Dr. Michael Boehnke (University of Michigan) – who pioneered large-scale studies identifying genetic risk in diabetes and bipolar disorder – shared with us some recent insights about recent advances in exome and genome sequencing and their applications to better understand disease biology and etiology of psychiatric disorders, the relevance of statistical data analysis to overcome the burden of multiple testing, and how the genome can influence the epigenome to modulate gene expression and risk of type 2 diabetes.

Dr. Boehnke is a true pioneer in precision medicine having conducted a number of the first large scale studies to identify genetic risk in diabetes and bipolar disorder. As a biostatistician, Dr. Boehnke’s research focuses on the genetic dissection of complex traits. In his 35-year career he has developed methods for analysis of human pedigrees, examined the history of breast cancer in genetically at risk individuals, and contributed important discoveries on the genetics of type 2 diabetes and related traits, such as obesity and blood lipid levels. He has served on the University of Michigan faculty since 1984, focusing on problems of study design and statistical analysis of human genetic data with a particular emphasis on development and application of statistical methods for human gene mapping. His current focus is on disease and trait association studies based on genome sequence and genotype-array data. Read his full bio.

PMWC 2018 Michigan takes place June 6-7, 2018.

Q&A with Michael Boehnke

Q: Little is known about the molecular basis of mood and psychotic disorders such as bipolar and schizophrenia. How do genetic studies using whole genome or exome analysis provide us an insight for the development of novel drugs, therapies, and preventive strategies?

A: Genome-wide association studies (GWAS) based on genotype arrays or sequencing identify genetic variants associated with any disease (or trait), including these psychiatric disorders. Availability of low-cost arrays assaying millions of sites in the genome together with clever statistical and computational tools now allow us to assay all but the rarest or most complex genetic variation in hundreds of thousands or even millions of individuals. Exome and genome sequencing allow near-complete assay even of very rare genetic variation, but sequencing costs need to fall even further to allow the sample sizes we need to identify disease-associated variants with high statistical confidence. Each disease-associated region we identify provides a potential entry point to understand disease biology and etiology, to suggest targets for new drugs, or to better target existing drugs to people for whom they will be helpful and not harmful. Taking the step from associated variant to causal mechanism to a drug is challenging, and a major focus for both academic and pharmaceutical researchers. The good news is that drug targets suggested by genetic studies have a substantially higher rate of progressing through the drug development pipeline than those without support from genetic studies.

Q: What are the challenges and some of the solutions you developed for analyzing genome or exome sequence data from 10,000s of individuals?

A: Analysis of sequence data challenges us computationally and statistically. A BAM file which includes the complete information for a single human genome requires 25 x 109 bytes (25 gigabytes) of computer storage, so that for our NHLBI-funded TOPMed project which has to date sequenced >120,000 genomes requires storage of 3 x 1015 bytes (3 petabytes) of data. It was only a few years ago I learned what the prefix peta meant! Dealing with that much data requires careful consideration of issues such as minimizing data transfers and avoiding multiple data copies. While the cost of sequence data generation has dropped by many orders of magnitude, the cost of computer storage has dropped more slowly, making careful data management critical.

Statistical analysis of such large data files also is challenging and has required us to develop analysis software that is computationally very efficient. To test for association with many millions of sites in the genome requires extreme levels of statistical significance to overcome the burden of multiple testing, so that many of our standard statistical tests are no longer well behaved and have to be modified. For example, we use modified disease association tests when the number of cases with disease is much smaller than the number of controls without disease. Carrying out so many tests on such large samples also requires very careful quality control to avoid even a low rate of false positives that would swamp true association signals with spurious ones. For example, we developed methods to identify and discard DNA samples that are contaminated by DNA from another person.

Q: What are the challenges we face and the opportunities that exist in resolving the complex processes underlying common diseases such as breast cancer and obesity?

A: We geneticists always need to keep in mind that genetics is just small part of the overall picture, and that environmental and behavioral factors also are critical to health and disease. Still, genetic information has the advantages that it is simple (a 4-letter alphabet), finite (3 billion base pairs is a lot, but is finite), and does not change (so we can measure it once and use it forever), whereas behaviors and the environment change all the time and measuring and summarizing them is truly challenging. GWAS identify genetic regions associated with disease, providing valuable entry points to understand human biology and disease. We seek to move from genomic regions to specific causal variants, genes, and pathways, which in turn can illuminate the complex causal processes underlying these and other diseases.

Q: You published last year a paper on genetic regulatory signatures that are associated with increased risk for type 2 diabetics. What is the significance of this discovery and could it help lead to more personalized treatments for diabetes?

A: My research group and our collaborators are working to understand the genetic basis of type 2 diabetes. Our work has identified hundreds of regions in the human genome that impact risk to type 2 diabetes and variability to diabetes-related traits like glucose and insulin levels. An important next step is to identify the specific genes and genetic variants involved, and their mechanisms of action. In Varshney et al., we presented an integrated analysis of human pancreatic islet molecular profiling data. We found that genetic variants associated with type 2 diabetes are more frequently present in regions of the genome where transcription Regulatory Factor X (RFX) is predicted to bind in an islet-specific manner, and that genetic variants that increase type 2 diabetes risk are predicted to disrupt RFX binding. Our findings provide a molecular mechanism by which the genome can influence the epigenome, and so modulate gene expression and risk of type 2 diabetes. It is our hope that these sorts of mechanistic insights, that result from combining molecular data on open chromatin and gene expression with other sources of genomic annotation can help pinpoint the functional mechanisms underlying type 2 diabetes and lead to better understanding of type 2 diabetes etiology and treatment.

Interview with Gabriel Bien-Willner of Palmetto GBA

Q: What does your role entail as the director of the MolDX program at Palmetto GBA?

A: The job directing MolDX is multifaceted; first and foremost the MolDX program is responsible for assessing molecular diagnostic tests on the market and makes coverage and pricing determinations for such tests and technology. This is usually done through local coverage determination policies or technical assessments.

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Interview with Peter Marks of FDA

Q: The CBER’s Regenerative Medicine Advanced Therapy Designation program has been very successful, with about 100 requests for designation in the two years of its existence. Can you please tell us about the program and how it was put together?

A: The Regenerative Medicine Advanced Therapy (RMAT) Designation program came into being as part of the 21st Century Cures Act that was signed into law on December 13, 2016.

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Interview with Calum MacRae of Harvard Medical School

Q: What patient data do we need to better understand the underlying cause of disease and how to prevent it?

A: Medicine at present is highly underdetermined and data poor. To be precise, one must be comprehensive, so medicine (with our consent) will use not only what we currently conceive of as biomedical information, but also data from across our lives.

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Headlines from PMWC 2019 Silicon Valley

A big ‘Thank You’ to all of our presenters and attendees for celebrating 10 years of precision medicine progress with us! PMWC 2019 Silicon Valley was attended by 2000 participants from 35 countries, which included over 400 speakers in 5 parallel tracks!

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Interview with Ken Bloom of Ambry Genetics

Q: Tell us more about your organization/company. What patient population are you serving and which services are you specializing in?

A: Ambry Genetics is a recognized leader in high quality complex genetic testing. We seek to find the genomic cause or contributors to rare diseases, abnormal phenotypes and hereditary disorders.

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Interview with Lee Pierce of Sirius Computer Solutions

Q: What is the state of big data and analytics in healthcare, and how to best use the reams of data available?

A: More than ever, Healthcare organizations are achieving measurable value through use of their data and analytics assets. There is more raw material available than ever to create value. This raw material is the data flowing from internal systems and applications and also from devices and systems external to healthcare organizations.

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Interview with Anita Nelsen of PAREXEL

Q: There are various new, emerging technologies that bring us closer towards a cure for life-threatening disorders such as cancer, HIV, or Huntington’s disease. Prominent examples include the popular gene editing tool CRISPR or new and improved cell and gene therapies. By when can we expect these new technologies being part of routine clinical care?

A: Today’s emerging technologies are making the promise of individualized treatment a reality.

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Interview with Ilan Kirsch of Adaptive Biotechnologies

Q: The Nobel Prize in Medicine was awarded recently to James Allison and Tasuku Honjo for their work on unleashing the body’s immune system to attack cancer, a breakthrough that has led to an entirely new class of drugs and brought lasting remissions to many patients who had run out of options. The Nobel committee hailed their accomplishments as establishing “an entirely new principle for cancer therapy.” What is your first-hand experience the impact that those new drugs had on patients?

A: For decades cancer was viewed as solely a cell-autonomous condition.

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BMS buys Celgene | Lilly buys Loxo Oncology – Does this Signal a Return to Strong Deal-Making Activities in 2019?

Bristol-Myers Squibb’s blockbuster $74B deal to buy Celgene creates an oncology powerhouse amid industrywide excitement about the rapidly evolving science and explosive growth of the sector. The agreement could signal a return to deal-making for the pharmaceutical industry in the $133B global oncology therapeutics market.

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Interview with Gini Deshpande of NuMedii

Q: What need is NuMedii addressing?

A: NuMedii, has been pioneering the use of Big Data, artificial intelligence (AI) and systems biology since 2010 to accelerate the discovery of precision therapies to address high unmet medical needs. Artificial Intelligence approaches are a natural fit to harness Big Data as they provide a framework to ‘train’ computers to recognize patterns and sift through vast amounts of new and existing genomic

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Interview with Minnie Sarwal of UCSF

Q: Genomic medicine is entering more hospitals and bringing with it non-invasive technology that can be used to better target and treat diseases. What are some key milestones that contributed to this trend?

A: Completion of complete sequence data from the human genome project, and the advances in proteomic, microRNA and epigenetic assays added a layer of pathway biology to the understanding of human diseases.

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Interview with Shidong Jia of Predicine

Q: Once sequencing has been validated as a clinical solution via trusted workflows, and coinciding with the technological developments driving costs lower, we can expect accelerated human genome profiling for clinical Dx. How soon, do you think, will we see accelerated growth and what can we expect?

A: We will see accelerated human genome profiling for clinical Dx in 2019 and the coming years as more biomarker-based cancer drugs are gaining approval.

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Interview with Iya Khalil of GNS Healthcare

Q: Artificial intelligence (AI) techniques have sent vast waves across healthcare, even fueling an active discussion of whether AI doctors will eventually replace human physicians in the future. Do you believe that human physicians will be replaced by machines in the foreseeable future? What are your thoughts?

A: I think that there’s a lot of speculation and uncertainty around AI, but I don’t foresee a time when we won’t need physicians.

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Interview with Ilya Michael Rachman of Immix Biopharma Inc.

Q: The Nobel Price in Medicine was awarded recently to James Allison and Tasuku for their work on unleashing the body’s immune system to attack cancer, a breakthrough that has led to an entirely new class of drugs and brought lasting remissions to many patients who had run out of options. The Nobel committee hailed their accomplishments as establishing “an entirely new principle for cancer therapy.” Besides CAR T-cell therapy what do you think next generation immunotherapies will look like to successfully combat cancer?

A: The next generation of immunotherapies will build on the insights discovered by immunologists like James Allison and Tasuku Honjo and extend them to modify the body’s response to tumors.

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Join me to Kick off PMWC Silicon Valley in the Santa Clara Convention Center, Focusing on Every Element of Precision Medicine

My team worked in collaboration with Bill Dalton, Kim Blackwell, Atul Butte / India Hook Barnard, Nancy Davidson and Sharon Terry to create a program that touches every component of precision medicine while bringing together all of its key stakeholders. Leading participating institutions including Stanford Health Care, UCSF, Duke Health, Duke University, John Hopkins University, University of Michigan and more will share their learnings and experiences and their successes and challenges, as they make precision medicine the new standard of care for all.

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Johns Hopkins
University Of Michigan

The Precision Medicine World Conference (PMWC), in its 17th installment, will take place in the Santa Clara Convention Center (Silicon Valley) on January 21-24, 2020. The program will traverse innovative technologies, thriving initiatives, and clinical case studies that enable the translation of precision medicine into direct improvements in health care. Conference attendees will have an opportunity to learn first-hand about the latest developments and advancements in precision medicine and cutting-edge new strategies and solutions that are changing how patients are treated.

See 2019 Agenda highlights:

  • Five tracks will showcase sessions on the latest advancements in precision medicine which include, but are not limited to:
    • AI & Data Science Showcase
    • Clinical & Research Tools Showcase
    • Clinical Dx Showcase
    • Creating Clinical Value with Liquid Biopsy ctDNA, etc.
    • Digital Health/Health and Wellness
    • Digital Phenotyping
    • Diversity in Precision Medicine
    • Drug Development (PPPs)
    • Early Days of Life Sequencing
    • Emerging Technologies in PM
    • Emerging Therapeutic Showcase
    • FDA Efforts to Accelerate PM
    • Gene Editing
    • Genomic Profiling Showcase
    • Immunotherapy Sessions & Showcase
    • Implementation into Health Care Delivery
    • Large Scale Bio-data Resources to Support Drug Development (PPPs)
    • Microbial Profiling Showcase
    • Microbiome
    • Neoantigens
    • Next-Gen. Workforce of PM
    • Non-Clinical Services Showcase
    • Pharmacogenomics
    • Point-of Care Dx Platform
    • Precision Public Health
    • Rare Disease Diagnosis
    • Resilience
    • Robust Clinical Decision Support Tools
    • Wellness and Aging Showcase

See 2019 Agenda highlights:

    • Five tracks will showcase sessions on the latest advancements in precision medicine which include, but are not limited to:
      • AI & Data Science Showcase
      • Clinical & Research Tools Showcase
      • Clinical Dx Showcase
      • Creating Clinical Value with Liquid Biopsy ctDNA, etc.
      • Digital Health/Health and Wellness
      • Digital Phenotyping
      • Diversity in Precision Medicine
      • Drug Development (PPPs)
      • Early Days of Life Sequencing
      • Emerging Technologies in PM
      • Emerging Therapeutic Showcase
      • FDA Efforts to Accelerate PM
      • Gene Editing / CRISPR
      • Genomic Profiling Showcase
      • Immunotherapy Sessions & Showcase
      • Implementation into Health Care Delivery
      • Large Scale Bio-data Resources to Support Drug Development (PPPs)
      • Microbial Profiling Showcase
      • Microbiome
      • Neoantigens
      • Next-Gen. Workforce of PM
      • Non-Clinical Services Showcase
      • Pharmacogenomics
      • Point-of Care Dx Platform
      • Precision Public Health
      • Rare Disease Diagnosis
      • Resilience
      • Robust Clinical Decision Support Tools
      • Wellness and Aging Showcase
  • Luminary and Pioneer Awards, honoring individuals who contributed, and continue to contribute, to the field of Precision Medicine
  • 2000+ multidisciplinary attendees, from across the entire spectrum of healthcare, representing different types of companies, technologies, and medical centers with leadership roles in precision medicine
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