Conference Presentation, Panel, Roundtable
Decoding Disease: Can Genetics Unlock New Interventions? | Future of Health Summit 2024
- Genetically informed therapies and treatments are expected to reach the market, with pre-pregnancy and preterm genetic testing accelerating patient eligibility for gene therapy upon birth.
- A 10 to 15-year horizon is projected to systematically unlock genetic discoveries for all human diseases by coupling large-scale biobanks with electronic health records.
- A specific goal targets sequencing a quarter million individuals with bipolar disorder within the next five to seven years across international settings and diverse genetic ancestries.
- Chronic diseases such as Alzheimer's and type 2 diabetes will be subdivided into multiple molecular subtypes, similar to the 80 histological subtypes of breast cancer currently recognized.
- Disease reduction research pace will improve significantly due to gene editing capabilities in model systems, a process reduced from years to one day.
- Common diseases like bipolar disorder and diabetes will be fractured into coherent subsets by identifying strong-acting rare variants to facilitate targeted interventions.
- Drug discovery for common diseases will adopt a reductionist approach focusing on rare variants to increase effect sizes, thereby reducing trial sizes and improving pricing and access.
- The proportion of the drug pipeline supported by genetic evidence is expected to rise continuously, though many targets will be tested in clinical trials for traits not initially indicated by the genetics.
- Genomic data analysis combining next-generation sequencing with machine learning will direct targeted therapies and enable non-invasive disease monitoring via DNA methylation detection in blood, urine, and saliva.
- Health outcomes data tracking the impacts of genomic testing is anticipated to become available within five years as population health programs expand.
- Healthcare providers will increasingly rely on AI tools integrated into electronic health records to determine when and for whom to order genetic testing.
- AI applications will evolve to predict biologically active protein parts and integrate complex data non-linearly, though very large language models may eventually hit a utility plateau.
- Comprehensive genetic data from minority populations, particularly African American, Hispanic, and Latino groups, is required to overcome limitations in data derived solely from European ancestry.
- Policy, regulation, and social acceptance are expected to lag behind scientific discovery, creating bottlenecks in drug approval and patient access.
- Current reimbursement structures and provider recognition create barriers; Medicare does not recognize genetic counselors as a provider type, and Medicaid coverage remains variable across the nation.
- Legislation to pass the Access to Genetic Counselor Services Act is necessary to enable hospitals to hire genetic counselors, who will play a critical role in coordinating care and interpreting gene-environment interactions.
- Despite guidelines recommending genetic testing for men with metastatic prostate cancer, a vast majority of patients will not receive testing, partly due to a need for more data on risk alleles in men of African ancestry.
- Genetic counseling and "genetic navigator" roles will expand to help patients understand results, navigate the clinical community, identify clinical trials, and improve adherence to lifestyle modifications.
- Technological development is needed to create cellular models that more accurately recapitulate human biological processes, specifically ensuring neurons in a dish behave like those in the human body.
- Large-scale research projects like "All of Us" will enable patients to participate in research, while AI tools will assist rare disease families in identifying others with similar genetic changes to attract drug company attention.
- Prevalence rates for rare diseases will increase as sequencing identifies more patients with relevant mutations for specific drugs.
- Behavioral modification driven by genetic risk information is expected to improve healthcare outcomes, with patients responding better to genetic insights than standard medical advice.
- Rapidly evolving clinical guidelines may outpace the ability of community hospital providers to keep up with the latest standards.
- The cost of sequencing continues to decline, facilitating broader patient access and enabling the development of larger research and clinical diagnostics programs.
- Clinical practice in cancer currently leads the science curve regarding the adoption of sequencing technology, whereas a narrow treatment window remains a challenge for patients with aggressive or metastatic disease forms.
- Structural analysis of proteins is advancing and will feed back into genetic discovery cohorts to enrich signals, while next-generation sequencing and AI will help analyze vast genomic data to direct targeted therapy.
- Novel markers and algorithms must be developed to monitor treatment-induced genomic changes and incorporate family history, diet, and lifestyle factors to address tumor heterogeneity.
- Drug discovery efforts will increasingly focus on reversing strong-acting mutations in model systems to address specific subsets of individuals, potentially improving response rates and reducing trial duration.
- Psychiatrists may utilize genetic insights regarding the ACAP11 gene to guide lithium use in individuals with psychosis and mood disruption.