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Improving Health with Aging, by Sara Espinoza, MD, M.Sc.

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Dr. Sara Espinoza's presentation from Texas Public Radio's Think Science event, held on Friday, August 16, 2019.

Published in: Health & Medicine
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Improving Health with Aging, by Sara Espinoza, MD, M.Sc.

  1. 1. Clinical Research to Improve Health with Aging Sara E. Espinoza, MD, MSc Associate Professor, Department of Medicine Sam and Ann Barshop Institute for Longevity & Aging Studies
  2. 2. Aging in the U.S. U.S. Census Bureau
  3. 3. Aging is Unique for Every Person • Aging is a spectrum, and individualized – Environmental – Genetic • Unfortunately, many older adults will – Be frail – Have multiple chronic diseases – Become disabled • Goal is to prevent or delay if possible and do what we can to enhance quality of life for all adults as they age
  4. 4. “Healthy Aging” • Minimize the number of years with: –Disease –Disability –Depending on others • Want to be active and independent for as long as possible
  5. 5. Heterogeneity with Aging Independent Dependent Few health problems, active and robust Some health problems Multiple medical problems Frail, vulnerable J Walston
  6. 6. How important is aging? Smoking Alcohol Diet Infection PercentIncrease 0 10 20 30 40 Risk Factors for Cancer
  7. 7. Aging overwhelms all other risk factors for Cancer Smoking Alcohol Diet Infection Aging PercentIncrease 0 1000 2000 3000 4000 5000 6000
  8. 8. Aging as a therapeutic target AGINGStroke Arthritis Sarcopenia Heart Disease Type II Diabetes Cancer Neurodegenerative diseases (Alzheimer’s, Parkinson’s, ALS) Osteoporosis Adapted from: Biochim. Biophys. Acta (2009) 1790: 1067-1074.
  9. 9. The Barshop Institute Mission • To understand the basic biology of aging • To discover the therapies that will treat diseases of aging • To educate and train our future scientists and clinicians • To promote public awareness of age-related issues
  10. 10. Clinical Studies • UT Health Science Center and the SA GRECC partner to conduct clinical research trials • These studies help further the medical knowledge of specific treatments and preventions of various age-related diseases • Participants can help make a difference in the care and treatment of future patients
  11. 11. Barshop Institute Clinical Studies CURRENTLY RECRUITING: • Cognitive improvement • Healthy eating and physical activity • Improving the immune system • Loss of muscle & strength • Metformin for the prevention of frailty • South Texas Aging Registry & Repository COMING SOON: • MOTRPAC – Exercise The Molecular Transducers of Physical Activity Consortium
  12. 12. Barshop Institute Clinical Studies COMPLETED: • Aspirin for the prevention of events in the elderly • Effect of rapamycin on clinical outcomes, function and cognition • Healthy weight • Effect of Microbiome on Metabolism • Mild cognitive impairment • Sarcopenic obesity • Senolytics for older patients with IPF
  13. 13. Metformin for Frailty Prevention in Older Adults with Pre-Diabetes
  14. 14. Age-adjusted Prevalence of Obesity and Diagnosed Diabetes Among US Adults Obesity (BMI ≥30 kg/m2) Diabetes 1994 1994 2000 2000 No Data <14.0% 14.0%–17.9% 18.0%–21.9% 22.0%–25.9% > 26.0% No Data <4.5% 4.5%–5.9% 6.0%–7.4% 7.5%–8.9% >9.0% CDC’s Division of Diabetes Translation. United States Surveillance System available at http://www.cdc.gov/diabetes/data 2015 2015
  15. 15. Source: NIDDK, Diabetes in America, 3rd edition; niddk.nih.gov
  16. 16. Aging Consequences of Diabetes • Diabetic sequelae − Microvascular: Renal, eye, − Macrovascular: heart disease, stroke, peripheral vascular disease − Peripheral neuropathy • Cognitive impairment & Dementia • Poor muscle strength/quality − Disability − Frailty
  17. 17. Frailty • Clinical, geriatric syndrome • Poor tolerance to stressors • Vulnerable to decline • At risk population for poor outcomes –Falls, hospitalization, disability, death
  18. 18. Fried Model • Weight loss • Exhaustion • Low physical activity • Weak hand grip • Slow walking speed Fried LP, Tangen CM, Walston J. J Geron Med Sci 56:M146-M157 (2001) Trichotomous: 0=Not frail, 1 or2 = Pre-Frail, 3 or more=Frail Dichotomous: < 3 = Not frail, 3 or more= Frail Cardiovascular Health Study, N = 5,317
  19. 19. SALSA - San Antonio Longitudinal Study of Aging • Longitudinal, observational study • Baseline Exam (1992-96) & 3 Follow-up Exams (2000-05) – Comprehensive assessment of the disablement process – Frailty classified using Fried criteria • Original cohort characteristics: – Unique, bi-ethnic: 394 MAs, 355 EAs – Sociocultural variation among the MAs
  20. 20. Frailty is Associated with Obesity and Diabetes in SALSA Diabetes defined by ADA criteria: fasting blood glucose ≥126 mg/dL and/or taking glucose lowering medications N = 671 Non-frail N = 249 Pre-frail N = 356 Frail N = 66 P- value BMI, kg/m2 27.6 ±4.2 28.7 ±5.6 30.1 ±6.8 .0018 Waist circumference, cm 97.5 ±11.7 99.8 ±14.3 104.3 ±16 .0013 N (%) N (%) N (%) Diabetes 29 (12.7) 77 (24.3) 27 (44.3) <.001
  21. 21. Diabetes Predicts Onset of any One Frailty Characteristic Covariate OR (95% CI) P-value Diabetes 2.15 (1.18-3.94) 0.01 Ethnicity (MA vs. EA) 0.66 (0.38-1.13) 0.13 Age (1-year increments) 1.07 (1-1.14) 0.06 Sex (male vs. female) 3.38 (2.07-5.52) <0.001 Income (1-category increment) 0.87 (0.79-0.96) 0.006 Education (1-category increment) 1.02 (0.96-1.09) 0.53 Comorbidity (not including diabetes) 1.3 (0.83-2.05) 0.26 Using GEE analysis, average follow-up of 6.5 years. N=466 Espinoza, Jung & Hazuda, JAGS, 2012
  22. 22. Insulin Resistance & Inflammation Predict Frailty Frailty HR (95% CI) IR-HOMA 1.15 (1.02-1.31) Metabolic Syndrome 1.05 (0.92-1.19) CRP 1.16 (1.02-1.32) Barzilay et al., Arch Intern Med, 2007 Multivariable analysis adjusting for age, sex, smoking, SES, BMI, depression, cognition, incident diabetes, heart disease, stroke, and cancer. N = 2,826 ~10 yr f/u IR-HOMA: insulin sensitivity based on fasting insulin and glucose levels using nonlinear statistical modeling Cardiovascular Health Study
  23. 23. Glycoprotein Biomarkers 0 10 20 30 40 50 60 70 80 90 100 Non-frail Pre-frail Frail FibrinogenConc.g/L Frailty category Plasma Fibrinogen P < .0001 0 10 20 30 40 50 60 70 80 Non-frail Pre-frail Frail Transferrinconc.ng/ml Frailty category Plasma Transferrin P < .001 N = 65 Remained significant after age and sex adjustment Haptoglobin did not significantly differ by frailty Darvin et al., J Geron Biol Sci, 2013
  24. 24. Conceptual Model/Rationale Insulin Resistance Aging & Obesity Inflammation MetforminMetformin Frailty
  25. 25. Inclusion Criteria • Age 65+ • Non-frail or Pre-frail • Community-dwelling • Impaired glucose tolerant (OGTT)* Exclusion Criteria • Chronic disabling neurologic, heart, pulmonary, rheumatologic disease * 2 hour values of 140- 199 mg/dL Study Design Screening Frailty Status OGTT Eligibility Baseline Measures Insulin Sensitivity Inflammation Randomize Follow 2 years Metformin Placebo
  26. 26. Outcomes Primary Outcomes Frailty Category Frailty Score Secondary Outcomes Gait speed, Grip Strength, SPPB Systemic inflammation IL-6, CRP, TNFα, IL-1RA, TNFs R1 and 2, fibrinogen, transferrin Muscle Inflammation IL-1β, IL-6, MCP-1, and TNFα mRNA; MAPK & NFκB activation Muscle Insulin Signaling AMPK and ACC phosphorylation, PGC-1α expression, and insulin (IRS-1, Akt , AS160, mTOR and S6K) signaling Body composition DEXA Glucose Tolerance & Insulin Sensitivity OGTT, Insulin clamp
  27. 27. Metformin for Frailty Prevention • Metformin targets underlying mechanisms of frailty • The results of this trial may lead to a novel way to prevent frailty • Positive results will have major implications for clinical frailty screening and early intervention
  28. 28. Thank You, Questions? Acknowledgements San Antonio Pepper Center San Antonio Nathan Shock Center Robert Wood Johnson Foundation NIH, 1KL2RR025766-01 (San Antonio CTSA) VISN 17 New Investigator Award San Antonio Area Foundation Research Support:

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