1. DIABETES MELLITUS
AND ROLE OF GENOMICS
By
Maria Armie Pacheco RN, BSN,CPA N
Rutgers State University

3. DM and genomics
Case Presentation
28 Year old AA male presents to the E.R .with C/O of abdominal
pain associated with nausea/vomiting, generalized weakness,
increased frequency in urination, extreme thirst (as per the patient “
I can’t seem to drink enough water”, I am also extremely hungry
although I am too tired to eat”), the patient’s complaint also
included mild blurring of vision.

4. DM and Genomics
 Medical History : No past medical history reported
 Familial history: Grandmother, Father, Uncle and aunt with DM.
 Social History: denies smoking, (+)ETOH and elicit drug use
 Immunization: Flu Vaccine updated
 Medications: No current medication
 Allergies: NKDA

5. DM and Genomics
Physical Exam:
 V/S : BP 100/61 Temp. 36.2
HR 118 Spo2 94% RR- 28
 General Constitutional: AAO3, in mild distress, speech is clear, appropriate
affect
 Skin: Dry, cool, intact
 HEENT: Normocephalic, atraumatic, no ear discharges, anicteric sclerae,
pupils reactive and size 3mm bil., no thyromegaly, no lymphadenopathy
 Cardiopulmonary: ST, S1S2, no murmurs, no rubs, no gallops, clear lungs
bilaterally
 GI: soft abdomen, mild tenderness on palpation, no bruising
 GU: (+) frequency, non-distended bladder, no dysuria, no hematuria
 Musculoskeletal: overall muscle strength 4/5, no ROM limitation, no falls
 Psychological: anxious about current status, no suicidal tendencies

6. DM and Genomics
Chest X-ray: no cardiomegaly, no PTX, no signs of pleural effusion
EKG: Sinus tachycardia at 118
CT: Normal findings
Labs :
 WBC 11,000, HGB 11.4, HCT 34.3,
 Na 136, K 4.1, Cl 108, CO2 14,
 Glucose: 514, osmolality 310
 BUN 21, Creatinine 1.5,
 U/A : (+) ketones, (+) glucose
 Alb 3.5, Bili 0.7, AST 32, ALT 53, ALK P 89
 ABG: PH 7.32, CO2 29.1, PO2 95, Hco3 17 SpO2 97

7. DM and Genomics
Differential Diagnosis:
 DM
 DKA
 Pancreatitis
 Cholecystitis
 Appendicitis

8. DM and Genomics
This patient presented with early
manifestations of Diabetic Ketoacidosis
(DKA)

9. DM and Genomics
Diabetes mellitus is a group of metabolic disorders
characterized by:
 hyperglycemia
 abnormalities in carbohydrate, fat, and protein metabolism.
 It is resultant of insulin secretion, insulin sensitivity or both
Incidence Rates in U.S. (Nat. Diabetes Statistics Report/2014).
2.9 million people or 9.3% of the U.S. population has DM
Diagnosed : 21.0 million
Undiagnosed: 8.1 million (27.8% of people with diabetes are undiagnosed)

10. Diabetes mellitus
Forms of DM:
 Type I – absence of insulin
 Type 2 – Insulin deficiency
Insulin resistance
 MODY
 Gestational DM

11. DM and Genomics
Type 1
Epidemiology:
 Hallmark - autoimmune destruction of beta cells
 Represents approximately 10% of all cases
 Lifelong insulin
 Incidence of T1D is increasing at a rate of 3% per annum
 Puberty - peak age at onset
Risk factors:
 Genetics
 Environmental risk factors- initiators of beta cell autoimmunity
 Enteroviruses (CVB)
 Cows milk vs breast milk

12. DM and genomics
Type 2
 accounts for up to 90% of all DM cases and is usually characterized by the
presence of both insulin resistance and relative insulin deficiency.
 increase lipolysis and free fatty acid production,
 increased gluconeogenesis
 decreased skeletal muscle uptake of glucose
 B-cell dysfunction is progressive and contribute to worsening blood glucose
control over time.
 Type II DM occurs when a diabetogenic lifestyle (excessive calories,
inadequate exercise and obesity) is superimposed upon a susceptible genotype

13. DM and Genomics
Type 2
Epidemiology:
 Most common form (90% of all cases)
 High in Native A., predominant in Hispanics and AA than in
Caucasians
 Prevalence increases with age of population
 Prevalence increased by 6-fold in adolescents (Bloomgard/2004)
Risk factors:
 Obesity
 Sedentary lifestyle
 Waist-to-hip ratio (WHR)

14. DM and Genomics
Pancreas
Islets of Langerhans
Alpha, beta, delta, and gamma cells
Glucagon
Insulin

16. hypothalamus
Polyphagia
Polydipsia
Polyuria
Liver
(glycogenolysis)
adipocytes
VLDL/Triglyc.
receptor site
Intra-cellular
Energy
for cellular
activities
Intra-
vascular
Osmotic pressure
Glucose
+
Insulin
Absence/ deffic.
/Insensitivity.
CHOO/CHON
Utilization =
Ketosis
Retinopathy
Neuropathy
Nephropathy
CHD
PAD
CVA
Gastro paresis
Infections
Skin Changes

17. T1Dandgenomics
HLAregiononchromosome6
MHC–multiplehistocompatibilitycomplex
involvedinpresentingantigentoimmune system
MHC
MHC1 MHC2 MHC3 Humoral Cell-mediated
T-killercell(CD8) T-helpercell(CD4)
…………
SeveralT1Dsusceptibilitygenes: ………..…….
HLA-DQB1,DQB1*0201,DQB1*0302, HLADR3, HLADQ1*0301 …………..
INS -∙∙chromosome1 …………
CTLA-4chromosome 2

18. Common susceptibility genes in DM:
T1DM
HLA region
on chromosome 6
- Polymorphisms in the
HLA complex account
for 40-50% of the
genetic risk
- HLA DR3
- HLADQ1*0301
- HLADQB1*0302
- HLADQB1*0201
T
Caucasians:
DQA1*0501-
DQB1*0201
and
DQA1*0301-
DQB1*0302
African Ame:
DRB1*07-
DQA1*0301-
DQB1*0201
T2DM
Transcriptor factor
7-like 2 gene
- Alters islet
function, alters
development, and
insulin secretion
PPARy
ABCC8
KCNJ11
CALPN10

19. DM and Genomics
Criteria for the Diagnosis of DM:
 Symptoms of DM
+ Random blood glucose conc. >200mgs/dl
 Or FPG = 126 mg/dl or
 Or AIC > 6.5 % or
 Or 2-hr plasma glucose>200mg/dl during OGTT
Criteria for DKA Diagnosis:
 Plasma glucose > 250
 ph <7.25
 Hco3 15-18
 Serum osmolality variable
 Anion gap >10
Impaired fasting glucose
Impaired glucose tolerance

20. Interventions:
DKA Management:
 Replace fluids (2-3L 0.9% NSS over 1-3h), then 15-20ml/kg/h; 0.45% NS
250-500ml/h; D5.45(150-250ml/h) when plasma glucose level is
200mgs/dl
 Short acting Insulin(0.1u/kg) then 0.1/kg/h cont. infusion. Increase 2-3
fold if negative response by 2-4h.
 If K+ is <3.3, do not give insulin till it’s corrected
 K replacement 10meq/h when K < 5.0-5.2 mEq /L, 40-80mq/h if K is <
3.5meq.
 Assess underlying cause (non-compliance, infection, cocaine, etc.)
 Glucose monitoring- q2hr, electrolytes/anion gap q4 1st 24 hr.
 Close monitoring of v/s, LOC, Intake/Output
 Cont. above till pt. is stable, Glucose goal is (150-250mg/dl), and
acidosis resolved.
 Administer Long Acting Insulin as soon as patient is eating.

21. HHNS Management:
 Fluid replacement (1-3L 0.9%sal. 2-3h)
 If serum Na is >150meq/L, use .45%
 When hemodynamically stable, IVF administration directed at
reversing the free H2O deficit.
 Potassium repletion is necessary, depending on serum K
measurements.
 Hypophosphatemia may occur during treatment – give KPO4
 Insulin bolus 0.1u/kg followed by IV insulin @ constant infusion
rate of 0.1 u/kg/hr.
 When plasma glucose falls to 250-300mg/dl, glucose should be
added to IVF and insulin rate decreased to 0.05u/kg/hr.
 Once patient resumes eating – SC insulin regimen
 Patient should be discharged from hospital on insulin.

22. Insulin Therapy
Brands Time
given
Peak Duration
Rapid acting Novolog,
Aspart
Lispro
Given before
or with meals
15 mins prior.
1-3 hours 3-5 hours
Short acting Novolin R Given 30-1 hr.
before meals
2-4 hours 6-8 hours
Intermediate NPH
(Novolin)
Begins to
work 1-2 hrs.
4-12
hours
22-24
hours
Long acting Lantus 4-6 hrs. None 24-36 hrs.
Long acting Levemir 2-8 hrs. Flat peak 24 hrs.
Combinations Novolog
Mix
70/30
Begins to
work 10-
20 mins.
1-12 hrs. 22-24 hrs.

23. DM – Pharmacologic agents
 Biguanides : Metformin
 Sulfonylureas: glyburide, glipizide, glimepiride
 Meglitinide derivatives: repaglinide, nateglinide
 Alpha- glucosidase inhibitors
 Thiazolidinediones (TZDs): pioglitazone (Actos),
rosiglitazone (Avandia)
 Glucagonlike peptide–1 (GLP-1) agonists: exenatide,
liraglutide
 Dipeptidyl peptidase IV (DPP-4) inhibitors: sitagliptin,
saxagliptin, linagliptin
 Amylinomimetics: Pramlintide acetate
 Bile acid sequestrants
 Dopamine agonists: bromocriptine mesylate (Cycloset)

24. Outcome and Follow up Care for this patient:
Goal of therapy in DM are:
 ameliorate symptoms
 reduce micro vascular and macro vascular
complications
 reduce mortality and improve quality of life.
Therapeutic alliance between patient/family/health care
team
Recognize:
Self-management education
Ongoing diabetes support

25. DM and Genomics
Article:
Continuous Subcutaneous Insulin Infusion at 25 years
Evidence base for the expanding use of insulin pump therapy in
type 1 DM
Purpose:
To review the evidence base for the expanding use of CSII, in
the light of its efficacy and possible side effects, and to initiate
a debate about the need for clinical guidelines on the most
suitable patients for pump therapy

26. DM and Genomics
Findings:
 Evidence suggests that hypoglycemia is less common on CSII than injection
therapy
 Frequency of ketoacidosis is decreased with use of CSII, the likelihood of DKA
are attributed to remediable factors: doctor inexperience, use of unbuffered insulin,
breakdown of less reliable pumps, cannula dislodgement and unsuitable patients.
 Dawn phenomena is decreased with CSII.
 Evidence from RCTs indicate large proportion Type 1 subjects, the glycemic
control on CSII is comparable with or only slightly better than that achievable by
intensive insulin injection regimen.
 CSII work efficacious on suitable patients: willingness/able to learn about
undertake pump therapy and its associated procedures such regular monitoring of
blood sugar

27. Diabetes mellitus
Conclusion:
 The evidence base suggests that the expanding use of CSSI is justified.
 The unwillingness to fund pump therapy arises in part from the erroneous belief
that it is indicated for a large proportion of type 1 diabetics, which would open a
floodgate of cost implication. Clinical guidelines for CSII, those who stand to
benefit could be greatly helped at an affordable cost.
 A continued audit of the clinical reasons for starting pump therapy, its metabolic
effectiveness, possible side effects, impact on long-term tissue complications,
quality of life, and patient choice of treatment methods in type 1 DM must still
be sought after.

28. DM and Pharmacogenomics
Article:
Pharmacogenetics of Anti-diabetes Drugs
Purpose:
 To explore the role of causal gene or polymorphism, and its impact on
response to anti-hyperglycemic medications.
 To provide a comprehensive review of pharmacogenetics
investigations of specific anti-diabetes medications namely,
sulfonylureas, biguanides, and thiazolidinedione's.

29. Pharmacogenetic studies ofAnti-Diabetes Drugs
Sulfonylureas
- Agents: Tolbutamide, gliclazide, glibenclamide, and glimepiride
- MODY- arises from mutations in hepatocyte nuclear factor 1 homeobox A gene
(HNF1A)
- Sulfonylureas causes dramatic changes in HbA1clevels
- Mutations in potassium inwardly-rectifying channel, subfamily J, member 11
(KCNJ11) successful with sulfonylureas treatment rather than insulin
- Mutations in ATP-binding cassette, sub family C (CFTR/MRP), member 8 gene
(ABCC8) can be successfully treated with sulfonylureas
- CYP2C19 genotype results to poor metabolism of sulfonylureas
- Other markers:
- Genotype GLy972Arg has high incidence of sulfonylureas therapy failure
- TCF7L2 (alleles at rs12255372 and rs7903146 carriers) sub-optimal response to
sulfonylureas

30. Pharmacogenetic studies ofAnti-Diabetes Drugs
(Biguanides) Metformin
- Ameliorates hyperglycemia by decreasing hepatic glucose output
and GI glucose absorption and improving insulin sensitivity
- Not metabolized, undergoes renal elimination via glomerular
filtration
- Hydrophilic
- OCT1 and OCT2 (solvent carriers)
Genetic variants reducing Metformin activity:
 SLC22A1
 SLCA22A2
 SLC47A1

31. Pharmacogenetic studies ofAnti-Diabetes Drugs
Thiazolidinediones (TZD)
Pioglitazone (Actos) and Rosiglitazone (Avandia)
 Insulin-sensitizing drugs that are agonists for the nuclear receptor proliferator-
activated receptor-y (PPARG).
 Increases insulin sensitivity on adipose tissue and muscle
 3 known variants of PPARG :
PPARG-a, PPARG-y, PPARG2
 PPARG2 is predominant in adipose tissue
 TZD found to be associated with weight gain and edema
 Monotherapy is not recommended in patients at-risk for CHF
 Variation in CYP2C8 gene is associated with pharmacokinetic characteristics
of Avandia- lesser drug clearance rate requiring lower dosage

32. Findings:
 Genetic associations do provide information regarding specific genetic
markers that may be predictive of drug efficacy.
 To date, association studies have not formally assessed specificity or
sensitivity but they do provide some information on the utility of a given
marker as a predictive tool.
 Furthermore, there has not been a study to jointly examine all variants for a
given therapy to assess whether the joint information accounts for a greater
proportion of the variability in drug response compared to the individual
markers alone.
 Prospective studies testing the power of genetic markers to predict drug
response are requisite to fully endorse their introduction into the clinical care
setting.
 Rapid advances in genomic technologies have revolutionized studies of
human genetics. As of this study, 38 loci underlying susceptibility to T2D
have been identified, mostly in populations of northern European ancestry

33. DM and Role of Genomics
Conclusion:
 Pharmacogenetics research provides a means to better understand and
improve on pharmacotherapy.
 Studies have identified several gene variants that are potentially associated
with differential response to anti-diabetes medications; these preliminary
results are promising and warrant investigations in larger, well-designed
cohorts to assess their potential roles in optimal drug selection and
individualized pharmacotherapy in patients with T2D.
 At this time, larger, well-powered studies with clearly defined outcomes and
utilizing a global approach are needed, as they will not only be more
informative than extant candidate gene investigations, but will also be
necessary to define the array of genetic variants that may underlie drug
response. Such results will likely enable achievement of optimal glucose
control, improvement of therapeutic efficacy, and reduction in risk of adverse
drug events in at-risk patients, which together will lead to personalized
treatment strategies for all individuals with T2D.

34. Implications for APN
 Understanding the pharmacogenetics of anti-diabetes medications can provide
critical baseline information for the management of patients with DM.
 Knowledge on the variations of a patient’s genetic make up can help the APN
provide individualized treatment goals for better outcomes.
 Keeping abreast with current genome-wide studies will help enhance the APN
and other disciplines involved in the care of a diabetic patient provide them
with the most effective treatment strategy given their individual background
Continue to provide the following:
 Life style changes counseling
 Referral to education programs
 Strategies to assist with problem solving
 Continual patient education
 Continuing support and encouragement,
 Relapse prevention,
 Ongoing follow-up.

35. DM and Genomics
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 Ahlqvist, E. (2015). The genetics of diabetic complications. Nat Rev Nephrol (6) 121-125.
 Albright, A., Khoury, M., Valdez, R. (2008). Public health genomics approach to diabetes. Diabetes 57:11:2911-2914.
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 Bak, P., Grey, M., Melkus, G., & Whittemore, R. (2003, August 15). Promoting lifestyle change in the prevention and
management of type 2 diabetes. Retrieved from US National Library of Medicine: National Institutes of Health:
http://www.ncbi.nlm.nih.gov/pubmed/14509099
 Dipiro, C. V., Dipiro, J. F., Schwinghammer, T. L., & Wells, B. G. (2012). Pharmacotherapy Handbook (Vol. 8 Edition).
USA: Mc Graw Hill.
 DiStefano, J., Watanabe, R. (2010). Pharmacogenetics of Anti-Diabetes Drugs. Pharmaceuticals Aug 13. doi
10.3390/ph3082610
 Fryhoper, S. (2014). The fight against type 2 DM: the promise of genomics. Retrieved from www.medscape.com
 Griffing, G. T., & Khardori, R. (2012, March 13). Type 2 Diabetes Mellitus Differential Diagnoses. Retrieved from
emedicine.medscape.com: http://emedicine.medscape.com/article/117853-differential
 Hanson, M. (2015). Genetics: Epigenetic mechanisms underlying type 2 diabetes mellitus. Nat Rev Endocrinol (5)261-263
 McCarthy, M. (2010). Genomics, type 2 diabetes, and obesity. N Engl J Med 2010; 363:2339-2350.
 Narayan, N., Weber, K. (2015). Screening for hyperglycemia: the gateway to diabetes prevention and management for all
americans. Annal Intern Med. 162 (11):795-796.
 Sas, K. (2015). Metabolomics and diabetes: analytical and computational approaches. Diabetes 2015 Mar (3) 718-32
 Standards of Medical Care in Diabetes (2013). American Diabetes Association. Retrieved from
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 Wild, R., Roglic, G., Green, A. (2004). Global prevalence of diabetes. Diabetes Care 27:1047-1053