1. Pharmacogenomics in Diabetes Mellitus
Toni I. Pollin, MS, PhD, CGC
Associate Professor
Departments of Medicine and Epidemiology & Public Health
September 22, 2018

2. Disclosures
I, Dr. Toni Pollin, have nothing to disclose.

3. Learning Objectives
Pharmacists: At the completion of this activity, the participant should be able to
Explain the use of common genetic markers to predict treatment response in Type 2 Diabetes
Explain how diagnosis of specific and highly penetrant forms of diabetes informs the selection of appropriate treatment
Describe pharmocogenetic approaches used to identify novel drug target treatments for type 2 diabetes
Pharmacy Technicians: At the completion of this activity, the participant should be able to
Define pharmacogenomics
Define a genetic marker
List examples of genetic markers
Explain how genetic markers are used in the treatment of diabetes

4. Pharmacogenomics
NHGRI: Pharmacogenomics is a branch of pharmacology concerned with using DNA and amino acid sequence data to inform drug development and testing.
Includes:
Study of how individual genetic variation informs differential drug response (efficacy and adverse events)
Study of how the genome reveals novel drug targets

5. Quick DNA/Genetics Review
(Not to scale!)

6. DNA is a Blueprint for Protein
ASCO Curriculum: Cancer Genetics & Cancer Predisposition Testing
DNA is a Blueprint for Protein
How it all works
Our Bodies are made up of cells
Inside our cells are packets of genetic information called chromosomes
The chromosomes are made up of strains of DNA that are wound up into tight little packets
Sections of DNA that tell us how to make something are genes
What genes make are called proteins
Basic Genetics 2

7. The Genetic Code

8. Gene Regulation

9. Genetic Variant/Genetic Marker
NHGRI: DNA sequence with a known physical location on a chromosome…The genetic marker itself may be a part of a gene or may have no known function
Genetic Variant
Location in the DNA sequence that varies among individuals
May be rare or common
May impact protein sequence, regulatory or other sequence, or be a marker for a variant that does

10. Diabetes Classification
(ADA/WHO*)
Type 1 Diabetes (T1DM)
Type 2 Diabetes (T2DM)
Specific types of diabetes due to other causes
Gestational diabetes mellitus (GDM, ~4% of pregnancies)
Type 2
T1: destruction of pancreatic beta cells, usually autoimmune
T2: heterogeneous
T3: Nongenetic (e.g., injury) and rare single gene forms
Gestational—won’t be addressed here
Pie show “permanent” types
Specific
types due to
other causes
Type 1
*ADA = American Diabetes Association
WHO = World Health Organization

11. Relevant to Type 2 Diabetes: Metformin Pharmacokinetics
SLC47A1
SLC29A4
SLC22A3
SLC22A1
SLC22A2
Adapted from Todd and Florez, Pharmacogenomics 15:529, 2014

12. SLC22A1 coding variants reduce metformin response in stably transfected HEK293 cells
Shu et al, JCI 117:1422, 2007

13. SLC22A1 coding variants associated with reduced metformin glycemic response in healthy volunteers
Shu et al, JCI 117:1422, 2007

14. Diabetes Prevention Program (DPP)
Multi-ethnic, multicenter clinical trial randomizing individuals with pre-diabetes to three treatment arms and followed for diabetes incidence for mean follow-up time of 3.2 years
Placebo
850 mg metformin 2x/day
Intensive lifestyle intervention: Goal of 150 minutes/week moderate exercise and 7% weight loss through dietary fat intake reduction
Troglitazone (ended prematurely due to drug recall)
DPP Research Group, NEJM 346:393, 2002

15. Diabetes Prevention Program (DPP): Main Results
DPP Research Group, NEJM 346:393, 2002

16. SLC22A1 (OCT1) Coding SNPs Associated with Metformin Response
Pollin et al, in preparation

17. Haplotype Analysis Reveals Specific OCT1 Isoform Associated with Reduced Response
Pollin et al, in preparation

18. Diabetes Free Survival: All
Pollin et al, in preparation

19. Diabetes-Free Survival by OCT1 Haplotype
Pollin et al, in preparation

20. GoDarts Study
Patients: Scottish observational cohort of individuals with T2DM of Scottish Ancestry
Outcome: Ability of metformin or sulfonylurea to reduce %HBA1c to 7% within first 18 months of therapy
Zhou et al, Nature Genetics 43:117, 2011

21. Zhou et al, Nature Genetics 43:117, 2011

22. CYP2C9 loss of function variants reduce risk of sulfonylurea monotherapy failure
Zhou et al (2009) Clinical Pharmacology & Therapeutics 87:52.

23. Metformin Response GWAS in GoDarts Study: Results in 1024 patients
Zhou et al, Nature Genetics 43:117, 2011

24. Metformin Response GWAS in GoDarts Study: Results
Zhou et al, Nature Genetics 43:117, 2011

25. Metformin Response GWAS in GoDarts Study: ATM Variant
Zhou et al, Nature Genetics 43:117, 2011

26. Replication of ATM Association with Metformin Response
HBA1c ≤ 7%
HBA1c
van Leeuwen et al, Diabetologia 55:1971, 2012

27. No Association of ATM Variant with Metformin Response in the DPP
Florez et al, Diabetes Care 35:1864, 2012

28. Fajans et al, NEJM 2001

29. Shepherd et al, Diabetic Medicine 2009

30. Monogenic Diabetes is Underdiagnosed in the U.S.: The SEARCH Study
Pihoker et al (2013), JCEM 98:4055

31. SEARCH Participants with MODY Mutations
Pihoker et al (2013), JCEM 98:4055

32. Components of the Personalized Diabetes Medicine Program
Patient completes questionnaire
If pathogenic or likely
pathogenic variant found:
Diagnosed before 1 year?
Diagnosed before 30 years?
Age of diagnosis ____
Hearing or visual impairment/birth defects/ kidney disease?
Extremely overweight at diagnosis?
Type 1 diabetes?
Parent or child with type 1 diabetes?
2 or more people related by blood with diabetes?
Confirm, disclose and add to electronic health record and customize treatment
Make genetic counseling and testing available to family members
Further workup as indicated
If indicated…
C-peptide Positive?
IA-2 Antibody negative?
Consistent family/ medical history elicited by genetic counselor
Sequence 40 monogenic diabetes genes for mutations
If variant of unknown
Significance found:
Segregation in family
Functional studies

33. Next Generation Sequencing Panel
MODY
Neonatal Diabetes
Lipodystrophy
HNF4A
HNF1A
PDX1/IPF1/STF1
HNF1B
NEUROD1
KLF11
CEL
PAX4
BLK
AGPAT2
BSCL2
CAV1
LMNA
PLIN1
PPARG
PPP1R3A
PTRF
ABCC8
GCK
INS
KCNJ11
ZFP57
ALMS1
CISD2/WFS2
EIF2AK3
FOXP3
GATA6
GLIS3
INSR
PTF1A
RFX6
SLC19A2
SLC2A2
WFS1
Syndromes
Severe Obesity
Hyperinsulinemia
MC4R
LEP
LEPR
SIM1
GLUD1
HADH

34. IGNITE Network

35. PDMP Current Results by the Numbers
Individuals identified with monogenic diabetes
Gene
Disease
Number
GCK
MODY2/
GCK-MODY 19
HNF1A
MODY3/
HNF1A-MODY 7
HNF4A
MODY1/
HNF4A-MODY 2
INS
MODY10
LMNA
Familial partial lipodystrophy
HNF1B
MODY5/
Renal Cysts & Diabetes 1
KCNJ11
MODY13/
KATP diabetes
WFS1
Wolfram syndrome
MC4R
Monogenic obesity
2,190 patients screened with questionnaire at 4 sites
532 patients enrolled
507 patients sequenced and analyzed (includes 311 suspected monogenic diabetes cases plus 196 controls)
36/311 (11.6%) hit rate in cases
Study sites (Figure 1):
University of Maryland Medical System & Center for Diabetes and Endocrinology – academic medical center with a large active pediatric and adult diabetes population
Geisinger Health System – integrated health system in northeastern Pennsylvania
Bay West Endocrinology Associates –endocrinology private practice in Towson, MD
Baltimore Veterans Administration Medical Center – VA Maryland Health Care facility
Primary screen: Simple 7-question screening tool distributed to diabetes patients of study locations that determines which patients are invited for enrollment in the study.
Patient visit: Patient provides informed consent, samples for routine blood tests, and samples for genetic testing. A genetic counselor collects the patient’s individual and family medical history.
Routine laboratory testing: Samples are tested for C-peptide to measure residual insulin secretion and anti-GAD65 and anti-IA-2 antibodies to detect signs of type 1 diabetes.
Asynchronous case conference: Patients are selected for genetic testing based on study inclusion criteria (Table 1) through an online discussion of de- identified patient data, including individual medical history, family medical history, and diabetes blood tests.
Genetic testing: Using an Ion Torrent PGM benchtop sequencer (Figure 3), sequencing of the coding and flanking regions of 40 genes causative for MODY, NDM, syndromic forms of diabetes, and non-syndromic forms of diabetes. Genetic variants are interpreted and classified based on ACMG standards and guidelines.5
Clinical confirmation: “Likely pathogenic” or “Pathogenic” variants are confirmed by Sanger sequencing in the CLIA/CAP accredited UMMS Translational Genomics Laboratory.
Return of results: Patients with reportable findings have an appointment with a genetic counselor and a medical geneticist to discuss the findings and implications for their healthcare treatment. Written reports are provided to the patient and to the patient’s physician through the EHR.

36. Case Example 9 y/o female dx T1DM at 15mth
No DKA
Neg GAD*, IA2
Treated with insulin
Family hx significant for T1DM in mother (dx.5) and first cousin once removed

37. Diagnosis
KCNJ11: c.697C>T p.(Leu233Phe); (heterozygous): Likely pathogenic
MODY13
Specific protocol to transition from insulin

38. KCNJ11 p.Leu233Phe mutation was previously reported only once—in a sulfonylurea-responsive child dx DM at 5 weeks with polyuria since 3 days and showed in vitro response to sulfyonylureas
Joshi and Phatarpekar (2011) World J Pediatrics 7:371
Babiker et al (2016) Diabetologia 59:1162

39. Follow-up on Case
9-year old proband successfully transitioned from insulin to glyburide in 13 days
42-year old mother diagnosed with T1DM at 5 years confirmed to have same mutation and has transitioned from insulin to glyburide
Mother’s endocrinologist now convinced of importance of antibody testing for all T1DM dx
6 year old brother with normoglycemia confirmed not to have the mutation
Mother’s cousin with diabetes also confirmed not to have the mutation
Mother’s parents do not have the mutation (de novo in proband’s mother)

40. High dose sulfonylureas are efficacious and safe in KCNJ11 diabetes in the long term (n = 81)
Bowman et al (2018) Lancet Diabetes & Endocrinology 6:637

41. At least 4.5% (22/488) of overweight/obese youth diagnosed with T2DM have MODY: The TODAY Study
Treatment Options for type 2 Diabetes in Adolescents and Youth (TODAY) study analyzed the effectiveness of metformin alone or in combination with rosiglitazone or lifestyle changes in adolescents (10-17) with recently (within two years) diagnosed T2D. JF/TP, etc. analyzed the prevalence of monogenic diabetes in 488 TODAY study participants and their outcomes.
Kleinberger, et al., Genetics in Medicine 2017

42. Patients with HNF4A-MODY diagnosed with T2DM fail treatment with metformin: The TODAY Study
From paper: However, none of the patients
with GCK-MODY failed the treatment regimens in the
TODAY study. This is consistent with the GCK-MODY
phenotype of mildly elevated fasting blood glucose (fasting
glucose of 5.49–8.66mmol/L and HbA1c of 5.6–7.6%) that
usually needs no treatment to avoid chronic complications of
diabetes. In contrast, 6 of 7 patients with HNF4A-MODY failed
treatment across study arms (hazard ratio = 5.03 P = ),
indicating poor response regardless of therapies offered in the
TODAY study. Similarly, though not statistically significant,
3/5 patients with HNF1A-MODY failed the TODAY study
treatments. These results would be expected since the
established treatment for HNF1A- and HNF4A-MODY are
sulfonylurea drugs, rather than metformin and/or
rosiglitazone.7,8 Metformin is an insulin-sensitizing agent,
while sulfonylureas are insulin secretagogues that improve
the insulin secretion deficit found in HNF1A- and HNF4AMODY
patients. Therefore the finding that HNF4A-MODY
patients failed metformin treatments in the TODAY trial is a
demonstration of the consequences of not attaining a genetic
diagnosis of MODY.We note that it is possible that in addition
to sulfonylureas, metformin and/or thiazolidinediones may be
appropriate for some monogenic diabetes patients with
concomitant obesity and insulin resistance.
Kleinberger, et al., Genetics in Medicine 2017

43. Zinc Transporter Null Variants Appear to Protect Against Diabetes
Flannick et al (2014) Nature Genetics

44. Concluding Remarks
Some promising research suggests potential pharmacogenetic targets for type 2 diabetes
Replication needed
Pharmacogenetic targets already exist for monogenic diabetes (~2% of diabetes)
Future diabetes treatments may be informed by novel type 2 diabetes genetic discoveries

45. Acknowledgments Jose C. Florez Sook-Wah Yee Kathleen A. Jablonski
Jarred B. McAteer
Andrew Taylor
Kieren Mather
Edward Horton
Neil H. White
Elizabeth Barrett-Connor
William C. Knowler WC
Kathleen M. Giacomini
Alan R. Shuldiner
Diabetes Prevention Program Research Group
NIH R01 DK72041

46. Alan Shuldiner
Kathleen Palmer
Mickaela Nicholson
Tom Fitzgerald
Tameka Alestock
Devon Nwaba
Mary Pavlovich
Kristin Maloney
Casey Overby
Daniel Mullins
Daisuke Goto
Kate Tracy
Deborah Greenberg
Stephanie Stein
Kristi Silver
Rana Malek
Katie Bisordi
Nanette Steinle
Melanie Leu
Richard Horenstein
Elizabeth Lamos
Kashif Munir
Ilias Spanakis
Elizabeth Streeten
Yasaman Mohtasebi
Linda Jeng
Coleen Damcott
Nicholas Ambulos
Jeff Kleinberger
Trevor Matthias
Danielle Sewell
Haichen Zhang
Keith Tanner
Yue Guan
UM CDE Staff and Patients
PPGM/ UMB MODY Fund

47. UMB Program for Personalized and Genomic Medicine
Partners and Funding
David Carey
John Kennedy
Ying Hu
Kristina Blessing
Misha Rashkin
Jessica Goehringer
Natacha Antunes
Mallory Snyder
Philip Levin
Karen Klein
Lee Bromberger
Harvey Institute
Amy Kimball
Christie Newsome
Christy Haakonsen
Marcia Ferguson
Jennifer Billiet
NHGRI U01 HG00775
ignite-genomics.org
NICHD U24 HD093486
UMB Program for Personalized and Genomic Medicine
UMB Foundation MODY Fund

48. References www.genome.gov
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49. References, continued
Shepherd M, Shields B, Ellard S, Rubio-Cabezas O, Hattersley AT. A genetic diagnosis of HNF1A diabetes alters treatment and improves glycaemic control in the majority of insulin-treated patients. Diabet Med Apr;26(4): doi: /j x. PubMed PMID:
Pihoker C, Gilliam LK, Ellard S, Dabelea D, Davis C, Dolan LM, Greenbaum CJ, Imperatore G, Lawrence JM, Marcovina SM, Mayer-Davis E, Rodriguez BL, Steck AK, Williams DE, Hattersley AT; SEARCH for Diabetes in Youth Study Group. Prevalence, characteristics and clinical diagnosis of maturity onset diabetes of the young due to mutations in HNF1A, HNF4A, and glucokinase: results from the SEARCH for Diabetes in Youth. J Clin Endocrinol Metab Oct;98(10): doi: /jc Epub 2013 Jun 14. PubMed PMID: ; PubMed Central PMCID: PMC
Joshi R, Phatarpekar A. Neonatal diabetes mellitus due to L233F mutation in the KCNJ11 gene. World J Pediatr Nov;7(4): doi: /s z. Epub 2011 Jan 5. PubMed PMID:
Babiker T, Vedovato N, Patel K, Thomas N, Finn R, Männikkö R, Chakera AJ, Flanagan SE, Shepherd MH, Ellard S, Ashcroft FM, Hattersley AT. Successful transfer to sulfonylureas in KCNJ11 neonatal diabetes is determined by the mutation and duration of diabetes. Diabetologia Jun;59(6): doi: /s Epub 2016 Mar 31. PubMed PMID: ; PubMed Central PMCID: PMC
Bowman P, Sulen Å, Barbetti F, Beltrand J, Svalastoga P, Codner E, Tessmann EH, Juliusson PB, Skrivarhaug T, Pearson ER, Flanagan SE, Babiker T, Thomas NJ, Shepherd MH, Ellard S, Klimes I, Szopa M, Polak M, Iafusco D, Hattersley AT, Njølstad PR; Neonatal Diabetes International Collaborative Group. Effectiveness and safety of long-term treatment with sulfonylureas in patients with neonatal diabetes due to KCNJ11 mutations: an international cohort study. Lancet Diabetes Endocrinol Aug;6(8): doi: /S (18) Epub Jun 4. Erratum in: Lancet Diabetes Endocrinol Sep;6(9):e17. PubMed PMID: ; PubMed Central PMCID: PMC
Kleinberger JW, Copeland KC, Gandica RG, Haymond MW, Levitsky LL, Linder B, Shuldiner AR, Tollefsen S, White NH, Pollin TI. Monogenic diabetes in overweight and obese youth diagnosed with type 2 diabetes: the TODAY clinical trial. Genet Med Jun;20(6): doi: /gim Epub 2017 Oct 12. PubMed PMID: ; PubMed Central PMCID: PMC
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50. CE Access Code and Instructions
pharmacogenomicsDM