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Archive for the ‘Genetics & Innovations in Treatment’ Category


First Cost-Effectiveness Study of Multi-Gene Panel Sequencing in Advanced Non-Small Cell Lung Cancer Shows Moderate Cost-Effectiveness, Exposes Crucial Practice Gap

WASHINGTON (June 27, 2019) — The results of the first economic modeling study to estimate the cost-effectiveness of “multi-gene panel sequencing” (MGPS) as compared to standard-of-care, single-gene tests for patients with advanced non-small cell lung cancer (aNSCLC) show that the MGPS tests are moderately cost-effective but could deliver more value if patients with test results identifying actionable genetic mutations consistently received genetically guided treatments. The results of the study, which was commissioned by the Personalized Medicine Coalition (PMC), underline the need to align clinical practices with an era of personalized medicine in which physicians can use diagnostic tests to identify specific biological markers that inform targeted prevention and treatment plans.

The study, which was published yesterday in JCO Clinical Cancer Informatics, analyzed the clinical and economic value of using MGPS testing to identify patients with tumors that over-express genetic mutations that could be targeted by available therapies designed to inhibit the function of those genes — a mainstay of modern care for aNSCLC patients. Using data provided by Flatiron Health, researchers examined clinical and cost information associated with the care of 5,688 patients with aNSCLC treated between 2011 – 2016, separating them into cohorts who received MGPS tests that assess at least 30 genetic mutations at once and those who received only “single-marker genetic testing” (SMGT) of less than 30 genes.

Compared to SMGT, the MGPS testing strategy, including downstream treatment and monitoring of disease, incurred costs equal to $148,478 for each year of life that it facilitated, a level suggesting that MGPS is moderately cost-effective compared to commonly cited thresholds in the U.S., which range from $50,000 to $200,000 per life year (LY) gained.

The authors of the study point out, however, that physicians only prescribed a targeted therapy to some of the patients whose MGPS test results revealed actionable mutations. MGPS tests can only improve downstream patient outcomes if actionable results are used to put the patient on a targeted treatment regimen that is more effective than the therapy they would otherwise have been prescribed. It is therefore impossible for the cost of an MGPS test to translate into additional LYs if actionable results do not result in the selection of a targeted treatment regimen.

Although MGPS testing revealed actionable mutations in 30.1 percent of the patients in the study cohort, only 21.4 percent of patients who underwent MGPS testing received a targeted treatment.

The study’s authors calculated that if all MGPS-tested patients with actionable mutations had received a targeted therapy, MGPS testing would deliver measurably better value ($110,000 per LY gained).

“This research underlines the importance of ensuring that clinical practices keep pace with scientific progress in personalized medicine so that we can maximize the benefits of diagnostic tests that can improve patient care and make the health system more efficient by ensuring that safe and effective targeted therapies are prescribed to those patients who will benefit,” said PMC President Edward Abrahams.

The study’s authors include Dr. Lotte Steuten, Vice President and Head of Consulting, The Office of Health Economics, London, U.K., and Affiliate Associate Faculty Member, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center; Dr. Bernardo Goulart, Associate Faculty Member, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center; Dr. Neal Meropol, Vice President, Research Oncology, Flatiron Health; Dr. Daryl Pritchard, Senior Vice President, Science Policy, Personalized Medicine Coalition; and Dr. Scott Ramsey, Director, Hutchinson Institute for Cancer Outcomes Research, Fred Hutchinson Cancer Research Center.

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About the Personalized Medicine Coalition:

The Personalized Medicine Coalition, representing innovators, scientists, patients, providers and payers, promotes the understanding and adoption of personalized medicine concepts, services and products to benefit patients and the health system. For more information, please visit www.personalizedmedicinecoalition.org.

SOURCE

From: Personalized Medicine Coalition <pmc@personalizedmedicinecoalition.org>

Reply-To: “Christopher Wells (PMC)” <cwells@personalizedmedicinecoalition.org>

Date: Thursday, June 27, 2019 at 9:32 AM

To: Aviva Lev-Ari <AvivaLev-Ari@alum.berkeley.edu>

Subject: First Cost-Effectiveness Study of MGPS in aNSCLC Shows Moderate Cost-Effectiveness, Exposes Crucial Practice Gap

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Real Time Coverage @BIOConvention #BIO2019: Chat with @FDA Commissioner, & Challenges in Biotech & Gene Therapy June 4 Philadelphia

Reporter: Stephen J. Williams, PhD @StephenJWillia2

 

  • taking patient concerns and voices from anecdotal to data driven system
  • talked about patient accrual hearing patient voice not only in ease of access but reporting toxicities
  • at FDA he wants to remove barriers to trial access and accrual; also talk earlier to co’s on how they should conduct a trial

Digital tech

  • software as medical device
  • regulatory path is mixed like next gen sequencing
  • wearables are concern for FDA (they need to recruit scientists who know this tech

Opioids

  • must address the crisis but in a way that does not harm cancer pain patients
  • smaller pain packs “blister packs” would be good idea

Clinical trial modernization

  • for Alzheimers disease problem is science
  • for diabetes problem is regulatory
  • different diseases calls for different trial design
  • have regulatory problems with rare diseases as can’t form control or placebo group, inhumane. for example ras tumors trials for MEK inhibitors were narrowly focused on certain ras mutants
Realizing the Promise of Gene Therapies for Patients Around the World

103ABC, Level 100

Speakers
Lots of promise, timeline is progressing faster but we need more education on use of the gene therapy
Regulatory issues: Cell and directly delivered gene based therapies have been now approved. Some challenges will be the ultrarare disease trials and how we address manufacturing issues.  Manufacturing is a big issue at CBER and scalability.  If we want to have global impact of these products we need to address the manufacturing issues
 of scalability.
Pfizer – clinical grade and scale is important.
Aventis – he knew manufacturing of biologics however gene therapy manufacturing has its separate issues and is more complicated especially for regulatory purposes for clinical grade as well as scalability.  Strategic decision: focusing on the QC on manufacturing was so important.  Had a major issue in manufacturing had to shut down and redesign the system.
Albert:  Manufacturing is the most important topic even to the investors.  Investors were really conservative especially seeing early problems but when academic centers figured out good efficacy then they investors felt better and market has exploded.  Now you can see investment into preclinical and startups but still want mature companies to focus on manufacturing.  About $10 billion investment in last 4 years.

How Early is Too Early? Valuing and De-Risking Preclinical Opportunities

109AB, Level 100

Speakers
Valuing early-stage opportunities is challenging. Modeling will often provide a false sense of accuracy but relying on comparable transactions is more art than science. With a long lead time to launch, even the most robust estimates can ultimately prove inaccurate. This interactive panel will feature venture capital investors and senior pharma and biotech executives who lead early-stage transactions as they discuss their approaches to valuing opportunities, and offer key learnings from both successful and not-so-successful experiences.
Dr. Schoenbeck, Pfizer:
  • global network of liaisons who are a dedicated team to research potential global startup partners or investments.  Pfizer has a separate team to evaluate academic laboratories.  In Most cases Pfizer does not initiate contact.  It is important to initiate the first discussion with them in order to get noticed.  Could be just a short chat or discussion on what their needs are for their portfolio.

Question: How early is too early?

Luc Marengere, TVM:  His company has early stage focus, on 1st in class molecules.  The sweet spot for their investment is a candidate selected compound, which should be 12-18 months from IND.  They will want to bring to phase II in less than 4 years for $15-17 million.  Their development model is bad for academic labs.  During this process free to talk to other partners.

Dr. Chaudhary, Biogen:  Never too early to initiate a conversation and sometimes that conversation has lasted 3+ years before a decision.  They like build to buy models, will do convertible note deals, candidate compound selection should be entering in GLP/Tox phase (sweet spot)

Merck: have MRL Venture Fund for pre series A funding.  Also reiterated it is never too early to have that initial discussion.  It will not put you in a throw away bin.  They will have suggestions and never like to throw out good ideas.

Michael Hostetler: Set expectations carefully ; data should be validated by a CRO.  If have a platform, they will look at the team first to see if strong then will look at the platform to see how robust it is.

All noted that you should be completely honest at this phase.  Do not overstate your results or data or overhype your compound(s).  Show them everything and don’t have a bias toward compounds you think are the best in your portfolio.  Sometimes the least developed are the ones they are interested in.  Also one firm may reject you however you may fit in others portfolios better so have a broad range of conversations with multiple players.

 

 

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Tweets and Re-Tweets by @Pharma_BI ‏and @AVIVA1950 at 2019 Petrie-Flom Center Annual Conference: Consuming Genetics: Ethical and Legal Considerations of New Technologies, Friday, May 17, 2019 from 8:00 AM to 5:00 PM EDT @Harvard_Law

 

Tweets by @Pharma_BI ‏and @AVIVA1950

  1.   Retweeted

    AMAZING conference on Genomics and Ethics

  2. Amazing Conference LIVE 2019 Petrie-Flom Center Annual Conference: : and Considerations of New Technologies, Friday, May 17, 2019 from 8:00 AM to 5:00 PM EDT via

  3. Concluding remark cited by ⁦⁩ ⁦ Great Panel on the Impact of Genetic Information new conceptual approach prioritizing parental autonomy with restriction built in

  4. ⁩ ⁦ NIPT test for fetal sex blood type Trisonomy Whole Genome-wide analysis routinization of procedure READY at Birth impact intrafamilial discrimination babySeqProject G2P ⁦

  5. Leila Jamal, NIAID Pre- Test Genetic Counseling – information and testing need, indication for testing Post-Test Informational Burden low vs high: Likely pathogenic, Pathogenic benign – natural history data potentially high impact

  6. Leila Jamal, NIAID benefit the patient, positive autonomy, benefiesence – how potentially impactful is the Test Information Nondirectiveness – Why? distance from eugenics + abortion politics persons and patient autonomy

  7. Leila Jamal, NIAID Genetic and Genomics Testing: Prenata, Pediatric, Vancer, other: Cardiology, Neurology, Hematology, Infectious diseases, pharmaco genomics, DTC, Ancestry

  8. Emily Qian, Genetic Counselor, Veritas Genetics – Physician-Mediated Elective Whole Genome Sequencing Tests: Impacts on Informed Consent DTC Physician-initiated Genetic Testing Physician-initiated DTC Informed consent is a process

  9. ⁩ ⁦ Recommendation based on best evidence guidelines available

  10. Natalie RamGenetic Genealogy and the Problem of Familial Forensic Identification Familial Forensic Identification – Privacy for information held by Telephone companies Involuntarily Identification by genetic data genetic markers

  11. Natalie Ram, Assistant Professor of Law, University of Baltimore School of Law – Genetic Genealogy and the Problem of Familial Forensic Identification Opt in to share genetic data on the platforms opt in national DB

  12. Natalie Ram, Univ of Baltimore School of Law Genetic relatedness is stickier than social relations Voluntary sharing of genetic information – no other party can protect genetic information of any person, thu, if shared voluntarily

  13. ⁩ ⁦ gene APO-E e-2, e-3, e-4 If e-4 variant risk AD is 40% 23andMe since 2011 rest for e-4 unlock result # copies of e-4 are present little clinical value post diagnosis recommendation do not depend on e-4

  14. Jonathan Kahn, Precision Medicine and the Resurgence of Race in Genomic Medicineprecision medicine – classification of individuals into subpopulations that differ in their susceptability to a particular disease

  15. Kif Augustine-Adams, BYU Law School – Generational Failures of Law and Ethics: Rape, Mormon Orthodoxy, the Revelatory Power of Ancestry DNAComplex Sorrows: Anscestry DNA – 20 Millions records. Complete anonymity and privacy collapsed

  16. Regulating Consumer Genetic Technologies Conclusions: DTC policies are over the place, FDA poised to regulate Big Data, Human Genomics Somatic vs Germline are key distinctions NY Dept Health 3rd Party Certification in Genomics

  17. Scott Schweikart, Council on Ethical and Judicial Affairs, American Medical Association and Legal Editor, AMA Journal of Ethics – Human Gene Editing: An Ethical Analysis and Arguments for Regulatory Guidance National and Global Levels

  18. Catherine M. Sharkey, The Emerging Role of the FDA Genetic predisposition – BRCA I & II approved Testing Pharmaco-genetic Test authorization incorrect interpretation, incorrect action based on results False positive and False negative

  19. Scott Schweikart, AMA Ethical concernsTechnologiesCRISPR-Cas-9 Somatic vs GermlineAMA: Individual liberty (1) Autonomy & Gene Editing (2) Non-maleficence and Beneficence (3) Social Justice Treatment vs Enhancement National Regulations

  20. Patricia J. Zettler, Regulators can do: Promote self regulations vs restrict community labs Drugs: premarket approval by FDA 11/2017: any use of CRISPR is subjected to regulation Bio hacking materials are distributed outside channels

  21. Patricia J. Zettler, FDA agency – regulation can’t reach everything, Not seen wide range abuse, FDA encourage learning and information dissemination and Educate

  22. Maxwell J. Mehlman, Governing Non-Traditional Biology On-Line gene editing equipment CRISPR-Cas9 – IGEM – international Competition in community of Scientists Biological weapons – issues of Prior Art impeding patentability may come up

  23. Maxwell J. Mehlman Harm to subjects Biosafety Safety Phase I Gene drives in Human?? – Human gene editing: “Nanoparticle and liposomal delivery” and “Allelic drive using CRISPR”

  24. ⁩ ⁦ regulatory options: liabilities, legal requirements industry restrictions on access to material community labs, NTB IRBs self-governing bodies FBI surveillance

  25. Barbara J. Evans Is it FDA duty on Cosmetic enhancement Genome is Software, US is not good in regulating software The Harm Principle, Legal Paternalism benevolent vs non-benevolent Legal Moralism – no body is harmed but it’s just wrong

  26. Barbara J. Evans Multiple Agencies: In the 80’s on Future Products of Biotechnology: EPA, FDA, USDA, OSHA, CPSC, NIH, NEPA, ESA, APA Skepticism that compulsory regulation for compliance with norms

  27. Barbara J. Evans Regulatory Challenges Citizen Science and DIY Bio democratization of science and medicine narrative, new frontiers for institutional science narrative nostalgia narrative, political narrative: “hacker” portrayals

  28. in Preparing for Future Products of Biotechnology, NAS

  29. Seema Mohapatra, AAbolishing the Myth of “Anonymous” Gamete Donation in the Age of Direct-to-Consumer Genetic TestingAnonymous sperm donation Sell sperm $30 – $130 per sample – industry is thriving due to donor anonymity last 3 years,

  30. Seema Mohapatra, 2.6 million Ancestry DNA only to keep donor Anonymity Donor-Conceived Individuals at age 18 can identified the DonorLegal landscape ART – no federal laws regarding UT and WA [medical disclosure about the donor

  31. Nita Farahany, Professor Law, Philosophy Duke Law School need new Framework if anonymity is dead, most uses are diverted for medicinePrivacy is improving, ACA – protects from preexisting conditionsIndividual costs vs societal benefits

  32. Liza Vertinsky Courts: Pushing the boundaries: (1) Privacy (2) publicity rights (3) property (commodificationPresidential Figures: Infidelity gene, gambling geneLegal pathways Junk DNA Law enforcement databasesAlternative legal framing

  33. Kayte Spector-Bagdady, Data coming into Academia – Genetic data partnerships Academia (41% NIH funding) and Industry: Use of existing private data, company performs analysisPatients: using data and specimens in ways they do not wish

  34. Kayte Spector-Bagdady, to secondary research: stay anonymousPublic health covers Informed consent forms – conceptualize for secondary research protocols Transparency In BioBank Research 67% commercialization of biospecimens agree

  35. Property and Health Data: Excludability, Alienability and Divisibility, Valuation and compensation, Unstewarded and Orphan data, duration, tracking Propertization of medical information effect on biomedical research

  36. Genetic “Property” Statues: @CO – genetic information pertain to the individual health data – common law Personal Property vs Information as Property object

  37. direct consumer protection may get that by Claim of conversion – Common Law Genetic Testing companies are protected by three legal laws consumers as employees face genetic information been accessed by employers via Wellness Programs

  38. Courts shows a newfound openness to claims for genetic conversion claims will not stifle reaserch or create moral harms consumers genetics, claims for genetic conversion necessary to adequately protect people’s interests in their DNA

  39. ⁩ ⁦ three new regulations of ownership of genetic test information ownership even Dx of breast cancer Insurance may not cover BRCA testing

  40. ⁩ ⁦ employment law and genetic testing property ownership

  41. Family not in treatment relationship with the Researcher – Court rejected the claim family donated to research unfair benefir of the Hospital from the data and tissue donatedClaim of conversion – Common LawGene by Gene Family Tree DNA

  42. Insurance may or may not cover BRCA testing Law suit on that matter is pending

  43. Life insurance company initiated genetic testing: (a) Gatekeeping policy underwriting new comer applicants (b) Wellness Employer wellness programs incentivize healthy behavior Incorporate genetic testing into wellness Programs Testing

  44. wellness Programs Test for preventing genetic conditions Like BRCA, Lynch syndrome, preventable – win/win proposition –>>> Healthier employees. Studies show shift of cost from employer to employee and employer have access to genetic i

 

 

RE-TWEETS

 

  1.   Retweeted

    Max Mehlman thinks “DIYBio” is problematic b/c often team efforts; “biohacking” has negative connotations. Suggests “non-traditional biology.”

  2.   Retweeted

    In reviewing how reviewed various tests, Catherine Sharkey discusses how some were reviewed through De Novo and others through 510(k) pathway and benefits and drawbacks of each.

  3.   Retweeted

    . invokes THE CONE OF SILENCE. NO MORE DATA FROM THIS TALK! Medical/scientific publishing norms are weird.

  4.   Retweeted

    A very full house today (480 people registered!) for the Consuming Genetics conference . opening a day that promises to be fascinating. Kudos also for selecting hot topics and amazing speakers.

  5.   Retweeted

    Talking about her ⁦team’s ⁩ paper ⁦⁩ shows most patients want notification of commercial use of biospecimens, most are uncomfortable about profit from biospecimens, but feel better if reinvested in research.

  6.   Retweeted

    You don’t have to identify as a biohacker to understand their goals, interests, and culture.

  7.   Retweeted

    Blog post about about my upcoming presentation at Petrie-Flom Center’s upcoming Consumer Genetics conference this Friday, May 17.

  8.   Retweeted

    Incredibly difficult topic.

  9.   Retweeted

    I asked Maxwell Mehlman how he envisioned biohackers could form an IRB-style review process. One suggestion was to engage with insitutional IRBs. Raise your hand if you think an establishment IRB would approve enhancement experiments? (I don’t…)

  10.   Retweeted

    Gene editing has become cheaper, easier to do in community labs. Max Mehlman ⁦⁩ compares it to where Steve Jobs and Bill Gates began with the personal computer. But US gov has listed as a “weapon of mass destruction”

  11.   Retweeted

    Thanks to for hosting another great conference!

  12.   Retweeted

    “Diversity” means a LOT of different things–it’s very easy to slip back and forth (problematically) between molecular/genetic diversity and social constructs of race. Just using “diversity” elides and blurs important concepts. – Jonathan Kahn @

  13.   Retweeted

    Audience member during Q&A calls the first group of talks “very very interesting — and terrifying.” That’s what we’re here for, folks. These issues are real and we’re happy you’re here to talk about them with us.

  14.   Retweeted

    Just FYI my research showed you cannot waive statutory nondiscrim rights (under GINA or others) but can waive right to judicial forum to decide if there has been a violation (2009 Pyett v 14 Penn Plaza decision-ie case after GINA-overturned 30 years of precedence)

  15.   Retweeted

    FYI in Perlmutter & Peerenboom, the claim was not ownership in the DNA material. It was in the genetic information contained within it

  16.   Retweeted

    “If I want to edit my genes and make my skin glow green, whose business is that?” Barbara Evans on paternalism issues in our views of regulating DIYbio

  17.   Retweeted

    Takeaways from Regulating : Hazel: existing DTC genetic privacy policies are all over the place Sharkey: in an era of big data, FDA is poised to pose enhanced role as health information regulator Schweikart: in gene editing, somatic ≠ germline editing

  18.   Retweeted

    I have been waiting so long for this and is finally here!

  19.   Retweeted

    Many of the regulatory issues/possibilities raised by DIYbio will presented by (co-authors and ) “What can we do with what we’ve already got?”

  20.   Retweeted

    Moderators summary: In today’s panel we heard: -Property law won’t work -Anonymity is dead -Data is being commercialized and we don’t realize it -May be need for publicity rights for DNA. But there is hope. Good things are being done with this data.

  21.   Retweeted

    Is ⁦⁩ right, asks Vertinsky ⁦⁩,to be worried about “genetic ” publishing of information derived from your genetic information (especially discarded DNA). Or a presidential candidate ? What role for law?

  22.   Retweeted

    Interesting points by : Because many biohacking materials exchanges may not take place in traditional commercial contexts, attempting to regulate the trade of materials could prove difficult for FDA.

  23.   Retweeted

    We have not seen much FDA involvement in “genetic biohacking” says , but that might be a shame.Don’t need “harsh involvement” but “engagement” such as education — e.g., how long you can leave potato salad out at picnic, does not mean enforcement

  24.   Retweeted

    On genetic ownership and federalism. ⁦⁩ discusses the 5 states that have protected genetic property and skeptical about how well thought out the common law property approach has been. ⁩ ⁦

  25.   Retweeted

    “When you’re doing something that’s really high risk and cutting edge, maybe you SHOULD experiment on yourself–maybe that’s the most ethical way.” Barbara Evans talks up self-experimentation (reffing previous Nobels) @

  26.   Retweeted

    I feel simultanously very overwhelmed and very excited

  27.   Retweeted

    “Whatever the boundaries of FDA’s authority are [re: biohacking]…there are important questions about how it should use that authority.” @

  28.   Retweeted

    One person uploading info to a genetic database illuminates hundreds or thousands of other people–those people’s info isn’t “voluntarily” in datasets. Genetic databases familial searches aren’t voluntary. Natalie Ram @

  29.   Retweeted

    DIY gene therapy, CRISPR, etc. – failures likely to cause more harm (inadvertent) than successes. Speaker at analogizes to regulation of drones, beer, computer hacking many stakeholders with competing interests.

  30.   Retweeted

    Excellent talk by showing that in the face of clinicians can be legally damned if they do use revealed info and also damned if they don’t–potentially liable for patient’s misguided medical decisions

  31.   Retweeted

    “We need to rethink our Informed Consent methods for our secondary research protocols” – given all the confusion arising among Patients, their Doctors and the Researchers working with the data specimens about the use of the data, says – at Wasserstein Hall

  32.   Retweeted

    How do we deal with Publicity Rights in DNA? Thought-provoking talk by Professor Vertinsky of The “Genetic Paparazzi” conundrum – at Wasserstein Hall

  33.   Retweeted

    argues against recognizing Property Rights in personal health data: “A vast amount of ‘orphan Biomedical data’ is useless” – doesn’t help advance research in the field Other protections already available and more suitable

  34.   Retweeted

    Leading up to Friday’s Conference on Consuming Genetics () here’s a post about my topic: why law isn’t a good fit for health data.

  35.   Retweeted

    Professor Kif Augustine-Adams of says that individual privacy settings on Consumer Genetics testing have limited power; total anonymity is a myth. It is only a matter of time before the relational nature of DNA makes all connections identifiable. – at Wasserstein Hall

  36.   Retweeted

    “Wellness Programs” by Employers or Insurance underwriters – how should they deal with collecting genetic data? suggests Employers / Insurers only act as mediators between members and DTC genetic testing companies, and only get aggregate, anonymized data – at Harvard Law School

  37.   Retweeted

    Natalie Ram: there’s an idea of voluntariness re: searching & genetic information. THAT’S FICTION. Genetic relatedness is different–it’s sticky! “I could decline my aunt’s FaceBook request…but [she] can still serve as reliable-as-ever genetic informant on me.”

  38.   Retweeted

    A lot of thought-provoking posts this month from leading scholars in law, ethics, genetics. Get immersed in the issues before Friday’s conference!

  39.   Retweeted

    When employer “wellness programs” incentivize employees to use , consider what goes to , what to or , & what does employee have about any of this.

  40.   Retweeted

    Looking forward to joining this awesome line-up of speakers at ‘s conference & talking about ‘s, ‘s & my work. Thx to , & for organizing!

  41.   Retweeted

    It’s not every day that a serious conference on discusses Brad Pitt in a bath leaving behind sperm that later impregnates a woman and the legal challenges that emerge. Well done – you managed to get everyone’s attention 🙂

  42.   Retweeted

    Anguishing story told with elegance and grace. We are all utterly unprepared for generations of secrets unearthed by 26 million ++ kits sold to date.

  43.   Retweeted

    “Civilized societies are nearby, believe it or not!” explains how when is implemented in Canada, it means the government pays for it. (We are all v jealous about your developed country to the north, Vardit)

  44.   Retweeted

    Jonathan Kahn ⁦⁩ ⁦⁩ discusses the fall and rise of race in genetic medicine, its science and politics.

  45.   Retweeted

    Yes! And we should continue to strive to have racial and ethnic representation to ensure that genomic research and policy doesn’t continue to exacerbate racial disparities

  46.   Retweeted

    Fascinating discussions today at the conference

  47.   Retweeted

    Potential consequences are greater when editing germline compared with somatic cells, because its modification can allow for the generational transmission of altered genes. laying out priciplist bioethical concerns of

  48.   Retweeted

    Health information should not be treated as property to protect individuals, says . Instead, we should continue to enhance existing regulatory and liability rules to safeguard individual privacy and data security.

  49.   Retweeted

    There has been a relunctance by courts to recognize information as property, but that could change drastically when it comes to genetic data.

  50.   Retweeted

    Sir Wm. Blackstone is always a hit on the big screen — from my talk today on why health data isn’t property .

  51.   Retweeted

    FDA involvement with DTC tests hasn’t shut them down. Five have been approved, and FDA has been flexible in its approval pathway (4 de novo, 1 510(k)). – Catherine Sharkey @

  52.   Retweeted

    Emily Qian of is a genetic counselor and is co-author on one of the blog posts in our symposium:

  53.   Retweeted

    At the Ethics Conference on Consuming Genomics. There was a question about why patients decline participating in precision medicine research. Check out our paper on why patients decline genomic sequencing

  54.   Retweeted

    Great turnout at DTC genomics conference today. Tour de force discussion of the issues facing the personal genomics industry and consumers today.

  55.   Retweeted

    “Informed consent is a process” that should include: test’s purpose, possible results of the test, test’s limitations/consequences, confidentiality/privacy, risks of testing and familial implications, and voluntary participation.

  56.   Retweeted

    The amazing ⁦⁩ closes out the conference by discussing the ethics of non-invasive prenatal testing (NIPT), it’s ethical challenges, and how whole genome NIPT may make “the fetus transparent.”

  57.   Retweeted

    .: what about DNA vigilantes who upload information to databases explicitly to help law enforcement? Natalie Ram: BAM I ALREADY WROTE THAT ARTICLE CHECK IT OUT. (forthcoming , mayyyybe here? )

  58.   Retweeted

    23andMe does a pretty good job situating and contextualizing results, but APOE testing may have little benefit

  59.   Retweeted

    Is ⁦⁩ ‘s test for APOE associated with Alzheimer’s different ethically speaking from its other tests? ⁦⁩ ⁦⁩ discuss ⁦

  60.   Retweeted

    Ultrasound technology made the uterus transparent, so parents could see their child before it was born. In the future, could make the fetus itself transparent, so parents can see the whole genome. Many associated ethical challenges, both pre- and post-birth

  61.   Retweeted

    Great talk by one of the authors at on the need for laws and regulations to protect the privacy rights of genetic testing consumers and assuage concerns about information

  62.   Retweeted

    Johnathan on The Fall and Rise of Race in Genomics: – not a thing (2000) – a stepping stone to true targeting (2005) – useful to classify subpopulations (2011) – under-representation of ethnically diverse subpopulations are necessary for good data (2019)

  63.   Retweeted

    When tests allow the breach of anonymity and privacy of relatives who don’t want to be known–including in cases of rape–what should we do? Answers aren’t easy. -Kif Augustine-Adams

  64.   Retweeted

    Listening to the brilliant discuss the concept of non-directiveness in genetic counseling.

  65.   Retweeted

    Grateful for the opportunity to participate in the Annual Conference – thanks Carmel Sachar & Cristine Hutchison-Jones for a great line-up & planning- learned a lot & left with many more ?s to consider

  66.   Retweeted

    & : “The more jurisdictions that adopt a cautionary approach to their own regulations for genome editing (particularly heritable genome editing) the more likely negative world-wide consequences can be mitigated.”

  67.   Retweeted

    There’s no prospect of potentially suing because of the disclaimers and forced arbitration put into agreements by the company ⁦

  68.   Retweeted

    explains the ways employer wellness programs is only a “theoretical win-win.” Minimal results come at the cost at privacy, and all of which can also show up in insurace realms as well. (Ex: Life insurers also implementing wellness policies)

  69.   Retweeted

    Although increasing access to predictive/actionable genetic tests could theoretically be beneficial, we should be cautious about using third-parties, like life insurers, to disseminate these tests to their consumers without greater regulatory protections.

  70.   Retweeted

    . has examined for years whether we should own our genetic info. Three reactions: Lay: yeah, duh Lawyers: no, duh (see Moore v Regents of U of Cal) Clinicians/researchers: Good God No! Disaster! (Not live-tweeting b/c draft here: )

  71.   Retweeted

    Property Conversion in Genetic Property Rights – who owns the rights? “Researchers need to be transparent and use adequate informed consent” – claims for generic conversion should not stifle research or create moral harms, suggests – at Wasserstein Hall

  72.   Retweeted

    We’re so proud of our friend and Academic Fellowship alum ! ✨🕺🏻

  73.   Retweeted

    Why is most insurance typically a state issue? FYI – Congress essentially “blessed” and preserved a state regulatory system of the insurance industry with passage of the McCarran-Ferguson Act of 1945. It makes it politically difficult to push this at federal level

  74.   Retweeted

    DTC genetic testing customers lack legal protections. Genetic conversations might offer them some rights… ?

  75.   Retweeted

    . takeaway: Wellness programs aren’t necessarily bad, but question is what data goes to consumers, what data to employers and insurers, and what can they do with it?

  76.   Retweeted

    . takeaway: w/r/t liability, companies are essentially immune because of disclaimers & arbitration clauses; doctors may be on the hook.

  77.   Retweeted

    Q by : What do we tell GCs/trainees when we get a DTC result that needs to be confirmed but insurance won’t pay for confirmation? Answer: not very clear, but might be liable if we do nothing. Yikes!

  78.   Retweeted

    Major disconnect with the ideas of ways to convert health data into what we have traditionally considered property-like rights.

  79.   Retweeted

    Great point from about how to treat “control group” genetic data, from those without the indicative genetic information, in arguments for genetic ownership/remuneration arguments.

  80.   Retweeted

    The story of a mom who contacts her (donor conceived) five-year-old’s grandmother — then gets threatened by a sperm bank

  81.   Retweeted

    The ethical debate about anonymity is MOOT. There is no anonymity for sperm donors, nor are there any federal laws regarding anonymity of sperm donors. (Some states address medical information/disclosure but not anonymity)

  82.   Retweeted

    Three observations: 1. Biomedical data/samples are governed by method of procurement 2. Contributors care about use 3. Specimens/data procured differently end up being used similarly (lots of mixing between academia & industry). ==>TENSION. – @

  83.   Retweeted

    Rights to privacy or publicity – What will the courts decide? Well, it’s unclear because there are gaps in the existing laws. Liza Vertinsky also looking at the underlying implications of the choices of legal pathways

  84.   Retweeted

    . is an active moderator! Asking excellent questions (including mine–how do we react to patients not ‘getting’ consent info?, and then ‘s on right not to be a genetic parent! Need to think on your feet w/ Nita around!)

  85.   Retweeted

  86.   Retweeted

    Wondering how panelists and fellow attendees feel about this lack of anonymity? and individuals conceived from egg or who want to know about their background never consented to anonymity of donors

  87.   Retweeted

    Yeah that looks simple! Barbara Evans on what the regulatory pathway issupposed to look like and what makes it challenging in the world of genetics using charts from 2017 reports. And an ode to the “pink golden retriever” we all want

  88.   Retweeted

    You’re welcome!

  89.   Retweeted

    Barbara Evans: Peer-review is no longer the threshold for good science it once was – grant review is. But if research is not funded…those protections aren’t there

  90.   Retweeted

    How well are companies doing in complying with the privacy principles they themselves signed on to? James Hazel talks about the work he and Chris Slobogin ⁦⁩ ⁦⁩ have done. ⁦

  91.   Retweeted

    Excellent talk by Barbara Evans expressing skepticism about a top down regulatory approach on biohacking (“If I want to turn my skin bright green who’s the FDA to tell me I can’t?), citing Lisa Ikemoto’s excellent DIY Bio Hacking article

  92.   Retweeted

    Terrific representation of women at ! Speakers: 14F, 6M Moderators: 4F, 2M Nicely done, folks.

  93.   Retweeted

    Panel takeaways: * DTC privacy policies are all over the place, and Best practices are a good way forward. * FDA is poised to take an advanced role as a regulator in the field. * We must differentiate between germline and somatic editing for regulation

  94.   Retweeted

    Catherine Sharkey asks us to consider the FDA may play in managing the conceptual risk and regulatory model for DTC genetic testing especially given the complexities that AI, machine learning, and big data add to this industry

  95.   Retweeted

    You can hear a pin drop in the auditorium as Kif Augustine tells a very personal tale about how reveals a story of rape and a lost half sister. Secrets, lies, ancestry, DNA, and Mormon Orthodoxy in 1959 Utah.

  96.   Retweeted

    And what does diversity mean? What does it do? Among other things, drives $$$$ funding in the research cycle.

  97.   Retweeted

    Health equity is due to structural and systemic racism in the field present from its beginnings. Seeking more diversity in the workforce will not solve this “health equity” issue. As Jonathan Khan notes, these d&i initiatives can be used to elide responsibility

  98.   Retweeted

    Natalie Ram at talks about familial investigations for law enforcement. For a short, recent piece w/ & Amy McGuire: . Longer ago and longer (by far) in :

  99.   Retweeted

    Natalie Ram uses her baby bump as the ultimate scholarly “flex” in showing the involuntary and immutable nature of informational revelation for the children we produce. How do these elements make the forensic use of that information different?

  100.   Retweeted

    Ooh interesting! Natalie Ram argues that the involuntariness of familial info getting into databases means the Third Party Doctrine [which sucks anyway] shouldn’t apply. (here’s her piece, DNA by the Entirety: )

  101.   Retweeted

    providing a range of policy/legal choices about how to address new forms of noninvasive prenatal testing

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Reporter and Curator: Dr. Sudipta Saha, Ph.D.

 

RNA plays various roles in determining how the information in our genes drives cell behavior. One of its roles is to carry information encoded by our genes from the cell nucleus to the rest of the cell where it can be acted on by other cell components. Rresearchers have now defined how RNA also participates in transmitting information outside cells, known as extracellular RNA or exRNA. This new role of RNA in cell-to-cell communication has led to new discoveries of potential disease biomarkers and therapeutic targets. Cells using RNA to talk to each other is a significant shift in the general thought process about RNA biology.

 

Researchers explored basic exRNA biology, including how exRNA molecules and their transport packages (or carriers) were made, how they were expelled by producer cells and taken up by target cells, and what the exRNA molecules did when they got to their destination. They encountered surprising complexity both in the types of carriers that transport exRNA molecules between cells and in the different types of exRNA molecules associated with the carriers. The researchers had to be exceptionally creative in developing molecular and data-centric tools to begin making sense of the complexity, and found that the type of carrier affected how exRNA messages were sent and received.

 

As couriers of information between cells, exRNA molecules and their carriers give researchers an opportunity to intercept exRNA messages to see if they are associated with disease. If scientists could change or engineer designer exRNA messages, it may be a new way to treat disease. The researchers identified potential exRNA biomarkers for nearly 30 diseases including cardiovascular disease, diseases of the brain and central nervous system, pregnancy complications, glaucoma, diabetes, autoimmune diseases and multiple types of cancer.

 

As for example some researchers found that exRNA in urine showed promise as a biomarker of muscular dystrophy where current studies rely on markers obtained through painful muscle biopsies. Some other researchers laid the groundwork for exRNA as therapeutics with preliminary studies demonstrating how researchers might load exRNA molecules into suitable carriers and target carriers to intended recipient cells, and determining whether engineered carriers could have adverse side effects. Scientists engineered carriers with designer RNA messages to target lab-grown breast cancer cells displaying a certain protein on their surface. In an animal model of breast cancer with the cell surface protein, the researchers showed a reduction in tumor growth after engineered carriers deposited their RNA cargo.

 

Other than the above research work the scientists also created a catalog of exRNA molecules found in human biofluids like plasma, saliva and urine. They analyzed over 50,000 samples from over 2000 donors, generating exRNA profiles for 13 biofluids. This included over 1000 exRNA profiles from healthy volunteers. The researchers found that exRNA profiles varied greatly among healthy individuals depending on characteristics like age and environmental factors like exercise. This means that exRNA profiles can give important and detailed information about health and disease, but careful comparisons need to be made with exRNA data generated from people with similar characteristics.

 

Next the researchers will develop tools to efficiently and reproducibly isolate, identify and analyze different carrier types and their exRNA cargos and allow analysis of one carrier and its cargo at a time. These tools will be shared with the research community to fill gaps in knowledge generated till now and to continue to move this field forward.

 

References:

 

https://www.nih.gov/news-events/news-releases/scientists-explore-new-roles-rna

 

https://www.cell.com/consortium/exRNA

 

https://www.sciencedaily.com/releases/2016/06/160606120230.htm

 

https://www.pasteur.fr/en/multiple-roles-rnas

 

https://www.nature.com/scitable/topicpage/rna-functions-352

 

https://www.umassmed.edu/rti/biology/role-of-rna-in-biology/

 

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LIVE – Translating Genetics into Medicine, April 25, 2019, 8:30 AM – 6:00 PM, The New York Academy of Sciences, 7 World Trade Center, 250 Greenwich St Fl 40, New York

Real Time Press Coverage: Aviva Lev-Ari, PhD, RN

Aviva Lev-Ari, PhD, RN

Director & Founder

https://lnkd.in/eEyn69r

Leaders in Pharmaceutical Business Intelligence (LPBI) Group, Boston

Editor-in-Chief

http://pharmaceuticalintelligence.com 

e-Mail: avivalev-ari@alum.berkeley.edu

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Translating Genetics into Medicine

Thursday, April 25, 2019, 8:30 AM – 6:00 PM

The New York Academy of Sciences, 7 World Trade Center, 250 Greenwich St Fl 40, New York

 

Presented By

The Biochemical Pharmacology Discussion Group



The first genome-wide association studies (GWASs) began unraveling the genetic basis of complex diseases over a decade ago. In that time, the development of innovative analytical and experimental methods enabled genomic data to inform how genetics relates to human traits, health, and disease. Nevertheless, progress has stalled in translating genetic association signals to an understanding of their underlying biological mechanisms, in identifying causal links between genetic variants and phenotypes, and in developing therapies based on this knowledge — few drug targets identified through GWASs have advanced.

This symposium will highlight emerging strategies to experimentally and computationally identify and validate causal association from patient cohorts, and outline the challenges and opportunities in translating GWAS hits into successful drug discovery programs.

Key Speakers
  • Richard P. Lifton, MD, PhD

The Rockefeller University

  • Robert Plenge, MD, PhD
Celgene
SOURCE

Translating Genetics into Medicine

Thursday, April 25, 2019

Keynote Speakers
Richard P. Lifton, MD, PhD
The Rockefeller University
“From Genes and Genomes to Targets and Therapies”Robert Plenge, MD, PhD
Celgene
“Making Medicines in the Future: Humans as a Model Organism”
REGISTER
This symposium will highlight emerging strategies to experimentally and computationally identify and validate genetic associations, explore the biological mechanisms of genetic variants and their link to phenotypes, and outline the challenges and opportunities in translating genome-wide association study (GWAS) hits into successful drug discovery programs.
For the full list of speakers and meeting agenda, please visit nyas.org/genmed2019
REGISTER TODAY

Program Support

Biochemical Pharmacology Lead Supporters
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Regeneron logo
Biochemical Pharmacology Supporter
Boehringer Ingelheim logo
Biochemical Pharmacology Member
https://mailchi.mp/nyas/genmed_2019_04_04?e=2d875d53e9

Agenda

https://event.crowdcompass.com/genmed2019/activities

#GenMed2019

Thu, April 25th, 8:30 AM – 9:00 AM

Continental Breakfast and Registration

Translating Genetics into Medicine

 

Thu, April 25th, 9:00 AM – 9:15 AM

Introduction and Welcome Remarks

Translating Genetics into Medicine

 

Thu, April 25th, 9:15 AM – 9:45 AM

Precision Medicine in Obesity — The Value of Genetic Information

Session 1: Linking Disease to Genetic Variation

Translating Genetics into Medicine

Description

With a growing understanding of the genetic basis of diseases, the expectation is that genetics will soon revolutionize health care. Knowing a patient’s genome would enable us to predict risk of future disease more accurately and to prescribe personalized treatment strategies, as opposed to the traditional “one-size-fits-all” approach.Online genomic companies offer genetic testing directly-to-consumers (DTC), many of which focus on diet, nutrition, physical performance, and fitness. They claim that, based on their customer’s genotype data, they can they can design “genetically matched-diets” to help them lose weight more easily, determine what nutrients their body favors during exercise, what type of training is most effective, among others. Besides personalizing recommendations to live healthier lives, genetics is also being used to predict future risk of disease, such as obesity, using polygenic risk scores (PRSs). PRSs assess an individual’s overall genetic risk based on the cumulative effect of many common genetic variants. Some claim that a PRS can identify people-at-risk early in life, allowing prevention to start at a young age.I will discuss the scientific evidence currently available that supports (or not) personalizing lifestyle recommendations and predicting obesity based on genetic information. I will also briefly review the potential implications of inaccurate “genotype-driven” recommendations. For now, it seems that genotype-based recommendations are likely as effective as the “one-size-fits-all” recommendations and that current PRS prediction of obesity is outperformed by family history.

Speakers

  • Ruth Loos, PhD

    Icahn School of Medicine at Mount Sinai

    Presenter

  • mutations LEP Leptin agonist for Leptin deficiency Mutations on POMC, LEPReceptor MC4R agonists
  • Common obesity vs LEP deficiency,
  • Genetics in early age
  • Health weight Screening on exosome, genome transcriptome,
  • treatment based on genetic profile c
  •  – response vs Direct-to-consumer: bold adviceompanies use data from 23 and me and offer protpcols for health weight
  • Saturated Fat diet  – Framingham Offspring = show predicted data
  • longitudinal group not affected by high saturated died
  • no actual dat ahigh fat dairy high interactionAPOA2, APOA2CC
  • avoid fast food limiting meat
  • Score did not capture extreme obese, score is not predictive
  • 10% on top risk not predicts
  • Will knowing GENETIC Profile change behaviour??
  • Survey 23 diseases – 3600 participants
  • Odesity life risk and genetics — all other factors are critical
  • MCAR – Appetite suppression in the brain — suppresses appetite, satiety
  • Risk Score is like a flip coin

 

 

Thu, April 25th, 9:45 AM – 10:15 AM

Title to be announced

Session 1: Linking Disease to Genetic Variation

Translating Genetics into Medicine

Speakers

  • Christopher Brown, PhD

    University of Pennsylvania

  • GTEx: Geno Type DeneExpression
  • every gene has genetics variations in expression regulatory
  • Any random SNP is an eQTL – most of these tags
  • Concept of co-localization: Chromosome position phenotyoe 1 & 2 No association to Association
  • GTEx explains 52% of GWAS hits Nearest gene, Not nearest Gene No co-localization
  • Disease genes enriched for tissue specific eQTLs: Tissue specific eGene vs Tissue shared eGene
  • Epigenomic fine-mapping: GWAS locus
  • Study design: BioBank Liver biopsies for bio-genomics profiling
  • MOST EXPRESSED GENES INTERACT WITH DISTAL OVER DISTANCE THAN PREDICTED BY NEAREST
  • tissue specific of cis-eQTLs: Liver specific vs shared: associated with enhancer overlap
  • hQTL discovery – are enriched for liver LT alpha
  • identify co-regulated histone marks and genes’ An Example: Chromosome 18 position common loci
  • new Biology; KPLB1 – FADS1/2/3
  • FTO: Chromosome 16
  • Novel candidate have distinct properties: proxemity searches not significant vs research #Brown Lab, Penn, GTEx,
  • Transcriptomes of 5000 liver biopsy tissues
  • DIseased Liver tissue

 

Presenter

 

Thu, April 25th, 10:15 AM – 10:45 AM

Identifying Gene Regulatory Mechanisms of Disease

Session 1: Linking Disease to Genetic Variation

Translating Genetics into Medicine

Description

Genetic variation that alters gene regulation contributes to many and diverse human diseases. In particular, there is strong evidence that nearly all common human traits and diseases are influenced to some degree by non-coding genetic variation that acts via changes in gene regulation. Even for rare diseases, there is evidence that regulatory variation can influence the severity of diseases. Nonetheless, there persist major technological challenges in our ability to empirically or computationally identify specific regulatory mechanisms contributing to those diseases. Overcoming those obstacles will greatly benefit human health by revealing new opportunities for disease diagnosis and treatment.I will discuss recent progress in this area, focusing predominantly on the development and use of new high-throughput genome-scale technologies to quantify the effects of non-coding genetic variation on human gene regulatory element activity and the regulation of downstream target genes. I will also discuss recent progress and specific case studies that highlight the use of those techniques to map causal regulatory mechanisms of various human traits and diseases. Finally, I will discuss future directions in those techniques, with an eye towards making the identification of non-coding mechanism of human disease routine.

Speakers

  • Timothy E. Reddy, PhD

    Duke University

    Presenter

  • Genotype and phynotype
  • enhancers dCas9-P300 reveals HKDC1 is the target gene – is a 5th human kinases
  • gRNA hexokinases: HK1,HK2, HK3 – gloucose in Blood,
  • HK4 (Glucokinase – diabetesis
  • Mice in pregnancy – heperglycemia
  • New hypothesis  –  hyperglycemia during pregnancy:3q25 adipose
  • STARR-seq reporter assays: GFP
  • MASSIVELY PARALLEL REPORTER ASSAY FROM PATIENT’S DNA – PCR-BASED
  • CHROMOSOME 3 POSITION: TRANSVERSION POP-STARR
  • rere alleles have greater and typically deleterious effects
  • Scaling up POP-STARR to entire GWAS loci
  • HepG2 cells: Coverage of target regionsL DIfferences in regulatory activity in pregnancy hyper glacenia
  • epigenome editing screens on HER2
  • CRISPR mapped to target genes: HKDC1 – gene not looked at before
  • expance and scale opportunity exists
  • Cell Type Model

 

10:45 – 11:15 – Coffee Break

 

Thu, April 25th, 11:15 AM – 11:20 AM

Genomic Screening and Personalized Medicine in a Highly Diverse Biobank in New York City

Session 2: Data Blitz Presentations

Translating Genetics into Medicine

Speakers

  • Noura Abul-Husn, MD, PhD

    Icahn School of Medicine at Mount Sinai

    Presenter

  • phenotypic complexity + de novo loss of function mutations
  • Chromatin remodeler mutation can lead to prevention of surgery is treated
  • Neuronal migration defect
  • cutaneous disorder caused by somatic mutationsMutations in KRAS, Ichthyosis with confetti
  • Deviations from Mendelian models: Variable expressivity, Incomplete penetrance
  • CVD: loss of function mutation FLT4 – Tetralogy of Fallot heterozygous mutation
  • Pulmonary fibrosis – short telemere – inhalation if MUTATION + Environment – disease will occur
  • Congenital Heart Disease + Autism – gene loss function mutation vs de Novo mutation
  • Non-syndromic midline craniosynostosis – SMAD6 mutations: common variant near BMP2 and SMAD6 for OSTEOBLAST differentiation – to cause Non-syndromic midline cranio-synostosis
  • Coming revolution in therapeutics: Rare diseasese and common diseases

20,000 genes – known and studies are 5,000

Thu, April 25th, 11:20 AM – 11:25 AM

Immune Disease Variants Modulate Gene expression in CD4+ Regulatory T Cells and Inform New Drug Targets

Session 2: Data Blitz Presentations

Translating Genetics into Medicine

Speakers

  • Dafni Glinos, PhD

    New York Genome Center

    Presenter

Thu, April 25th, 11:25 AM – 11:30 AM

Age, Sex, and Genetic Polymorphisms Influence the Inherent Patterns of Infiltrating Immune Cells

Session 2: Data Blitz Presentations

Translating Genetics into Medicine

Speakers

  • Andrew Marderstein

    Weill Cornell Medicine

    Presenter

Thu, April 25th, 11:30 AM – 12:15 PM

Keynote Address ~ From Genes and Genomes to Targets and Therapies

Session 3: Keynote Address

Translating Genetics into Medicine

Speakers

  • Richard P. Lifton, MD, PhD

    The Rockefeller University

    Presenter

Thu, April 25th, 12:15 PM – 1:15 PM

Networking Lunch and Poster Session

Translating Genetics into Medicine

 

Thu, April 25th, 1:15 PM – 1:45 PM

Human Genetics to Identify Vascular Causes of Coronary Artery Disease and Myocardial Infarction: From Discovery to Function

Session 4: Characterizing Functional Relevance of Genetic Variants

Translating Genetics into Medicine

 

Description

Coronary artery disease and myocardial infarction remain the leading causes of death in the United States and throughout the world. New treatments will require a better understanding of the casual pathways in the cells of the blood vessel wall, where the atherosclerotic plaque is formed. The genetic loci identified through genome-wide association studies (GWAS) represent new therapeutic targets, but only a small number have been functionally characterized. The majority of these risk loci are not associated with plasma lipid levels, suggesting they can identify novel vascular mechanisms of disease.We have prioritized the functional analysis of GWAS loci associated with multiple vascular diseases. One such locus is the 6p24 region, which is associated with five vascular diseases including coronary artery disease, migraine headache, cervical artery dissection, fibromuscular dysplasia and hypertension. Through genetic fine mapping, we prioritized rs9349379, a common SNP in the third intron of the PHACTR1 gene, as the putative causal variant. Epigenomic data from human tissue revealed an enhancer signature at rs9349379 exclusively in aorta, suggesting a regulatory function for this SNP in the vasculature. CRISPR-edited stem cell-derived endothelial cells demonstrate rs9349379 regulates expression of endothelin 1 (EDN1), a gene located 600 kb upstream of the associated SNP. The known physiologic effects of EDN1 on the vasculature may explain the pattern of risk for the five associated diseases. Overall, these data illustrate the integration of genetic, phenotypic, and epigenetic analysis to identify the biologic mechanism by which a common, non-coding variant can distally regulate a gene and contribute to the pathogenesis of multiple vascular diseases.

Speakers

  • Rajat Gupta, MD

    Broad Institute, Massachusetts General Hospital, and Harvard Medical School

    Presenter

  • Lipid-related therapies vs Non-lipid Therapeutics
  • successful clinical Trials;
  • IL- 3B Inhibitor by Novatris
  • Endothelin-1 is a vasoconsrtictive peptide secteated by endothelial cells
  • Higher ET-1 secretion Genome editing 1bp change at SNP was technically difficult
  • 2-step Cas9 editing at rs9349379
  • EDN1 vs 6p24 locus, downstream doe ET1
  • higher circulating endothelin-1 in participants with risk genotype
  • Vascular biology ET-1 protein,
  • ET-A – brain
  • ET-B – kidney
  • EDNRA – ET-1 Increase CAD/MI decrease HTN – veaodiletion
  • distal genes
  • human genetcs variants with pleiotropic effects that the on-target effects predict consequences of other disease

Thu, April 25th, 1:45 PM – 2:15 PM

New Tools for High-throughput Functional Characterization of the Human Noncoding Genome

Session 4: Characterizing Functional Relevance of Genetic Variants

Translating Genetics into Medicine

Description

CRISPR/Cas9 has driven forward the validation of candidate regulatory elements by enabling high-throughput endogenous perturbation of the human noncoding genome. These advances have been enabled by Cas9’s suitability for use in pooled approaches to perturb and phenotype thousands of candidate regulatory elements in a single experiment. In my talk, I will cover two advances for pooled CRISPR/Cas9 screens of the noncoding genome. First, I’ll describe a method we devised to scan thousands of kilobase-sized deletions (“ScanDel”) across a desired region, programming one unique deletion per cell in a pool and phenotyping them in multiplex by pooled functional selection. In our proof-of-concept study, we used ScanDel to program 4,342 overlapping 1-and 2- kilobase (Kb) deletions that covered 206 Kb centered on HPRT1, the gene underlying Lesch-Nyhan syndrome. However, ScanDel and its contemporaries are limited to evaluating regulatory elements for their effect upon a single gene. To overcome this, we designed and implemented a second method in which large numbers of CRISPR perturbations are introduced to each cell, followed by single-cell RNA-seq to read out their effect upon any transcript. We designed CRISPR perturbations to 5,920 candidate regulatory elements in the K562 cell line, and tested for differential expression of all expressed genes within 1 megabase of each candidate enhancer. We thus effectively evaluated >70,000 potential enhancer-target gene relationships in one experiment, and associated 664 enhancer-gene pairs. Pooled perturbation methods of this scale are poised to facilitate the comprehensive elucidation of the gene-regulatory landscape of the human genome.Coauthors: Andrew J. Hill, Greg Findlay, José L. McFaline-Figueroa, Melissa D. Zhang, Anh Leith, Cole Trapnell, and Jay Shendure, University of Washingon; Nadav Ahituv, University of California San Francisco.

Speakers

  • Molly Gasperini

    University of Washington

    Presenter

  • study single gene at a timemonogenic screens can only
  • location of enhancers eQTL mapping is a masssive parallel methods to test all variants –
  • GWAS “synthetic variation” insert randomly CRISPR candidate enhancer vs target gene
  • CRISPRi – for Epigenetics monoclonal lines
  • crisprQTL mapping: Assay formarly known
  • Multiplex enhancer-gene pair screen
  • Leukhemia cell line K562: Open chromatin, RNA POL II
  • Lentivirus –  high multiplicity equ 5.8 million cells
  • detected 664 enhancer-gene pairs eMNU – enhancers gene pairs
  • distance between enhancers and thier target genes
  • monogenic pooled deletion scan vs multiplexing whole transcriptome enhancer-gene pair screen

 

 

 

Thu, April 25th, 2:15 PM – 2:45 PM

From Functional Genomics to Translational Therapeutics for Cardiometabolic Disease

Session 4: Characterizing Functional Relevance of Genetic Variants

Translating Genetics into Medicine

 

Description

The application of genome-wide approaches to the study of cardiometabolic disease and its risk factors is having a major impact on our understanding of this complex disease and our ability to prevent and treat it. Genome-wide common and rare variant studies and subsequent functional genomics approaches have provided important new insights into the biological pathways involved in lipoprotein metabolism, diabetes, fatty liver disease, atherogenesis, and cardiomyopathy. When these genomic data are coupled to human phenomic science, the potential for new information related to human health and disease is immense. The application of Mendelian randomization is allowing important inferences with regard to the causality of new cardiometabolic risk factors.The intense focus on human genetics is leading to the identification of new therapeutic targets. Functional genomics studies based on these new targets is helping to understand disease pathogenesis and pointing to more precise approaches to therapies. Wider application of genetic testing in the clinical arena is likely to lead to greatly improved risk stratification and personalization of preventive and treatment paradigms. The field of cardiometabolic disease has been at the forefront of translating genetics into medicines.

Speakers

  • Daniel J. Rader, MD

    Perelman School of Medicine, University of Pennsylvania

    Presenter

Thu, April 25th, 2:45 PM – 3:15 PM

Networking Coffee Break

Translating Genetics into Medicine

  • gene burden LMNA Cardiomyopaty – LOF 
  • REVEL – 40 carriers of deleterious variants with heart failure
  • Exome-wide LOF gene burden
  • Common variANT – TRIB1 VARIANTS: ADIPOKINES, LIVER FAT AND ENZYME, CAD, TG – LDL-C HDL-C
  • SLC39A8 GENOMIC LOCUS IS ASSOCIATES – A METAL MAGNESENE-DEPENDENT ENZYME – schesophrenia – magnesene related

 

Thu, April 25th, 3:15 PM – 3:45 PM

Fueling a Genetics-driven R&D Organization

Session 5: Emerging Opportunities in Genetics for New Therapeutics

Translating Genetics into Medicine

 

Description

Discovering and developing new medicines that are safe and more highly effective than existing therapies is an increasingly challenging and expensive endeavor. Over the past decade, human genetics has given us new insights into the biology of disease and clues into how to approach the discovery of new drugs that are more likely to be successful. The challenge for would-be drug discoverers is to gain access to powerful sources of genetic associations, understand their impacts on health and disease, disentangle the underlying causal mechanisms, and amongst the many options, choose the proteins that will provide the best drug targets.

Speakers

  • Matthew Nelson, PhD, MA

    GlaxoSmithKline

    Presenter

  • 2013 – 2014 – case studies at GSK disease via genomics using the Human as the organizm for drug development since Human genome is only human’s.
  • Genetics support between indication and therapeutics
  • UK Biobank – subject-based genetic data
  1. diversity of phenotypes
  2. exome seqencing – 2021 Regeneron + 5 big Pharma – collaboration
  3. GWAS analysis of osteoarthritis in iBiobank – 64loci
  4. GWAS and asthma – onset child or adult
  5. PheWAS vs GWAS – 500,000 individuals
  6. PheWAS – IL33 LOoF – SNVs proxies for target pertubation

Thu, April 25th, 3:45 PM – 4:30 PM

Keynote Address ~ Making Medicines in the Future: Humans as Model Organism

Session 5: Emerging Opportunities in Genetics for New Therapeutics

Translating Genetics into Medicine

Description

Human genetics offers the potential to transform drug discovery. However, the path from a human genetic discovery to a new medicine remains challenging. An “allelic series” model is a concept that offers one solution to utilize human genetics for decision-making along the drug discovery journey. There are several compelling examples in immunology that fit with the allelic series concept, including TYK2 and IL2RA. Extrapolating from these and other examples, it is conceivable to build a genetic dose-response portal in the near future.

Speakers

  • Robert Plenge, MD, PhD

    Celgene

    Presenter

50%-80% TYK2 effective without infection risk increase or JAK1,2,3 activation

  • IKZF1 – Common variants associated with SLE, T1D, IBD, allergy, B-cell ALL, blood cell counts and more
  • Rare variants associate with
  • Common variant GSAW Lead SLE SNP
  • Rare LoF mutations associated with immune deficiency: Low Ig, Pleiotropic effect of other common allele
  • matching modality to mechanism
  • HOW to build a genetic dose-response portal

 

 

 

Thu, April 25th, 4:30 PM – 5:00 PM

Panel Discussion: The Future of Transformational Genetics

Session 5: Emerging Opportunities in Genetics for New Therapeutics

Translating Genetics into Medicine

Speakers

  • Christopher Brown, PhD

    University of Pennsylvania

    Presenter

  • Ruth Loos, PhD

    Icahn School of Medicine at Mount Sinai

    Presenter

  • Matthew Nelson, PhD, MA

    GlaxoSmithKline

    Presenter

  • Robert Plenge, MD, PhD

    Celgene

    Presenter

  • gene function LoF GoF
  • Pick a human phenotype for
  • drug efficacy – Human Phenotype
  • effect of multiple phenotype as proxy for ADEs on efficacy and toxicity
  • New target for drug screens

Immunotherapy Example

  • Allelic series model TYK2
  • common protein reduce TYK2 – IL23A IL12B signaling and psoriasis
  • TYK2 – Typw 1 Biabetis RA
  • Variants: Autoimmunity: If knock out risk of Infection
  • InfectionsP1104A; protective from multiple autoimmune disease
  • I684S ANAOTHE
  • PARTIAL JAK 1,2,3,

 

Thu, April 25th, 5:00 PM – 6:00 PM

Networking Reception and Poster Session

Translating Genetics into Medicine

 

Thu, April 25th, 6:15 PM – 6:15 PM

Adjourn

Translating Genetics into Medicine

 

Posters

Please see attached pdf below to view the poster abstracts.

1.  Noura Abul-Husn, MD, PhD, Icahn School of Medicine at Mount Sinai, Genomic Screening and Personalized Medicine in a Highly Diverse Biobank in New York City

  1. Margot Brandt, New York Genome Center, Validation of cis-Regulatory Transcript Variants Using Fine-mapping and CRISPR/Cas9 Genome Editing
  2. Olof S. Dallner, PhD,The Rockefeller University, Dysregulation of a long noncoding RNA by Genetic Variants Reduces Leptin Leading to a Leptin Responsive Form of Obesity
  3. Dafni Glinos, PhD, New York Genome Center, Immune Disease Variants Modulate Gene expression in CD4+ Regulatory T Cells and Inform New Drug Targets
  4. Scott MacDonnell, PhD, Regeneron Pharmaceuticals, Using iPS Derived Cardiomyocytes to Identify Casual Links Between Genetic Variants and Phenotypes – Case Study Using MYH7 R403Q as a Model of Hypertrophic Cardiomyopathy
  5. Andrew Marderstein, BS, Weill Cornell Medicine, Age, Sex, and Genetic Polymorphisms Influence the Inherent Patterns of Infiltrating Immune Cells
  6. Christian Stolte, New York Genome Center, Turning WGS Genetic Testing into a Dialogue Between Physicians and Labs with GenomeDiver
  7. Archana Tare, MS, Albert Einstein College of Medicine, Integrated Analysis of Deep Sequencing and Functional Genomics Identifies SMAD3 as a Therapeutic Target for Longevity and Healthy Aging in Humans
  8. Fang Wang, Temple University School of Pharmacy, Using Integrative Bioinformatics Analysis to Reveal Novel Drug Repurposing Targets for COPD
  9. Junke Wang, MS, The Ohio State University, Genome Wide Association Analyses Identify Pleiotropic Variants Associated with Acute Myeloid Leukemia (AML) and Myelodysplastic Syndrome (MDS) Susceptibility

Documents

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From Technicall.y Philly.com

Reporter: Stephen J. Williams, PhD

Spark Therapeutics’ $4.8B deal confirmed as biggest-ever VC-backed exit in Philly

Quick update on this week’s news: The University City life sciences company’s acquisition by Swiss pharma giant Roche is the biggest acquisition ever of a VC-backed company within city limits, per PitchBook and PACT.

The eye-popping $4.8 billion sticker price on Spark Therapeutics’acquisition deal with Roche announced on Monday is shaping up to be the largest exit ever within city limits for a venture-backed company, according to data from financial data provider PitchBook and the Philadelphia Alliance for Capital and Technologies (PACT).

“Filtering down to just Philadelphia proper does reveal that Spark Therapeutics, once the deal closes, will be the biggest exit ever for Philly-based venture-backed exits,” the company said in an email, citing data from an upcoming report.

According to the Seattle-based company’s data, the current holder of the largest Philly-proper exit title goes to Avid Radiopharmaceuticals, which in 2010 announced its acquisition by Lilly in a deal valued at up to $800 million.

Founded in 2013, Spark is a publicly traded spinout of Children’s Hospital of Philadelphia (CHOP), which invested $33 million in the company. The Philadelphia Inquirer reports that CHOP stands to reap a total return of $430 million for its minority stake in Spark Therapeutics.

As part of the acquisition deal, the company will remain based out of 3711 Market St., and continue to do business as a standalone Roche company.

“This transaction demonstrates the enormous value that global biotech companies like Roche see in gene therapy, a field in which Philadelphia is the unquestioned leader,” said Saul Behar, senior VP of  advancement and strategic initiatives at the University City Science Center, the West Philly research park where Spark began and grew its operations. “[This] further validates Greater Philadelphia’s status as a biotech hub with a very bright future.”

Spark CEO Jeff Marrazzo said the deep pool of resources from Roche, the company plans to “accelerate the development of more gene therapies for more patients for more diseases and further expedite our vision of a world where no life is limited by genetic disease.”

Other articles on Gene Therapy and Retinal Disease on this Open Access Online Journal include:

Women Leaders in Cell and Gene Therapy

AGTC (AGTC) , An adenoviral gene therapy startup, expands in Florida with help from $1 billion deal with Biogen

Artificial Vision: Cornell and Stanford Researchers crack Retinal Code

D-Eye: a smartphone-based retinal imaging system

 

 

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Individuals without angiographic CAD but with hiPRS remain at significantly elevated risk of mortality after cardiac catheterization

Reporter: Aviva Lev-Ari, PhD, RN

 

A genome-wide Polygenic risk scores (PRS) improves risk stratification when added to traditional risk factors and coronary angiography. Individuals without angiographic CAD but with hiPRS remain at significantly elevated risk of mortality.

 

Background:

Coronary artery disease (CAD) is influenced by genetic variation and traditional risk factors. Polygenic risk scores (PRS), which can be ascertained before the development of traditional risk factors, have been shown to identify individuals at elevated risk of CAD. Here, we demonstrate that a genome-wide PRS for CAD predicts all-cause mortality after accounting for not only traditional cardiovascular risk factors but also angiographic CAD itself.

Methods:

Individuals who underwent coronary angiography and were enrolled in an institutional biobank were included; those with prior myocardial infarction or heart transplant were excluded. Using a pruning-and-thresholding approach, a genome-wide PRS comprised of 139 239 variants was calculated for 1503 participants who underwent coronary angiography and genotyping. Individuals were categorized into high PRS (hiPRS) and low-PRS control groups using the maximally selected rank statistic. Stratified analysis based on angiographic findings was also performed. The primary outcome was all-cause mortality following the index coronary angiogram.

Results:

Individuals with hiPRS were younger than controls (66 years versus 69 years; P=2.1×10-5) but did not differ by sex, body mass index, or traditional risk-factor profiles. Individuals with hiPRS were at significantly increased risk of all-cause mortality after cardiac catheterization, adjusting for traditional risk factors and angiographic extent of CAD (hazard ratio, 1.6; 95% CI, 1.2–2.2; P=0.004). The strongest increase in risk of all-cause mortality conferred by hiPRS was seen among individuals without angiographic CAD (hazard ratio, 2.4; 95% CI, 1.1–5.5; P=0.04). In the overall cohort, adding hiPRS to traditional risk assessment improved prediction of 5-year all-cause mortality (area under the receiver-operating curve 0.70; 95% CI, 0.66–0.75 versus 0.66; 95% CI, 0.61–0.70; P=0.001).

Conclusions:

A genome-wide PRS improves risk stratification when added to traditional risk factors and coronary angiography. Individuals without angiographic CAD but with hiPRS remain at significantly elevated risk of mortality.

Footnotes

https://www.ahajournals.org/journal/circgen

*A list of all Regeneron Genetics Center members is given in the Data Supplement.

Guest Editor for this article was Christopher Semsarian, MBBS, PhD, MPH.

The Data Supplement is available at https://www.ahajournals.org/doi/suppl/10.1161/CIRCGEN.118.002352.

Scott M. Damrauer, MD, Department of Surgery, Hospital of the University of Pennsylvania, 3400 Spruce St, Silverstein 4, Philadelphia, PA 19104. Email 
SOURCE

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