Mental Health, Genomic Medicine and Patient Care for our VeteransGerry Higgins, M.D., Ph.D.; Facilitator

Chair, Genomics Advisory Panel, OSHERA

TOPICS

1. Mental Health Services – Challenges:→ Suicide→ Post-Traumatic Stress→ Treatment-resistant depression→ Poly-pharmacy and comorbidity

2. The Importance of the Million Veteran Program and Genomic Medicine at the VA

3. Integration of Genome Data into the VA’s EHR:→ Why it is important for the individual Veteran→ Update, challenges and risks

Rank order, Top Health Care Challenges in the Veterans Health Administration;

Survey of 67 VA Clinicians, All Specialties at 24 Sites:1

1. Treatment-Resistant Depression2. Treatment-Resistant Anxiety3. Traumatic Injury4. Addiction / Alcoholism5. Posttraumatic stress6. Cardiovascular Disease7. Oncology8. Gastroenterology9. Dementia10. Sleep Disorders

1. Conducted by Liberty Mutual Patient Safety Institute under contract with the VHA.

Challenges - Suicide

→“Suicide rates among Veterans treated in the VA System are about 50% higher than in the general population, and the rate of suicide among active duty service personnel has recently exceeded the rate in the general population.”

→From DoD Suicide Event Report Program (2008-2010):Previous diagnosis of Mood Disorder including Bipolar 22%Previous diagnosis of Anxiety Disorder 19%Previous diagnosis of Major Depressive Disorder 14%Previous diagnosis of Posttraumatic Stress 6%Outpatient behavioral health care visit within past 30 days 21%Outpatient health care consultation visit within past 30 days 44%Taking or previously taken psychotropic medications? 23%

Challenges - PTS→ Using the strictest PCL criterion for OIF/OEF Veterans

→ Time-course using DSM-5 ‘Experiencing’ criteria

PRE-DEPLOYMENT POST-DEPLOYMENTGrouped: 3.0%(95% CI: 2.9-3.1)

Support Unit 5.0% (95% CI: 4.9-5.2)Operational Unit 19.6% (95% CI: 19.1-20.2)

1 month

3 months

6 months

12 months

10 years

20 years*

0

5

10

15

20

25

30

35Unintentional Exposure to trauma

Intentional Exposure to Trauma

Israeli War Veterans

Perc

enta

ge d

iagn

osed

*5.2% after 20 years

Challenges – Treatment-Resistant Depression→Major depressive disorder (MDD) strikes 14% - 17% of

Americans during their lifetime.→ >30% of individuals with MDD do not achieve remission after 4

long antidepressant trials.→ 22% of Americans view MDD as a ‘personal weakness.’→ MDD costs the U.S. economy an estimated $150 B each year.→Co-morbidities:

MDD

SUICIDE

PTS

CARDIO

Poly-Pharmacy

Goals of VA Genomic Medicine Program• Collect and link genetic information with VA

Electronic Health Record and thereby:o Discover genetic predispositions, causes and

mechanisms of diseaseo Better define treatments

Pharmacogenomic & interventional customizationo Via research, advance understanding in all these

areas

• Establish how genetic information will be used in clinical medicine

o Translational research to link genotype to phenotypeo Complex, adult, multi-gene diseases possibly with

strong environmental influences

• The Million Veteran Programo ‘Whole genome sequencing & analysis’ to provide

largest study of disease associations and human genetics

o Will help all studies examining how genome variants lead to disease and help understand gene x environment interactions

Breakthroughs in Epigenomics may lead tounderstanding of how combat stress leads to PTSEpigenomics: A genomic approach to studying environmental effects, primarily DNA methylation, on gene function.

Repetitive combat stress causes

Epigenomic changes to genes in the

stress response

Breakthroughs in Epigenomics may lead tounderstanding of how combat stress leads to PTS

Combat stress → Prolonged stress Hypermethylation of PTS response glucocorticoid receptor

Breakthroughs in Epigenomics may lead tounderstanding of how combat stress leads to PTS

→ Patients with PTSD have increased plasma levels of cortisol, show a dysfunctional cortisol rhythm, and an exaggerated stress response.

PlasmaCortisol

Clinical Decision Support in the EHR - Only First Phase of Omic Integration

into EHRs

1.Centrally managed repositories of medical

knowledge2. Standardization of CDS

information for genomic medicine

3. Standard approach for representation and locating patient data

1.Computer processable medical knowledge

2.Computer-interpretable patient data

3.Generation of patient-specific advice using knowledge and patient data

Architecture for Pharmacogenomic Decision Support1:

Infrastructure Overview of Required Elements

1Based on: Kawamoto K et al. A national clinical decision support infrastructure to enable the widespread and consistent practice of genomic and personalized medicine. BMC Medical Informatics and Decision Making. 2009; 9:17 doi:10.1186/1472-6947-9-17.

Pharmacogenomic

Decision Support

Resources

CDS

Pre-Requisites

→ Rules Engine→ MLM→ Machine Learning component such as

Support Vector Machine (SVM)→ Remote web access input

→ Here are some reasons that the DGI domain has not received the focus it deserves:

A. Drug-drug interactions are difficult to model, except in a generic manner, and once the algorithm has to handle many drug pairs (i.e., >2) it becomes an impossible combinatorial problem – especially as poly-pharmacy seems to be on the rise. To add a patient's variable metabolizer phenotype into the math, and the problem becomes intractable.

B. The advent of next generation sequencing (NGS) has changed everything. Every vendor is very concerned that maintenance and upgrades will require tremendous resources to keep up with the very rapidly world of ‘omics.

C. Physicians are already upset about medication alert fatigue, and since they were never thoroughly educated in genomics or pharmacogenomics, vendors are uncertain about how to proceed. In addition, both professional medical organizations and payors are still somewhat skeptical about gene testing.

Architecture for Advanced Pharmacogenomic Decision Support:

What’s Missing? Drug – Gene Interactions (DGIs)

Preemptive Genotyping

High Risk Patients in

Medical Home

Obtain known actionable

pharmacogenomic variants for each

patient using multiplexing / NGS

panels

Inpatient Gets New

Prescription

Store pharmacogenomic

data in EHR

Trigger

Search for pharmacogeno

mic data in

patient’s EHR

Find possible risk variant

Advanced pharmacogeno

micdecision support

EHR system automatically

provides physician with

optimal therapeutic regimen for

patient

1. How could this be achieved?

2. Since epigenomic data, which has been highly replicated, shows a correlation between hyper-methylation of the glucocorticoid receptor and PTS (as well as MMD and BPD) – how can we integrate these data?

3. What concerns do Veterans have about protection of personal privacy in this rapidly moving domain?

Possible integration of omic data directly into the VistA electronic health record

END OF PART ONE:

Questions?

Discussion?