Serum chronicity markers as surrogate measures of frailty A. Pattisapu1,2, S. Leng2, N. Fedarko2, A. Jain2 Northeast Ohio Medical University, Rootstown, OH 2. Division of Geriatric Medicine and Gerontology, Johns Hopkins University, Baltimore, MD

Disclosure Statement The research reported on this poster was supported by NIA, NCRR & AFAR. The investigators retained full independence in the conduct of this research.

What is frailty?

Frailty Geriatric syndrome characterized by: Weight loss, exhaustion, slowness, low activity level, weakness Age-related, biological vulnerability decreased physiological reserves increased risk of disability & mortality Associated with immune dysregulation and chronic disease

Biomarkers Chitotriosidase (ChT) – produced by chronically activated macrophages Interleukin-6 (IL6) – pro-inflammatory cytokine Neopterin (NEO) – metabolite produced by macrophages during chronic disease/viral infection

Objective Biomarkers – IL6, ChT, NEO – reflecting different aspects of immune activation in response to chronic inflammation were assessed separately and together for their discriminatory ability between frail and nonfrail older individuals.

Methods Sera analyzed for ChT by enzyme activity assay, and NEO and IL6 levels by ELISA Diagnosis of frailty determined using the Fried criteria of at least 3 symptoms (out of: weight loss, exhaustion, slowness, low activity level, and weakness) Diagnostic capacity of the serum markers assessed by logistic regression with covariates including age, race, BMI and sex and by Receiver Operating Characteristic (ROC) analysis

Study Group Characteristics n 397 % African American 10% % Female 57% age, mean ± SD 58 ± 24 % > 70 years of age 38% BMI, mean ± SD 26.7 ± 6.8

Segregation by age group and frailty status Results Segregation by age group and frailty status   < 70 years  > 70 years Status Non-frail Frail p value n 246 104 47 age (years) 44 ± 13 82 ± 6 84 ± 4 - BMI (kg/m2) 27.5 ± 7.2 24.6 ± 3.4 25.5 ± 6.3 ChT 0.75 (0.05 - 7.57 4.19 (0.28 - 21.42) 11.07 (1.47 - 67.77) < 0.0001 IL6 1.36 (0.35 - 4.78) 1.66 (0.44 - 9.19) 2.27 (0.64 - 8.49) NEO 5.85 (2.59 - 10.93) 7.96 (5.37 - 13.43) 9.41 (5.53 - 36.12) Covariates ChT, IL6 and NEO each associated separately with frailty without controlling for other serum markers.

Results Frailty status

Results Table 2: Logistic Model Coefficients Table for Frailty Status: Modeling frailty with all biomarkers yielded only ChT and NEO as independently associating with an increase in the odds of frailty: ChT odds = 1.21(1.12-1.31), p<0.0001; neopterin odds = 1.40(1.13-1.74), p<0.005 (Table 2).

ROC Analysis Usig all 3 markers, a randomly selected frail subject is 86% more likely to have a higher test result than a randomly selected normal subject The AUC represents the probability that a randomly selected frail subject will have a higher test result than a randomly selected normal subject

Area under curve by ROC curve analysis of non-frail versus frail was 0.70 ± 0.05 for NEO, 0.66 ± 0.05 for IL6, 0.81 ± 0.04 for ChT, 0.86 ± 0.03 for all three markers combined. At a composite (all 3 markers combined linearly) cut-off value of 19.0, the likelihood ratio equals 5.5. At this cut-off, sensitivity was 75% and specificity was 87%.

Conclusion In adults 70 years and above, a one unit increase in ChT showed a 21.3% increase in odds of frailty A one unit increase in neopterin showed a 40.0% increase in odds of frailty.

Composites of biomarkers provide the greatest discriminatory capacity. These results suggest that the use of composites of surrogate chronicity markers may have utility in identifying frailty in older adults.

Limitations Relatively small sample size Biomarker levels influenced by many components/events Capacity to distinguish frailty from other chronic illnesses/syndromes unknown

Implications Further studies to validate marker utility will involve application of optimal marker cut-off values to a distinct, naive study population.

Acknowledgements Funding has been provided by the American Federation for Aging Research (AFAR) and National Institute of Aging (NIA) through the MSTAR Program and support from Johns Hopkins University. I would also like to thank the Jerry Kowal Student Scholarship Fund provided by the Ohio Geriatrics Society.

Contact Anish Pattisapu Email: apattisapu@neomed.edu