Dysfunctional Muscle in Aging, Obesity, and Neuromotor Disabilities: The Role of Strength Training to Enhance Health and Human Performance

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2 Dysfunctional Muscle in Aging, Obesity, and Neuromotor Disabilities: The Role of Strength Training to Enhance Health and Human Performance Mark D. Peterson, Ph.D., M.S., FACSM Assistant Professor University of Michigan Health Systems Department of Physical Medicine & Rehabilitation Faculty, Neuroscience Graduate Program

3 Agenda Very Brief Perspective Obesity Prevalence Current Epidemiology and issues with obesity screening The Role of Obesity in Musculoskeletal Dysfunction More than just excess baggage Mediators of Muscle Quality: CP Model Implications for cardiometabolic health risk and muscle dysfunction in aging and obesity Strength Preservation for Health and Function

4 Obesity is a Pandemic: Not new News

5 Simulation Modeling Predictions for 2030 suggest that 50% of the population will be obese Thus accruing an additional 6 8 million cases of diabetes 5 7 million cases of heart disease and stroke >500,000 additional cases of cancer* >50 million forgone QALYs Wang YC, et al. Lancet 2011; 378: *For every 5 kg/m² in BMI increases a man s risk of oesophageal cancer by 52% and for colon cancer by 24%, and in women, endometrial cancer by 59%, gall bladder cancer by 59%, and postmenopausal breast cancer by 12%

6 Body Mass Index (BMI): A Good Proxy for Obesity Body Mass Index = wt/ ht 2 (kg/ m 2 ) Utility of BMI is particularly relevant to Crosssectional research RISK of disease increases when BMI increases But

7 The Problem with BMI What we see on the surface or read from the scale is merely a glimpse of the truth 2 Trendy Terms Normal Weight Obesity Romero-Corral, A., et al., Eur Heart J, Metabolically Healthy Obese Blüher, M, Curr Opin Lipid, 2010

8 Percent Body Fat (%BF) Obesity Misclassification: NHANES :53 Friday, May 17, fatperc 60 Female Male Body Mass Index bmi (kg m -2 ) female 0 1

9 BMI Threshold Sensitivity Specificity Positive Predictive Value Negative Predictive Value Concordance C (AUC) 95% Wald CL (AUC) Men 24 (kg/m 2 ) (0.01) (kg/m 2 ) (0.01) (kg/m 2 )* (0.01) (kg/m 2 ) (0.01) (kg/m 2 ) (0.01) (kg/m 2 ) (0.01) (kg/m 2 ) (0.01) (kg/m 2 ) (0.01) Women 24 (kg/m 2 ) (0.01) (kg/m 2 )* (0.01) (kg/m 2 ) (0.01) (kg/m 2 ) (0.01) (kg/m 2 ) (0.01) (kg/m 2 ) (0.01) (kg/m 2 ) (0.01) (kg/m 2 ) (0.01) *Denotes the best overall threshold for BMI to detect obesity by percent body fat.

10 To Add Confusion: Non-Linear Changes in Muscle Mass with Aging Lexell et al., 1988

11 What about Muscle Quality? 25 Years Old 65 Years Old Goodpaster et al, 2006

12 Not only about age. Children with QCP have more IMAT than typically developing children, and was found to be related to their low level of physical Johnson et al. J Pediatr May;154(5): activity. Separation of AT from MRI of the midthigh of a prepubertal girl with QCP and D-F, a typically developing prepubertal girl. A and D contain subcutaneous, subfascial, and intermuscular AT; B and E contain only subfascial and intermuscular AT; and C and F contain only IMAT.

13 Muscle Attenuation An altered skeletal muscle composition in aging and obese individuals is manifest by a reduced attenuation coefficient on CT (HU) Associated with muscle weakness, a reduced oxidative enzyme capacity, and IR in muscle. *Goodpaster BH et al. J Appl Physiol 2001;90:

14 Standardized Regression Coefficient Adiposity Attenuates MQ In 634 health non-obese individuals, adiposity was negatively associated with MQ Diminished covariance between muscle mass & strength across each higher tertile of adiposity Adiposity mediates the association between mass and function. Males Females Low Fat Medium Fat High Fat Peterson et al. Int J. Obes, 2011.

15 Intermuscular adipose tissue (IMAT) and Intramyocellular Lipid (IMCL) Also develop as a feature of: Disease processes (e.g. DMD, T2DM) Spinal cord injury Sarcopenia ( sarcopenic obesity ) Obesity Prolonged sedentary behavior* *Manini TM, et al. Am J Clin Nutr. 2007; 85(2):

16 My Current Focus: Predictors, Confluence and Consequences of Frailty and Obesity in Cerebral Palsy + Peterson (PI): 1K01HD , R24 HD065702

17 Muscle and Bone Quality in CP a b CT image at L4, depicting trunk adiposity distribution and muscle size in: (a) a 53 year old, typically-developed male (65 kg body mass), and (b) a 54 year old male with CP (66 kg body mass).

18 Muscle Attenuation (IMAT) Adults with CP had significantly less psoas muscle cross-sectional area (β= mm 2, p<0.001) And lower muscle attenuation coefficient (β= , p<0.001) in HU (i.e., lower muscle density)

19 Muscle Attenuation in CP Typically developing, matched controls had significantly higher cortical (β=63.41 HU, p<0.001) and trabecular (β=42.24 HU, p<0.001) BMD Adults with CP had significantly greater VAT (β= mm 2, p<0.001) and SAT (β= mm 2, p<0.001) depots Peterson, M, Zhang, P., et al. Arch Phys Med Rehab. 96(10):

20 Correlation between Psoas density and BMD at L4 Muscle attenuation was significantly correlated with trabecular (r=0.51, p=0.002) and cortical (r=0.46, p=0.006) BMD; Whereas VAT was negatively associated with cortical BMD (β= HU/cm 2 ; r 2 =0.13; p=0.03).

21 Importantly, this is not specific to CP N=4200 Densities of muscles and bones were robustly and inversely associated with visceral adiposity Somewhat contrary to the widely-held belief about BMD and obesity Zhang, P, Peterson, M, et al. Am J Clin Nutr. 101(2):

22 And re-confirmed in a populationrepresentative sample N=5,268 adults with valid body composition and BMD data from DXA, 4 valid days of objectivelymeasured activity, and the necessary blood samples obtained after an overnight fast. Men Model Predictor(s) β SE t Pr > t Women Model Predictor(s) β SE t Pr > t Total Body BMD Lumbar BMD Total Body BMD Intercept <0.001 Intercept <0.001 Age <0.001 Age <0.001 BMI <0.001 BMI <0.001 Android Adiposity (per kg) <0.001 Android Adiposity (per kg) Lumbar BMD Intercept <0.001 Intercept <0.001 Age Age <0.001 BMI <0.001 BMI <0.001 Android Adiposity (per kg) <0.001 Android Adiposity (per kg) Unpublished

23 a b * * * Men * * c d * * * * Women * * * *

24 What is the mechanism? Morphologic and metabolic events of sedentary, obesity, and aging: Storage of adipose tissue (i.e. steatosis ) in liver, muscle, bone Decreased insulin sensitivity, and eventual IR & frank T2DM Chronic and aberrant inflammation Increased mitochondrial oxidative stress Increased formation of the free-radical superoxide (O 2 - ), and subsequent H emission (i.e. ROS) Decreased SM mitochondrial biogenesis and density Decreased or incomplete beta-oxidation = lipotoxicity And Decreased Muscle Regenerative Capacity Decreased Muscle Stem Cell density and myogenic lineage And altered lineage to form fibrocyte/adipocytes

25 Peterson MD et. al.. AJP-Endo Metab (9):E Sedentary Behavior High Fat Diet Aging Diminished Aerobic Capacity Sarcopenia Weakness Physical & Cognitive Frailty Decreased Mitochondrial Density Impaired Myogenesis Functional Deficit Muscular Fibrosis Fatigability Inflammation Cerebral Palsy FRAILTY Chronic Neural Inflammation Exaggerated Sedentary Behavior Abnormal Musculoskeletal Development Muscle Spasticity Oxidative Stress Ceramide Biosynthesis Incomplete beta-oxidation Hypertension Insulin Resistance Dyslipidemia Metabolic Inflexibility Altered Nutrient Partitioning Hyperglycemia Obesity Impaired Insulin Signaling Muscle Pathology and Accelerated Functional Decline Cardiovascular disease and type 2 diabetes

26 And yet The extent to which chronic conditions are a problem in CP, particularly as adolescents transition into and throughout adulthood, is virtually unknown

27 Percent (%) N=1,015 Adults with CP Prevalence of Various Chronic Diseases in CP 45.0% * 40.0% 35.0% 30.0% * * 25.0% 20.0% * * 15.0% 10.0% 5.0% * * * 0.0% Diabetes Asthma Hypertension Other Heart Stroke Emphysema Joint Pain Arthritis Problems Typically Developed 6.3% 9.4% 22.1% 9.1% 2.3% 1.4% 28.0% 17.4% Cerebral Palsy 9.2% 20.7% 30.0% 15.1% 4.6% 3.8% 43.6% 31.4% Peterson, M.D., et al. JAMA. 314(21): , 2015.

28 Other Significant Covariates Additionally: Age (OR: ) Obesity (OR: ) Degree of physical disability (OR: ) Physical inactivity (OR: ) Were each independently associated with greater odds of the 8 chronic diseases

29 We are also interested in implications for healthcare utilization at the population level

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32 Interestingly The presence of a frailty-related PD that accounted for the greatest proportion of increased healthcare utilization Costs associated with frailty-related PDs were >95% higher than non-physically disabled adults, regardless of BMI Whereas costs associated with obesity were only 13% greater than normal weight status, regardless of disability status

33 Healthcare utilization from adults with frailtyrelated PDs + obesity represents ~50% of the total annual medical costs attributed to obesity in the U.S. A staggering finding considering that this subset of individuals corresponds to approximately 7% of the total population. WHY???

34 Individuals with Physical Disabilities Ages 18 to 44 Individuals without Physical Disabilities 100% 80% 60% 40% 20% 0% 100% 80% 60% 40% 20% 0% Ages 45 to % 80% 60% 40% 20% 0% 100% 80% 60% 40% 20% 0% Ages 65 and over 100% 80% 60% 40% 20% 0% 100% 80% 60% 40% 20% 0%

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36 Model of Aging, Weakness, and Disability Threshold

37 The Ever-Changing Definition of Sarcopenia A very clear need to screen for sarcopenia and frailty as risk exposures for incident mobility disability Since 1998, 6 unique clinical approaches have been proposed to establish the diagnosis of sarcopenia in practice

38 Losses greater than 2 SD below the mean for young controls Sarcopenia Normal Men: < 7.26 kg/m 2 Women: < 5.45 kg/m 2-2 SD Mean Appendicular Skeletal Muscle (kg/m 2 ) Baumgartner R, Am J Epidemiol 1998

39 Using this classification of Muscle Mass: 10-20% of elderly between 60 and 70 years has sarcopenia 30% - 45% of persons in their 80s may be classified as sarcopenic Baumgartner R, Am J Epidemiol 1998

40 New/Improved Diagnostic Criteria In 2010 the European Working Group on Sarcopenia in Older People (EWGSOP) recommended a diagnosis of sarcopenia to occur with presentation of at least 2 out of 3: Low Muscle Mass, and Low Muscle Strength -or- Low Physical Performance Sarcopenia is akin to a syndrome with a risk of adverse outcomes such as physical disability, poor quality of life and death

41 EWGSOP Comments: The rationale for use of two criteria is: Muscle strength does not depend solely on muscle mass, and the relationship between strength and mass is not linear. Thus, defining sarcopenia only in terms of muscle mass is too narrow and may be of limited clinical value.

42 The three most recent definitions of sarcopenia are characterized by different easy-to-measure functional tool (gait speed and/or handgrip strength with a different cut-off) in addition to muscle mass (with a different cut-off). Dupuy, C., et al. J Cach, Sarc, & Muscle. 2015, 6 (2):

43 The estimated prevalence of sarcopenia ranged from %. Only 85 participants (3.1%) were identified as having sarcopenia according to all definitions.

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45 FNIH Criteria Weakness: defined as low grip strength (<26 kg for men and <16 kg for women) Low lean mass (from DXA): categorized as low appendicular lean mass (ALM; <19.75 kg for men and <15.02 kg for women) And/or low ALM-to-BMI ratio (<0.789 men and <0.512 women). Limitations: Primarily all white, clinical population

46 So How Much Muscular Fitness is Enough?

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48 Does body mass mediate the association between strength and function/health?

49 The weaker an individual is relative to their body mass, the less efficient he/she would be in lifting and maneuvering that mass through space

50 Moreover, since relative load dictates fiber recruitment pattern Two Problems with Sarcopenic/Dynapenic individuals 1. Body Mass is heavy Type II fiber needed 2. Etiology: Type II fiber denervation

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52 Baseline Age N=1958 Age: years Age: 75 years Sex p<0.001 Sex p<0.001 Men Women Men Women Grip Strength p<0.001 Grip Strength p<0.001 NGS 0.22 NGS >0.22 NGS 0.37 NGS >0.37 N=542 Median Survival: 11.9 Years N=129 Median Survival: 11.9 Years N=593 Median Survival: 16.7 Years N=142 Median Survival: 5.8 Years N=146 Median Survival: 7.4 Years N=406 Median Survival: 8.3 Years

53 Men Model Predictor(s) Hazard Ratio 95% CIs p-value Mortality Age (years) <0.001 Married Stratified joint Baseline Disability modeling Status (Reference: of No survival Disabilities) and longitudinal analysis for Baseline Diabetes Status (Reference: men No Diabetes) and women <0.001 Education Normalized Grip Strength 1.15* ** The effects of baseline covariates (i.e., age, marital status, disability, etc.) and time-dependent covariate (NGS) *HR for every 0.10 incremental decrease in NGS. **95% CIs for every 0.10 incremental decrease in NGS. Women Mortality Model Predictor(s) *HR for every 0.10 incremental decrease in NGS. **95% CIs for every 0.10 incremental decrease in NGS. Hazard Ratio 95% CIs p-value Age (years) <0.001 Married Baseline Disability Status (Reference: No Disabilities) <0.001 Baseline Diabetes Status (Reference: No Diabetes) <0.001 Education Normalized Grip Strength 1.12* ** 0.04

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55 U.S.: NGS and Diabetes in Adults HbA1c levels ( 6.5% [ 48 mmol/mol])

56 Men N=766 Prevalence Diabetes: 33.0%, p=0.002 Women N=1,075 Prevalence Diabetes: 38.3%, p<0.001 NGS 0.46 NGS >0.46 NGS 0.30 NGS >0.30 N=433 Prevalence Diabetes: 39.3% N=333 Prevalence Diabetes: 25.3% N=414 Prevalence Diabetes: 51.0% N=661 Prevalence Diabetes: 31.5% WEAK STRONG WEAK STRONG

57 Weakness in the MHAS Weakness among older Mexicans was associated with significantly increased odds of diabetes (OR: 1.69, 95%CI: ), even after adjusting for age, sex, and waist circumference. Weak individuals also had a significantly higher prevalence of obesity and abdominal obesity (both men and women), vitamin D deficiency (women only), elevated CRP (both men and women), and hypertension (women only) (all p<0.01).

58 How early should we begin thinking about this?

59 MetScore MetScore Strength and MetS in adolescents a b Normalized Grip Strength Normalized Grip Strength Peterson, MD, et al. Pediatrics, 133(4): e896 e903, 2014.

60 Weakness and Cardiometabolic Risk in Adolescents Conditional tree analysis revealed a high-risk threshold for boys ( 0.33) and girls ( 0.28), as well as an intermediate risk threshold (boys: >0.33 and 0.45; girls: >0.28 and 0.36). Boys N=630 Prevalence High- Risk Phenotype: 24.9%, p<0.001 Girls N=696 Prevalence High- Risk Phenotype: 25.0%, p<0.001 NGS 0.33 NGS >0.33 NGS 0.36 NGS >36 N=527 p<0.001 N=258 P=0.02 NGS 0.45 NGS >0.45 NGS 0.28 NGS >0.28 N=103 Prevalence High- Risk Phenotype: 57% N=262 Prevalence High- Risk Phenotype: 24% N=265 Prevalence High- Risk Phenotype: 12% N=72 Prevalence High- Risk Phenotype: 63% N=186 Prevalence High- Risk Phenotype: 38% N=438 Prevalence High- Risk Phenotype: 16% WEAK INTERMEDIATE STRONG WEAK INTERMEDIATE STRONG

61 Among the weakest adolescents, 57% and 63% had the high-risk cardiometabolic phenotype, as compared to 24% and 38% with intermediate strength, and 12% and 16% with the highest normalized strength, for boys and girls respectively. Peterson et. al. Am J Prev Medicine. 50(5): 593-9, 2016

62 Growth Charts for Muscular Strength Capacity with Quantile Regression. Peterson and Krishnan. Am J Prev Med. 49(6):

63 Women Age 5th Percentile 10th Percentile 25th Percentile 50th Percentile 75th Percentile 90th Percentile 95th Percentile 6 years years years years years years years years years years years years years years years years years years years years

64 Men Age 5th Percentile 10th Percentile 25th Percentile 50th Percentile 75th Percentile 90th Percentile 95th Percentile 6 years years years years years years years years years years years years years years years years years years years years

65 Summary Obesity and related cardiometabolic diseases are increasing in prevalence across populations Adipose tissue has a local negative influence of musculoskeletal integrity and functional capacity Neuromuscular populations and persons with physical disabilities are at heightened risk due to exaggerated sedentary behaviors, and risk for normal weight obesity and chronic disease Muscular strength preservation is important for metabolic health and function through the lifespan.

66 Acknowledgments Dr. Edward Hurvitz (UM) Dr. Charles Burant (UM) Dr. Peng Zhang (UM) Dr. Soham Al Snih (UTMB) Dr. Ken Ottenbacher (UTMB) Dr. Kyriakos S. Markides (UTMB) Dr. Brent Alvar (RMU) Dr. William Kraemer (Uconn) Dr. Jeff Horowitz (UM) Dr. James McClain (NIH) Dr. I-Min Lee (Harvard)

67 Thank you!

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