases presenting with similar clinical signs/symptoms. ◦ Examples: Heart failure, end-stage kidney disease. ◦ Divergent Phenotypes: A single underlying pathology resulting in distinct clinical presentations. ◦ Example: Antiphospholipid syndrome vs. aortic stenosis (different mechanisms leading to different clinical manifestations).

DIAGNOSTIC APPROACH

• Clinical Trial Design & Enrichment: 1. Population → Sample selection. 2. Enrichment Strategies: ◦ Prognostic Enrichment: - Goal: Decrease heterogeneity or increase representation of individuals with a high risk of observed outcomes. - Outcome: Facilitates trial conduct; does not necessarily improve precision in defining treatment response. ◦ Predictive Enrichment: - Method: Utilizes both trial participant characteristics and data from experiments conducted before or during (adaptive design) the trial. - Goal: Improve prediction of who is likely to have a more pronounced response to the treatment under study.

MANAGEMENT & TREATMENT

• Drug Repurposing via Network Analysis: 1. Identify disease-causing genes. 2. Perform network analysis to determine "proximity" (the proximity hypothesis). 3. Calculate shortest path to the closest drug target → identify candidates for repurposing (using existing drugs for new indications). • Pharmacogenomics & Tailored Therapy: 1. Identify specific genetic variants (e.g., TPMT, CYP2C19). 2. Correlate variant with metabolic pathways (e.g., thiopurine metabolism). 3. Adjust dosage or select drug based on individual's unique profile.

KEY PEARLS & HIGH-YIELD POINTS

• EBM Limitations: ◦ EBM provides an "inductive generalization" rather than a finished set of tools. ◦ Evidence gap: In cardiovascular guidelines, <15% of recommendations were based on the highest level of clinical trial evidence (a trend that persisted for 10 years). • Clinical Reasoning: ◦ Because many conditions cannot be tested in randomized trials, expert clinical reasoning and experience remain paramount. • Integration is Key: ◦ The future of medicine lies in an integrative approach: combining genomic context with individual patient preferences to manage complex diseases.