1. #AIDS2016 | @AIDS_conference When Genes and ART Collide: Modifying Effect of ARVs on Genetic Predisposition to Diabetes Melissa A. Frasco, Ph.D. Research Epidemiologist

2. #AIDS2016 | @AIDS_conference Agenda Background on diabetes in the HIV population Interaction between diabetes genetic markers and ART Application to treatment guidelines

3. #AIDS2016 | @AIDS_conference Agenda Background on diabetes in the HIV population Interaction between diabetes genetic markers and ART Application to treatment guidelines

4. #AIDS2016 | @AIDS_conference Risk Factors for Diabetes in HIV Untreated HIV infection may lead to – dyslipidemia – lipodystrophy – insulin resistance – metabolic syndrome Antiretroviral drugs (ARVs) appear to be implicated in risk of type 2 diabetes mellitus (DM)

5. #AIDS2016 | @AIDS_conference ART-Associated Diabetes Two out of three drugs classes used in combination ART increase risk of DM Protease inhibitors (PI) – Confer acute metabolic risks – Metabolic effect varies by individual drug Nucleoside reverse transcriptase inhibitors (NRTI) – Confer cumulative risk of diabetes – Stauvudine, zidovudine and didanoside

6. #AIDS2016 | @AIDS_conference Genetic Predisposition to Diabetes Genome-Wide Association Studies (GWAS) have identified genetic markers for DM – European, Asian, and Hispanic populations Replication of genetic markers have been challenging in African ancestral populations – DM incidence higher in African ancestry

7. #AIDS2016 | @AIDS_conference Agenda Background on diabetes in the HIV population Interaction between diabetes genetic markers and ART Application to treatment guidelines

8. #AIDS2016 | @AIDS_conference Objective Hypothesis: We hypothesize that NRTI/PI treatment modifies the effect DM risk variants in HIV-infected women. Objective: To evaluate the association of confirmed DM risk variants in a population of HIV-infected women with consideration for the effect of combination antiretroviral therapy (cART) regimen. To evaluate the association of confirmed DM genetic markers in HIV-infected women with consideration for the effect of ART regimen

9. #AIDS2016 | @AIDS_conference Methods Study population: Women’s Interagency HIV Study (WIHS) participants with fasting glucose & HgbA1C measurements Study design – prospective cohort study with visits every 6 months – followed for DM incidence or end of study (50 DM / 2,957 PY) – maximum follow-up was 10.4 years Exposure: 17 DM genetic markers Modifying factor: type of ART regimen

10. #AIDS2016 | @AIDS_conference GenePolymorphism Risk Allele Meta-OR European GWAS * p-value CDKAL1rs7754840C 1.164.58 x 10 -19 CDKN2A/Brs564398T 1.185.37 x 10 -21 CDKN2A/Brs10811661T 1.194.83 x 10 -16 FTOrs8050136A 1.061.76 x 10 -4 HHEXrs7923837G 1.122.68 x 10 -14 IGF2BP2rs1470579C 1.149.19 x 10 -16 IGF2BP2rs4402960T -- JAZF1rs864745T 1.112.22 x 10 -9 KCNQ1rs2237895C -- *Saxena, 2012 Confirmed DM Genetic Markers

11. #AIDS2016 | @AIDS_conference Results in Non-African Americans Cox regression adjusted for time-dependent BMI category, age, and genetic ancestry principal components, using calendar year as the time scale to control for drug utilization trends

12. #AIDS2016 | @AIDS_conference Results in non-African Americans ART regimens All Subjects 50 DM / 2,957 PY No Treatment 11 DM / 779 PY 2 NRTI + NNRTI † 6 DM / 845 PY ≥3 NRTI (non-PI) † 7 DM / 250 PY ≥2 NRTI + ≥1 PI 26 DM / 1,083 PY SNPHR95%CIHR95% CIHR95% CIHR95% CIHR95% CI rs7754840 1.21(0.80-1.84)0.94(0.46-1.93)0.36(0.09-1.40)1.29(0.44-3.79)1.77(1.12-2.80) rs564398 1.25(0.77-2.04)0.88(0.47-1.65)0.76(0.37-1.53)1.39(0.70-2.76)1.69(1.02-2.79) rs10811661 1.72(0.89-3.34)1.35(0.65-2.80)1.11(0.50-2.49)2.07(0.95-4.50)2.09(1.07-4.09) rs8050136 1.24(0.83-1.84)0.88(0.45-1.75)0.68(0.29-1.61)2.14(1.04-4.39)1.50(0.96-2.32) rs7923837 1.21(0.78-1.89)1.03(0.59-1.81)0.76(0.38-1.52)1.70(0.88-3.29)1.50(0.94-2.40) rs1470579 1.84(1.19-2.86)1.00(0.45-2.20)1.02(0.45-2.32)3.05(1.47-6.35)2.66(1.65-4.31) rs4402960 1.85(1.21-2.85)1.04(0.47-2.34)1.11(0.49-2.48)2.94(1.44-6.01)2.63(1.61-4.30) rs864745 1.09(0.70-1.69)0.92(0.51-1.66)0.61(0.28-1.31)1.37(0.66-2.82)1.39(0.87-2.24) rs2237895 0.93(0.62-1.39)0.80(0.41-1.57)0.37(0.13-1.07)1.04(0.43-2.52)1.25(0.80-1.94) Cox regression adjusted for time-dependent BMI category, age, and genetic ancestry principal components, using calendar year as the time scale to control for drug utilization trends

13. #AIDS2016 | @AIDS_conference Results Summary The risk of DM is substantial in genetically predisposed individuals who are taking PI-based regimens or NRTI-heavy regimens 10 of the 17 genetic markers tested showed statistically significant heterogeneity in genetic-DM associations across ART regimens No associations were observed in African American women with these DM genetic markers IGF2BP2 rs1470579 was the top association  HR per allele = 2.66 (95% CI 1.65-4.31) in women taking ≥2 NRTIs + ≥1 PI regimens  HR per allele = 3.05 (95% CI 1.47-6.35) in women taking ≥3 NRTIs (no PI) regimens  p het =2.92 x 10 -3 across ART regimens

14. #AIDS2016 | @AIDS_conference Conclusion Preferential treatment with non-PI regimens for HIV-infected persons carrying DM genetic markers Studies needed to replicate the interaction between ART and DM genetic markers found in African ancestral populations

15. #AIDS2016 | @AIDS_conference Agenda Background on diabetes in the HIV population Interaction between diabetes genetic markers and ART Application to treatment guidelines

16. #AIDS2016 | @AIDS_conference Application to Treatment Guidelines 1 st line ART = 2 NRTIs + NNRTI 2 nd and 3 rd line include PI + ≥2 NRTI – risk for development of DM is amplified in populations predisposed to diabetes – implement routine screening for DM