Importance of Attention. The Attention System 7/16/2013

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1 Importance of Attention Preliminary Evidence of an Association Between an IL6 Promoter Polymorphism and Self-Reported Attentional Function in Oncology Patients and Their Family Caregivers John Merriman, MS, RN ICCTF Conference March 16, 2012 Navigating treatment options Maintaining healthy social relationships Accomplishing meaningful goals 2 Cimprich 2011 The Attention System Alerting network vigilance Orienting network selectivity Executive network effortful control attentional fatigue Posner 2012 communication to CNS release of communication CNS to CNS s 1

2 release of diminished i i d communication CNS attentional to CNS s function Purposes 1. Identify latent classes of oncology patients and family caregivers with distinct trajectories of attentional function 2. Determine relationships between participant characteristics, including gene polymorphisms, and latent class membership Design and Methods Descriptive, longitudinal study Participation criteria >18 years of age Able to read, write, and understand English Karnofsky Performance Status (KPS) score >60 Scheduled to receive primary/adjuvant RT or family caregiver No metastases No more than one cancer diagnosis No diagnosed sleep disorders Study Procedures Recruitment at the time of simulation Written informed consent Seven assessments over six months Baseline assessment at simulation The midpoint and endpoint of RT Once a month for an additional four months Attentional Function Index (AFI) 16-item inventory 0-to-10 NRS Total score is the mean of the items Low levels of attentional function <5.0 Moderate levels High levels >7.5 Demonstrated validity and reliability Phenotypic Analyses Growth mixture modeling (GMM) New technique Latent class identification Better phenotyping Cimprich 2011 Muthen

3 n=39 (16%) n=121 (48%) n=92 (37%) Demographic and Clinical Characteristics Age (years) 65 (9) 63 (10) 58 (13) 3 < 1,2 Education (years) 16 (3) 16 (3) 16 (3) n.s. Comorbidities* 4 (2) 5 (3) 5 (3) 3 > 1 KPS score* 96 (9) 94 (10) 88 (14) 3 < 1,2 Female 20 (51) 59 (49) 56 (61) n.s. White 32 (82) 94 (78) 61 (66) n.s. Married/partnered* 33 (85) 87 (73) 54 (59) 3 < 1 Genotypic Data Collection Genotyping GoldenGate genotyping platform Blinded to clinical status 104 SNPs across 15 candidate genes IFNG1, IFNGR1, IL1B, IL1R1, IL2, IL8, IL17A, NFKB1, NFKB2, TNFA, IL1R2, IL4, IL10, IL13, IL6 Haplotypes (SNP combinations) Determined if haplotypes improved strength of association with phenotype Patient* 19 (49) 78 (65) 70 (76) 3 > 1 Genetic Association Analyses Univariate analysis Logistic regression models Only KPS remained a significant phenotypic predictor Controlled for functional status and race/ethnicity If overall model included a significant genotype, pairwise post hoc contrasts of classes n=39 (16%) n=121 (48%) n=92 (37%) 3

4 Genotypic Differences Among Classes Gene SNP MAF Alleles P Model IL4 rs C>T.047 A IL4 rs C>A.013 A IL4 rs C>G.013 A IL4 rs G>A.020 A IL4 HapA IL6 rs G>T.002 D IL6 rs G>C.007 D IL6 rs C>G.010 A IL6 rs G>T.007 D IL6 HapA NFKB2 rs T>G.048 D Genotypic Differences Among Classes Gene SNP MAF Alleles P Model IL4 rs C>T.047 A IL4 rs C>A.013 A IL4 rs C>G.013 A IL4 rs G>A.020 A IL4 HapA IL6 rs G>T.002 D IL6 rs G>C.007 D IL6 rs C>G.010 A IL6 rs G>T.007 D IL6 HapA NFKB2 rs T>G.048 D hoc: High Versus Improving Classes IL6 genotype , KPS , Overall model fit: χ 2 = 25.07, p =.002, R 2 = 0.15 Poor outcomes for carriers of the G allele Associated with elevated levels of IL6 High levels associated with poor outcomes Associated with symptoms of sickness behavior, including difficulty concentrating Protein Data Bank; Spath-Schwalbe, 1998; DeMichele, 2009; Bull, 2009; Hulkkonen, 2001 Research Possibilities Sample size Other physiological pathways Patrick Swift William Wara Brad Aouizerat Kathy Lee Claudia West Imaging Objective tests Chris Miaskowski Marylin Dodd Bruce Cooper Steve Paul Laura Dunn Funding: National Institute of Nursing Research, American Cancer Society, Oncology Nursing Society Posner

5 References 1. Cimprich B, Visovatti M, Ronis DL. The Attentional Function Index-a self-report cognitive measure. Psychooncology. Mar Posner M. Attention in a Social 2. World. New York: Oxford University Press, Ahles TA, Saykin AJ. Candidate mechanisms for chemotherapy-induced cognitive changes. Nat Rev Cancer. Mar 2007;7(3): Haroon E, Raison CL, Miller AH. Psychoneuroimmunology 4. meets neuropsychopharmacology: translational implications of the impact of inflammation on behavior. Neuropsychopharmacology. 2012;37(1): Juster RP, McEwen BS, Lupien SJ. Allostatic load biomarkers of chronic stress and impact on 5. health and cognition. Neurosci Biobehav Rev. Sep 2010;35(1): Muthen, B. (2000). Integrating gperson-centered and variable-centered analyses: GMM with latent trajectory classes. Spath-Schwalbe E, 7. Hansen K, Schmidt F, et al. Acute effects of recombinant human interleukin-6 on endocrine and central nervous sleep functions in healthy men. J Clin Endocrinol Metab. May 1998;83(5): DeMichele A, Gray R, Horn M, et al. Host genetic variants in the interleukin-6 promoter predict 8. poor outcome in patients with estrogen receptor-positive, node-positive breast cancer. Cancer Res. May ;69(10): Bull SJ, Huezo-Diaz P, Binder EB, et al. Functional polymorphisms in the interleukin-6 and 9. serotonin transporter genes, and depression and fatigue induced by interferon-alpha and ribavirin treatment. Molecular psychiatry. Dec 2009;14(12): Hulkkonen J, Pertovaara M, Antonen J, Pasternack A, Hurme M. Elevated interleukin-6 plasma levels are regulated by the promoter region polymorphism of the IL6 gene in primary Sjogren's syndrome and correlate with the clinical manifestations of the disease. Rheumatology (Oxford). Jun 2001;40(6): Posner MI, Rothbart MK, Sheese BE. Attention genes. Dev Sci 2007;10(1): Symptom Characteristics STAI-S 23.9 (5.8) 29.2 (9.6) 36.3 (11.5) 3>2>1 STAI-T 25.6 (5.6) 32.3 (9.0) 40.0 (8.9) 3>2>1 CES-D 3.8 (4.5) 6.7 (6.4) 13.8 (8.9) 3>2>1 GSDS 25.1 (11.1) 37.0 (16.7) 47.1 (19.6) 3>2>1 Evening fatigue 2.8 (2.0) 4.3 (2.0) 4.9 (1.8) 2,3>1 Morning fatigue 1.1 (1.8) 2.0 (1.8) 3.1 (1.8) 3>2>1 AFI score 9.1 (0.7) 7.7 (1.1) 5.7 (1.6) 3<2<1 Pain (% yes) 10 (26) 58 (48) 53 (58) 2,3>1 Symptom Characteristics Symptom Characteristics STAI-S 23.9 (5.8) 29.2 (9.6) 36.3 (11.5) 3>2>1 STAI-T 25.6 (5.6) 32.3 (9.0) 40.0 (8.9) 3>2>1 CES-D 3.8 (4.5) 6.7 (6.4) 13.8 (8.9) 3>2>1 GSDS 25.1 (11.1) 37.0 (16.7) 47.1 (19.6) 3>2>1 Evening fatigue 2.8 (2.0) 4.3 (2.0) 4.9 (1.8) 2,3>1 Morning fatigue 1.1 (1.8) 2.0 (1.8) 3.1 (1.8) 3>2>1 AFI score 9.1 (0.7) 7.7 (1.1) 5.7 (1.6) 3<2<1 Pain (% yes) 10 (26) 58 (48) 53 (58) 2,3>1 STAI-S 23.9 (5.8) 29.2 (9.6) 36.3 (11.5) 3>2>1 STAI-T 25.6 (5.6) 32.3 (9.0) 40.0 (8.9) 3>2>1 CES-D 3.8 (4.5) 6.7 (6.4) 13.8 (8.9) 3>2>1 GSDS 25.1 (11.1) 37.0 (16.7) 47.1 (19.6) 3>2>1 Evening fatigue 2.8 (2.0) 4.3 (2.0) 4.9 (1.8) 2,3>1 Morning fatigue 1.1 (1.8) 2.0 (1.8) 3.1 (1.8) 3>2>1 AFI score 9.1 (0.7) 7.7 (1.1) 5.7 (1.6) 3<2<1 Pain (% yes) 10 (26) 58 (48) 53 (58) 2,3>1 Demographic and Clinical Characteristics Age 65 (9) 63 (10) 58 (13) 3 < 1,2 Education 16 (3) 16 (3) 16 (3) - Comorbidities 4 (2) 5 (3) 5 (3) 3 > 1 KPS score 96 (9) 94 (10) 88 (14) 3 < 1,2 IL6 Haplotype A6 Gene SNP MAF Alleles P Model IL6 rs C>G.010 A IL6 rs T>C.474 A IL6 rs T>G.141 A IL6 rs G>A.141 A IL6 rs C>T.248 A IL6 rs A>G.755 A Female 20 (51) 59 (49) 56 (61) - White 32 (82) 94 (78) 61 (66) - Married/partnered 33 (85) 87 (73) 54 (59) 3 < 1 Patient 19 (49) 78 (65) 70 (76) 3 > 1 5

6 32 IL6 (rs ) - Percent 100 CC CG GG n=18 n=20 n=39 n=53 n=23 n=46 n=33 n=9 GMM Fit Indices GMM LL AIC BIC Entropy VLMR c 1-class n/a n/a 2-class * 3-class * 4-class n=1 High AF Improving AF Moderate AF GMM Parameter Estimates (n=39, 15.5%) Mean (SE) (n=92, 36.5%) Intercept 9.0 (0.1)* 7.5 (0.2)* 5.5 (0.2)* Linear slope 0.2(0.073) 073)* 0.2(0.1) 1)* -0.2(0.1) Quadratic slope (0.01) (0.01)* 0.04 (0.02)* Overall Model IL6 genotype , KPS , Overall model fit: χ 2 = 24.28, p =.002, R 2 = 0.12 Variances Intercept fixed at (0.1) 1.4 (0.3) Linear Slope fixed at 0 fixed at (0.01) 6

7 hoc: High Versus Improving Classes With Age in the Model IL6 genotype , KPS , Age , Overall model fit: χ 2 = 25.95, p =.002, R 2 = 0.15 hoc: High Versus Improving Classes With Race/Ethnicity Shown IL6 genotype , KPS , pc1_ev_ x x x , x pc2_ev_ x x x10-29, 4.20x pc3_ev_ x x x10-36, 3.64x _Iethnicge~ , _Iethnicge~ , _Iethnicge~ , Overall model fit: χ 2 = 25.07, p =.002, R 2 = 0.15 Schematic of IL6 Gene Miaskowski et al. current study Smith et al. Collado-Hidalgo et al. Smith, A. J. P. et al. Clin Chem 2008;54: Copyright 2008 American Association for Clinical Chemistry 7