The hype, the hope, and the reality of genomic medicine

Wendy K. Chung, MD, PhD Kennedy Family Professor of Pediatrics and Medicine Columbia University Disclosures

• Scientific advisor board of Regeneron Genetics Center • Research funding provided by Biogen

1994 “We always overestimate the change that will occur in the next two years and underestimate the change that will occur in the next ten.”

Bill Gates Genomic Testing Clinical Scenarios

• Diagnose symptomatic • Predict risk individuals • Identify pre-symptomatic • Prenatal & Postnatal Diseases individuals • Cancer (germline and • Pharmacogenetics somatic) • Screening • Cardiac conditions • Carrier Screening • Neurodevelopmental disorders/ • Prenatal Screening • Visual impairment • Newborn Screening Value of a Genetic Diagnosis

VALUE OF GENETIC TESTS THAT:

Confirm Inform Inform Inform disease suspected or prognosis reproductive management established Support from decisions and and prevention diagnosis other families life planning

Lerner et al, Genetic Medicine 2016 CLINICAL ACTIONABILITY: Why accurate predictions matter •Tailor health maintenance and prioritize health threats in real time •Increase alertness/monitoring to maintain health •Prevent disease, ideally using real time data •Provide reassurance or decreases ambiguity •Assist with life planning •Assist with family planning Reduced Sequencing Costs Enables Genomic Medicine Sensitivity of NIPS and First Trimester Serum Screening 100% 90% 80% 70% 60% 50% Serum FTS 40% NIPT 30% 20% 10% 0% Trisomy 21 Trisomy 18 Trisomy 13 NIPS Positive Predictive Value 120%

100%

80%

60%

40%

20%

0% 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 Trisomy 13 - NIPT Trisomy 13 - Serum FTS Trisomy 18 - NIPT Trisomy 18 - Serum FTS Trisomy 21 - NIPT Trisomy 21 - Serum FTS Prenatal Diagnosis Enables Treatment Fetus at 28 weeks gestation • Hydropic • Anatomy scan normal • Fetal echocardiogram normal • Irregular heartbeat, physician suspicious of LQT • No family history of sudden cardiac death/arrest, syncope, seizures Prenatal Diagnosis Enables Treatment •Goal of parents and clinical team was to administer correct neonatal therapy, not termination •Parents highly motivated •Possible diagnosis of LQT or an arrhythmia •After case review by cardiac and prenatal team, agreed to test the fetus (LQT panel) Result: KCNH2 mutation

• Pathogenic variant in KCNH2 previously reported as de novo in a neonate with: • Fetal bradycardia • Torsades de pointes • 2:1 atrioventricular block • Infant asymptomatic at 3 months following therapy with propanolol and a pacemaker • Our patient reported to match this presentation • Patient treated with beta blocker and is doing well Expansion of Newborn Screening

70 60 50 40 30 Pompe 20 Tandem SCID MPS-I Mass CHD X-ALD 10 0 1960 1970 1980 1990 2000 2006 2012 2016 Core Conditions Secondary Conditions Seizures

•9 year old female •Seizures and dyskinesia at birth, microcephaly, •No known family history of similar symptoms Positive for a de novo mutation in SLC2A1 Causing GLUT1 deficiency syndrome

GLUT1 deficiency syndrome is due to the inability to transport glucose to the brain Diagnostic Implications: • In individuals with SLC2A1 mutations, a ketogenic diet often improves control and reduces paroxysmal events, although cognitive impairment persists if damage has already been done. The Most Efficient Strategy to a Diagnosis for Many Conditions is Exome Sequencing: Yield by Clinical Indication

Retterer, Genetics in Medicine, 2015 Diagnostic Yield of Panels

Gene Panel Type N Overall Dx Yield

Dermatology 68 62% Endocrinology 36 61% Inborn errors of metabolism 122 59% Renal diseases 107 57% Deafness 147 54% Vision 418 52% Neurology 524 40% Syndromic DD/ID 25-47% Non-syndromic DD/ID 11% Dysmorphology-Dysplasia 354 38% Primary Immunodeficiencies 196 37% Pulmonology 36 36% Gastroenterology 73 29% Hematology 33 24% Adapted from Saudi Mendeliome Group Study, 2015 Panels vs Exomes Pros Cons • Cheaper • Miss novel • Less (more?) to analyze • No opportunity to interrogate • Shorter turnout time additional genes for other indications in the future • No incidental findings Diseases for which panels sufficient for most patients -Germline cancer -Cardiac diseases (cardiomyopathies, inherited arrhythmias, aortopathies) -Hearing loss -Retinitis Pigmentosa Publications of Novel Disease Genes Identified from Exome Sequencing Simons Variation in Individuals Project (Simons VIP)

• Study of monogenic forms of to increase Genes Associated with Features of Autism homogeneity of subjects to ACTL6B CHAMP1 DYRK1A KMT2C PURA enable more robust and ADNP CHD2 FOXP1 KMT2E REST replicable studies of the brain AHDC1 CHD8 GRIN2A MBD5 SCN2A and behavior ANK2 CSNK2A1 GRIN2B MED13L SETD5 ANKRD11 CTBP1 HIVEP2 PACS1 SMARCC1 ARID1B CTNNB1 HNRNPH2 PBRM1 SMARCC2 ASH1L CUL3 KAT6A POGZ STXBP1 ASXL3 DDX3X KATNAL2 PPP2R5D SUV420H1 BAF190 DSCAM KDM5B PTCHD1 SYNGAP1 BCL11A DST KDM6B PTEN TBR1 PACS1: bringing families together

• Arg203Trp mutation is associated with autism/intellectual disability/ • Associated with congenital heart disease • Transport that mediates the localization and movement of other along the trans-Golgi-network The mission of SPARK – an online, long-term study – is simple. We want to speed up research and advance our understanding of autism. Help spark better futures for all individuals and families affected by autism.

SPARKforAutism.org SPARK: Simons Foundation Powering Autism Research through Knowledge

To recruit, engage, and retain 50,000 individuals with ASD and their biological family members to:

• Identify causes of ASD • Accelerate clinical research and find new treatments • Enable genotype-driven research • WES performed and monogenic causes of autism are CLIA confirmed and returned to families

SPARKforAutism.org sfari.org/resources/sfari-base SPARK is returning individual genetic results related to ASD

• Pre-define list of genes that Committee agrees are established ASD genes, list updated annually (90 genes and CNVs)

• Variants are confirmed in CLIA lab and clinical report issued

• Committee reviews each case prior to returning result

• If participant chooses to receive result, SPARK returns result through a central genetic counselor/geneticist or report to participant’s medical provider

• Centralized expertise that scales Reinterpretation of Exome Data Has Significant Yield

25% 26% 49% 75% 10% 15%

DIAGNOSTIC YIELD ON REANALYSIS INITIAL DIAGNOSTIC YIELD OF NEGATIVE CASES

Diagnosis = 25% Diagnosis = 51% Known Genes No Diagnosis = 75% No Diagnosis = 49% Novel Genes Candidate Genes Opportunities and Challenges for Genomic Sequencing

In a study of WGS in 35 NICU patients (Petrikin et al., 2015) Diagnostic yield 57% (20/35) 65% are due to de novo variants Molecular diagnosis had not been considered in the differential diagnosis in 45% (9/20) Diagnosis had clinical impact in 65% of diagnosed patients. Turn around time Insurance coverage Need for iterative re-analysis Deciding what to report Impact of an Early Diagnosis

Petrikin JE et al., 2015 Impact of an Early Diagnosis

Petrikin JE et al., 2015 Solutions Needed for Clinical Exome/Genome Sequencing

• Turn around time: 2-4 weeks • Consolidation of data generation to sites able to do this cost effectively and efficiently • Continue family based analyses for now for diseases with high de novo frequency • Elimination of orthogonal confirmations in some scenarios • Automated pipelines for standard analysis • Federation of gene/disease experts for difficult interpretations Solutions Needed for Clinical Exome/Genome Sequencing

• Insurance coverage: for specific clinical scenarios sufficient evidence exists for coverage • Major congenital anomaly • Neurodevelopmental disorders (ID, autism, epilepsy, myopathy, neuropathy) • Early onset hearing/visual impairment • Rare presentations Solutions Needed for Clinical Exome/Genome Sequencing

• Need for iterative re-analysis • New methods to identify indels/CNVs • Better algorithms to predict pathogenic variants • New genes/phenotypic expansion of known genes • Better understanding of dual diagnoses Boycott et al., 2017 Solutions Needed for Clinical Exome/Genome Sequencing

• Deciding what to report • Need for interaction between clinicians and laboratorians • Incorporating patient preferences • Especially challenging for fetuses/newborns when phenotype is incomplete Improving Interpretation of Genomic Data: Integration of multiple data types • More data on controls • Cells, tissues and timing of expression • Value of data from communities with of all genes increased consanguinity • Binding sites of promoters, enhancers, • Constrained/haploinsufficient genes splice enhancers, RNA binding • Constrained regions of genes/gene proteins families • High throughput functional assays • Improved methods of predicting • Use of somatic mutation data functional impact of missense variants • 38% of all potentially causative damaging (LGD or D-mis) de novo variants observed • Improved methods of predicting in developmental delay cases are located functional impact of inframe indels in candidate cancer driver genes • Three dimensional structure of more proteins and sites of protein protein interaction What Do We Miss With Exomes? • CNVs, re- arrangements • Indels • Repeats • Non-coding regions • Mosaics (overgrowth, brain malformations, Jamuar et al., 2014 autism) What Is The Solution?

• Long reads • Higher read depth • More even coverage • Transcriptomes? • What is the incremental yield and cost (data generation, analysis and storage) • Genomes? • What is the incremental yield and cost (savings on library prep but increased cost in data generation, analysis and storage) Variant Classification is Not Uniform, But Converges With Discussion

Classification of the same variant across laboratories 80% 70% 60% 50% 22% 40% 71% 30% 5% 20% 34% 44% 10% 24% 0% Agreement Discordant Agreement Discordant Before After Amendola LM et al., 2016 What Should the Policy Be to Reinterpret Variants/Genomes?

• Whose responsibility? Pathogenic • How often? • Who pays? • Subscription services to handle VUS reinterpretation? • Which reclassifications get reported? • Same policy for retrospective versus prospective cases? • Same policy for interpretation of exomes/genomes? Benign • High yield of reinterpretation over time Laboratory Clinvar Private archive of Public archive of variants identified in lab variants EMR

Subscription Service Variant Alert Larger Data Sets Updated variant Machine Learning/Artificial interpretation available Intelligence Genomic Workforce Is Growing, But Not Fast Enough Future Dissemination of Genomic Medicine

CLINICAL EXPERTISE

Low

ENABLERS Medium Educational materials and public education Simplified billing/insurance coverage High Centralized clinical expertise for rare disorders

LAB EXPERTISE ENABLERS Larger datasets of ethnically diverse individuals Aggregated disease data Automated variant interpretation Automated exome/genome interpretation in clinical context Automated reinterpretation Peek Into The Future…

BFOR Study BRCA founder outreach study; provides genetic testing for common BRCA mutations for women and men of Ashkenazi Jewish ancestry.

Angelina Jolie Public awareness and education surrounding genetic testing is increasing. Cost Effectiveness of BRCA screening

Cost-effectiveness of strategies in the United States Testing Strategy Age range, Cost-effectiveness ratio population ($/QALY) Annual All ages >340,000 Mammography BRCA mutation >30, Universal 1.7 million (Myriad) screening >30, Universal 92,000 (Ambry) >30, Universal 53,000 (Color Genomics) >30, AJ Cost-saving Fine Tuning Risk for BRCA1 Carriers Improvements in Genetic Risk Calculators

HIGHLY MODERATELY POLYGENIC COMPOSITE PENETRANT PENETRANT RISK SCORE RISK GENES GENES Personalized Risk App

Analytics

Can adjust data to view risk over lifetime with lifestyle modifications

Dashboard

Receive alerts about scheduling annual health surveillance, news health alerts, etc.

Genetics

Calculate affect of genetic test results on health outcomes

Medical Record

View EMR and other medical record Personalized risk app that factors in genetics information as well as other risk modifying variables. Modern EMR Dashboard

Support Groups/News Feed

Problem List Genetic Test Results Right breast cancer CHEK2 positive High blood pressure KCNQ1 positive History of

Annual Health Surveillance Health Alerts Mammography/MRI Long QT syndrome Colonoscopy Pharmacogenetics Laboratory services Weight management (SMA) . Progressive degeneration & loss of spinal cord & brainstem motor neurons . Muscle weakness, atrophy . Difficulty breathing, poor weight gain, pneumonia, scoliosis, joint contractures Age at onset, symptoms, severity and survival vary (types 1, 2, 3, 4) SMA Incidence and Genetics

Most common genetic cause of infant & SMN2 = SMN1 homologue (Both produce SMN, differ by 5 nucleotides) toddler death

• Incidence: 1 in 6,000 to 1 in 11,000 full-length SMN (100%) • Carriers: 1 in 50 to 1 in 60 SMN1 C 6 7 8 SMN2 T 95%–98% homozygous deletion of Survival of Motor Neuron 1 (SMN1) exon 7 truncated, non-functional SMN (~85-95%) full-length SMN (~5-15%) SMN1 (5q13)

# genomic copies of SMN2 varies (0–5) exon 1 2a 2b 3 4 5 6 7 8 ↑ SMN2 ≈ less severe, later onset SMN2 copy number modifies SMA phenotype

Feldkoter et al.: Am.J.Human Genetics 70: 358-368, 2002. Pilot SMA Newborn Screening

NY Presbyterian, Morgan Stanley Columbia University Medical Center, Children’s Hospital NY Presbyterian Hospitals, and Manhattan NYS Newborn Screening Program 4,400 births/yr

Weill-Cornell Major Goals Medical Center  Develop SMN1 assay Manhattan  Demonstrate feasibility of high-throughput 5,800 births/yr newborn SMA screening  Offer screening, assess uptake and outcomes Allen Hospital Upper Manhattan/ Bronx 2,000 births/yr The result of SMA newborn screening GeneGene Therapy Therapy for withSMA with AAV9 AAV9 for SMA

Mendell et al NEJM 2017 Conclusions • Growing number of opportunities for genomic medicine • Demand will increase as sequencing costs come down and as interpretation improves and is automatable • Demand will increase as therapies and preventative options are available • We need scalable solutions with greater centralization of expertise enabled through collaborations of experts and the enable patients • We must collect evidence distributed across health care systems to support evidence collection Acknowledgements

• Arianne Perez-Garcia • Gudrun Aspelund Patients and their families • Michael Hadler • Mark Arkovitz • Isaura Rigo • Ken Azarow • Julia Wynn • Kara Kelly • Brian Bucher Postdoc positions available • Ashley Wilson • Chaim Jalas • Dai Chung • Donna Russo • Elisabeth Paietta • Tim Crombleholme • Janis Racevskis • Foong Yen Lim • Lan Yu • • Jacob M. Rowe George Mychaliska • Lijiang Ma • Doug Patoka • • Patrick Cheung Martin S. Tallman • John Pietsch • Maddalena Paganin • Patricia Lanzano • Bard Warner • Giuseppe Basso Wei Tong • Charles Stolar • Liyong Deng • Adolfo A. Ferrando • Usha Krishnan • Jiancheng Guo • Elizabeth E. Crouch • Eric Austin • Charles LeDuc • Jay Lefkowitch • Jeff Delaney • Jimmy Duoung • Mirjam M.C. Wamelink • Scott Fletcher • Cornelis Jakobs • Rob Gajarski • Yan Zhang • • Gajja S Salomons Mark Grady • • Eunice Hahn Josue Martinez • Xiaoyun Sun • Paul Appelbaum • Shelby Kutty • Rocky Kass • Eric Michelfelder • Robert Klitzman • Danilo Roman-Campos • Donald Moore • Roslyn Yee • Mélanie Eyries • Erika Rosenzweig • Dorothy Warburton • Kevin Sampson • Christiana Farkouh • Emma Marquez • Florent Soubrier • Annette Zygmunt • Jennifer Butcher • Katrina Celis • Marine Germain • David-Alexandre Trégouët • Kate Brennan • • Ismee Williams • Alain Borczuk Mary Michaeleen Cradock • Bob Drongowski • Jennie Kline • Erika Berman Rosenzweig • • Teresa Gratton Teresa Lee • Barbara Girerd • Barbra Jackson • Yufeng Shen • David Montani • Howard Needleman • Matthew Lewis • Marc Humbert • James E. Loyd Acknowledgments

Surgeons Research Coordinators Developmental Specialists Cardiologists/ Funding X01 HL136998 Gudrun Aspelund Julia Wynn Christiana Farkouh Pulmonologists R01 HD057036 Mark Arkovitz (p) Jennifer Kraszewski Annette Zygmunt Usha Krishnan CHERUBS Ken Azarow Lorrie S Burkhalter Anketil Abreu Eric Austin (p) ACDHO Brian Bucher Trish Burns Jennifer Butcher Jeff Delaney Global CDH Dai Chung (p) Kate Brennan (p) Mary Dabrowiak (p) Scott Fletcher Breath of Hope Michael Cotton Kerry Miller Help4CD Tim Crombleholme Brandy Gonzalez Mary Michaeleen Cradock Rob Gajarski Robert Cusick Sheila Horak Bob Drongowski Mark Grady National Greek Orthodox Melissa Denko Jeannie Kreutzman Teresa Gratton Eunice Hahn (p) Ladies Philoptochos Mahmoud ElFiky Michelle Knezevich Barbra Jackson Shelby Kutty Society, Inc. Kimberly Fischer Cheryl Kornberg Jolene Johnson Eric Michelfelder Fore Hadley Foundation Mamatha Gowda Karen Lukas Arielle Wilson (p) Donald Moore (p) The Wheeler Foundation Anthony Hesketh (p) Julia McKee Leah Miller (p) Erika Rosenzweig The Vanech Foundation David Kays Joy Perkins Howard Needleman Shannon Nees Larsen Family Przemyslaw Kosinski Tracy Perry Tasnim Najaf MGH Brountzas/Kostaridis Foong Yen Lim Molecular and Statistical Lab Min Shi (p) Patricia Donohoe Family David McCulley Patricia Lanzano Wilke Family Caroline Maloney Jayne Sicard –Su (p) Mauro Longoni Jiancheng Guo Henley Family George Mychaliska Gentry Wools Lan Yu Frances High Guzman and Padolina Xavier Pompar Jeannie Zuk Liyong Deng Maria Loscertales Family Doug Potoka (p) Connie Keung (p) Charles LeDuc Joy Maliackal Poulo John Pietsch (p) Julie Moteagudo (p) Jimmy Duoung Jessica Kim Orowitz Family David Schindel Christine Schad (p) Yuan Zhang Caroline Collette Schwartz Family Samuel Soffer Jessica Schultz (p) Yufeng Shen Betty Gilman Charles Stolar (p) Ruth Swedler (p) Hongjian Qi Functional Studies Amy Wagner Linshan Shang (p) Okochi Shunpel Gabrielle Kardon Brad Warner Chen Qiang Aqsa Schakoor Kate Ackerman Xie Yi-Min Xin Sun DHREAMS Participants Thank you to all the families & participants in SPARK

John Acampado Alex Lash Natalia Eirene Pamela Feliciano LeeAnne Jennifer Casey White- Elizabeth Brooks Wendy Chung Kiely Law Volfovsky O’Conner Scientific Green-Snyder Tjernagel Lehman Clinical Research Project Manager Chief Inform. SPARK PI Research Officer Analytics Man. Admin. Assist. Director Clinical Res. Sci. Proj. Man., VIP Proj. Man., SSC Specialist Consultant

Swapnil Shah Noah Lawson Matt Kent Alpha Amatya Richard Marini Chris Rigby Martin Butler Kevin Layman Cheryl Cohen Beverly Robertson Vincent Myers Software Eng. Res. Data Res. Data Sr. Software Sr. Software Sr. Software Software Sr. Software Community Outreach Manager Comm. Specialist Analyst Analyst Engineer Engineer Engineer Engineer Engineer Consultant

Ron Edgar Andrea Ace Emily Singer Luke Grosvenor Alex Stephens Lindsey Cartner Brianna Vernoia Wubin Chin Swami Ganesan Amy Daniels Hana Zaydens Development Business & Ops. Science Writer Research Coordinator Coordinator Research Sr. Software Business analyst Project Research Manager Coordinator Assistant Engineer Manager Coordinator Consultant The SPARK Team sfari.org Special thanks to the SPARK Clinical Network SPARKforAutism.org The Simons VIP Team Questions???

Wendy Chung [email protected] Acknowledgements

• Julia Wynn • Arianne Perez-Garcia • Gudrun Aspelund • Michael Hadler • Mark Arkovitz • Ashley Wilson • Isaura Rigo • Ken Azarow • Kara Kelly • Brian Bucher • Donna Russo • Dai Chung • Lan Yu • Chaim Jalas • Tim Crombleholme • Elisabeth Paietta • Foong Yen Lim • Lijiang Ma • Janis Racevskis • George Mychaliska • Patrick Cheung • Jacob M. Rowe • Doug Patoka • John Pietsch • Patricia Lanzano • Martin S. Tallman • Bard Warner • Liyong Deng • Maddalena Paganin • Charles Stolar • Giuseppe Basso Wei Tong • Usha Krishnan • Jiancheng Guo • Adolfo A. Ferrando • Eric Austin • Charles LeDuc • Elizabeth E. Crouch • Jeff Delaney • Scott Fletcher • Jimmy Duoung • Jay Lefkowitch • Rob Gajarski • Yan Zhang • Mirjam M.C. Wamelink • Mark Grady • Cornelis Jakobs • Eunice Hahn • Josue Martinez • Gajja S Salomons • Shelby Kutty • Eric Michelfelder • Paul Appelbaum • Xiaoyun Sun • Donald Moore • Robert Klitzman • Rocky Kass • Erika Rosenzweig • Danilo Roman-Campos • Christiana Farkouh • Roslyn Yee • Mélanie Eyries • Annette Zygmunt • Dorothy Warburton • Kevin Sampson • Jennifer Butcher • Kate Brennan • Emma Marquez • Florent Soubrier • Mary Michaeleen Cradock • Katrina Celis • Marine Germain • Bob Drongowski • David-Alexandre Trégouët • Teresa Gratton • Ismee Williams • Alain Borczuk • Barbra Jackson • Howard Needleman • Jennie Kline • Erika Berman Rosenzweig • Teresa Lee • Barbara Girerd • Yufeng Shen • David Montani • Marc Humbert [email protected] • James E. Loyd