Supplemental Materials

White matter hyperintensities in former American football players

Michael L. Alosco, PhD,¹ Yorghos Tripodis, PhD, ^2,3 Zachary H. Baucom, MA,³

Charles H. Adler, MD, PhD,⁴ Laura J. Balcer, MD, MSCE,⁵ Charles Bernick, MD,^6,7

Megan L. Mariani, MPH,² Rhoda Au, PhD,^1,8-11 Sarah J. Banks, PhD,¹²

William B. Barr, PhD,¹³ Jennifer V. Wethe, PhD,¹⁴ Robert C. Cantu, MD,¹

Michael J. Coleman, MA,¹⁵ David W. Dodick, MD,⁴ Michael D. McClean, ScD,¹⁶

Ann C. McKee, MD,^1,17 Jesse Mez, MD, MS,^1,8 Joseph N. Palmisano, MA, MPH,¹⁸

Brett Martin, MS,¹⁸ Kaitlin Hartlage, MPH,¹⁸ Alexander P. Lin, PhD,^15,19

Inga K. Koerte, MD, PhD,^15,20 Jeffrey L. Cummings, MD, ScD,²¹

Eric M. Reiman, MD,²² Robert A. Stern, PhD,^1,10,23 Martha E. Shenton, PhD,^15,24

Sylvain Bouix, PhD¹⁵

Appendix A: Methods

A.1. Overview of Inclusion and Exclusion Criteria

The DIAGNOSE CTE Research Project enrolled 120 former professional football players, 60 former collegiate football players, and 60 asymptomatic men without RHI/TBI; all men between 45-74 years. The sample sizes were determined to assure adequate statistical power to detect moderate effect sizes at a significance level of 0.05 for all hypotheses of the DIAGNOSE CTE Research Project [1]. Inclusion and exclusion criteria included no contraindications for MRI, lumbar puncture, or PET procedures; English as primary language; agreeing to all study procedures; and had an available informant to respond to questionnaires. The former college football players must have played >6 years of organized American football with >3 years at the college level. Former professional American football players must have played ≥12 years of organized football, including >3 in college and >4 seasons in the NFL. The two groups of former American football players spanned the symptom continuum, from asymptomatic to significant cognitive and/or neuropsychiatric impairment. The asymptomatic unexposed group must have had: no history of diagnosed TBI (of any severity); no previous participation in organized contact sports; no military combat history; no reported formal diagnosis or treatment of psychiatric illness or cognitive impairment; no self-reported cognitive, behavioral or mood symptoms at study screening; and a body mass index (BMI) >24. All participants were required to have an informant and adequate decisional capacity at the time of their baseline visit to participate.

A.2. Magnetic Resonance Imaging Acquisition and Quality Control

Participants were evaluated at one of four U.S. sites, including Boston University School of Medicine (MRI conducted at Brigham and Women’s Hospital), Cleveland Clinic Lou Ruvo Center for Brain Health in Las Vegas, Mayo Clinic Arizona, or NYU Langone Medical Center. MRIs across the four sites were all conducted using the same 3T MRI model (MAGNETOM Skyra, Siemens Healthineers, Erlangen, Germany). Imaging calibration and quality control procedures were completed for all sites. Four human subjects were scanned with the complete protocol at each site in the beginning of the study and two were scanned each year. MRI quality control was conducted on these human subjects to confirm consistency of acquisition parameters, signal-to-noise and contrast-to-noise ratio across modalities, and geometric features of images across scanners. Each scan was visually assessed for artifact based on standard operating procedures developed by the Psychiatry Neuroimaging Laboratory at Brigham and Women’s Hospital.

A.3. Tobit Regression Model Description

Because log-WMH values clustered at the lower end of the distribution, tobit regression analyses were used when WMH served as the outcome. A tobit model is a form of censored regression that is used to estimate linear associations between variables when there is left or right censoring (i.e., positive or negative skew) of the data [2,3]. For example, in this sample, the distribution of WMH was positively skewed, clustering toward the zero-end. The tobit regression down weights the impact of these individuals.

A.4. Post-Hoc Statistical Analyses: Tobit Regressions Among those with Intact Trail Making Test Part B Score

Former American football players spanned the continuum of symptomatic status upon study entry whereas the unexposed men were required to be asymptomatic. Differences in symptomatic status could contribute to increased burden of WMH being observed in the former American football players. To determine whether the symptomatic former football players accounted for effects observed, we repeated the primary tobit regression models (including stratified by age 60) after restricting the sample to those who had intact executive functions as defined by Trail Making Test Part B T-score >35. Note that Trails A-B served as a primary outcome, but could not be used here due to absence of T-scores to define impairment for this derived metric. Trail Making Test Part B was selected because executive function deficits are hallmark consequences of cerebrovascular disease and the literature has directly linked FLAIR WMH and worse performance on Trail Making Test Part B [4-8]. Executive function is also a core domain affected by exposure to RHI [9]. After restricting the sample to those who had intact performance on Trail Making Test Part B, it resulted in 116 former American football players and 49 asymptomatic unexposed men. Results of this sensitivity analysis are presented in Table A.4.

Figure A.1. Flow Diagram of Sample Size Derivation

Figure A.2. Distributions of Total and Regional Volume of Log-Transformed White Matter Hyperintensities in Former American Football Players and Same-Age Asymptomatic Unexposed Men. The distribution of total WMH was positively skewed and four participants had zero values; this was more pronounced for frontal, temporal, parietal, and occipital WMH. Total and regional WMH were natural log-transformed. Zero values were replaced with the minimum non-zero WMH value minus 0.01 so a log-transformation could be applied across the entire data set Negative values are present for total log-WMH because there were raw values between 0 and 1. For frontal, temporal, parietal and occipital WMH, the minimum non-transformed raw value was 0.99 (these were the zero values replace by 1 – 0.01), resulting in a minimum log-WMH of -0.01 and the histograms show this to be at or near 0.

Figure A.3. Association Between Age and Log-Transformed Total White Matter Hyperintensities. There was a statistically significant association between older age and greater log-transformed total white matter hyperintensities in the entire sample (r = 0.50, p < 0.01), in the former American football players (r = 0.54, p < 0.01), and in the unexposed participants (r = 0.44, p < 0.01).

Table A.1. Lobe Mapping for White Matter Hyperintensity Composites

Note. Volume of white matter hyperintensities (WMH) in the frontal, temporal, parietal and occipital lobes were computed. Lobe composites were computed by calculating the summary of WMH in white matter regions in both hemispheres that comprise their respective lobe based on FreeSurfer cortical parcellation recommendations for lobe mapping (https://surfer.nmr.mgh.harvard.edu/fswiki/CorticalParcellation).

Table A.2. Neuropsychological and Neuropsychiatric Status of the Sample

Statistical tests that compare the groups on these measures were not performed because the recruitment of participants for the DIAGNOSE CTE research project was based on our primary risk factor of interest (i.e., elite football play) and symptoms (i.e., unexposed men must have been asymptomatic). This recruitment strategy was appropriately designed for biomarker development and validation. However, it becomes problematic when clinical measures are outcomes as estimates of group differences would be magnified. N = 139 for all measures with the exception of Stroop Color-Word Interference (n = 137 due to missing data). Participants who had evidence of suboptimal effort on TOMM Trial 2 were excluded.

Abbreviations: NAB = Neuropsychological Assessment Battery; BRIEF-A = Behavior Rating Inventory of Executive Function-Adult Version; BRI = Behavioral Regulation Index; BDI = Beck Depression Inventory

Table A.3. Sample Characteristics by Age Group

Due to data distribution, race was recorded into White vs Black or African American, American Indian or Alaska Native, Native Hawaiian or other Pacific Islander, and multiple races all combined. Note that two participants did not report their race and were excluded because we required complete data on all participants as race was included in all statistical models. Ethnicity was not included in statistical models and one participant did not report their ethnicity. Sample size reduced for lobar white matter hyperintensities due to absence of a T2-weighted sequence to estimate regional WMH. For this Table purposes, total and lobar white matter hyperintensities are expressed in microliters. However, in analyses, total WMH are in milliliters and regional WMH are microliters. The total volume of WMH is based on all brain regions and not just those regions listed in Table A.1., which only refers to regions that made up the lobar composites. Therefore, discrepancy exists between total and lobar volume of WMH. For example, WMH were frequent around the lateral ventricles, in basal ganglia structures, and in the corpus callosum. These regions were not examined separately in this study (but did contribute to total volume of WMH) and were not necessarily included in the lobar composites.

Table A.4. Summary of Tobit Regression Models Comparing Former American Football Players and Asymptomatic Unexposed Participants on Total and Regional Log-Transformed White Matter Hyperintensities: Sensitivity Analyses Among those with Intact Trail Making Test Part B Scores

Tobit regressions compared the former American football players and the asymptomatic unexposed group on total, frontal, temporal, parietal, and occipital log-WMH. Sample was restricted to those who had intact executive functions as defined by a Trail Making Test Part B T-score>35. Model covariates included age (years), racial identity (White vs Black or African American, American Indian or Alaska Native, Native Hawaiian or other Pacific Islander, and multiple races all combined), rFSRP, BMI, APOE ε4 carrier status (absent/present), and evaluation site. As shown, effect sizes and statistical significance for group differences remained similar for total and lobar volume of WMH compare with those reported in the entire sample.

Abbreviations: Asymp. =. Asymptomatic; Est. = unstandardized estimate; FDR = false discovery rate; WMH = white matter hyperintensities

Appendix B: The DIAGNOSE CTE Research Project Current and Former Investigators and Key Personnel

Banner Alzheimer’s Institute

Investigators

Eric Reiman, M.D. (Co-PI)

Yi Su, Ph.D.

Kewei Chen, Ph.D.

Hillary Protas, Ph.D.

Non-Investigators

Connie Boker, M.B.A. (Director, Imaging Center Operations)

Boston University School of Medicine

Investigators

Michael L. Alosco, Ph.D.

Rhoda Au, Ph.D.

Robert C. Cantu, Ph.D.

Lindsay Farrer, Ph.D.

Robert Helm, M.D. *

Douglas I. Katz, M.D.

Neil Kowall, M.D. *

Jesse Mez, M.D.

Gustavo Mercier, M.D., Ph.D. *

James Otis, M.D. *

Robert A. Stern, Ph.D. (Co-PI)

Jason Weller, M.D.

Non-Investigators

Irene Simkin, M.S. (Lab Manager, Molecular Genetics Core Facility)

Boston University Project Coordinating Center Staff

Alondra Andino, B.A. (Project Administrative Manager) *

Shannon Conneely, B.A. (Site Coordinator) *

Courtney Diamond, M.B.A. (Project Manager) *

Tessa Fagle, B.A. (Research Assistant)

Olivia Haller, B.A. (Recruitment Coordinator) *

Tennyson Hunt, M.B.A. (Project Administrative Manager) *

Nicole Gullotti, M.B.A. (Research Administrator) *

Megan Mariani, B.S., B.A. (Project Manager)

Brian Mayville, B.S. (Site Coordinator)

Kathleen McLaughlin, B.A. (Research Assistant)

Mary Nanna, B.A. (Retention Coordinator)

Taylor Platt, M.P.H. (Recruitment Coordinator) *

Surya Pulukuri, B.A. (Research Assistant)

Fiona Rice, M.P.H. (Project Manager) *

Madison Sestak, B.S. (Assistant Recruitment Coordinator) *

Boston University School of Public Health

Investigators

Michael McClean, Sc.D.

Yorghos Tripodis, Ph.D.

Data Team Staff

Douglas Annis, M.S. (Systems Analyst) *

Christine Chaisson, M.P.H. (Leader of Data Management Sub-team) *

Diane B. Dixon (Project Manager)

Carolyn Finney, B.A. (Data Manager)

Kerrin Gallagher, M.P.H. (Statistical Analyst) *

Kaitlin Hartlage, M.P.H. (Statistical Analyst)

Jun Lu, M.S. (Data Security and Technology Analyst)

Brett Martin, M.S. (Statistical Manager)

Emmanuel Ojo, M.P.H. (Statistical Analyst) *

Joseph N. Palmisano, M.A., M.P.H. (Leader of Data Management Sub-team)

Brittany Pine, B.A., B.S. (Statistical Analyst)

Janani Ramachandran, M.S. (Data Manager)

Brigham and Women’s Hospital

Investigators

Sylvain Bouix, Ph.D.

Jennifer Fitzsimmons, M.D. *

Alexander P. Lin, Ph.D.

Inga K. Koerte, M.D., Ph.D.

Ofer Pasternak, Ph.D.

Martha E. Shenton, Ph.D. (Co-PI)

Non-Investigators

Hector Arcinieago, Ph.D. (Postdoctoral Research Fellow)

Tashrif Billah, M.S. (Software Engineer)

Elena Bonke, M.S. (Ph.D. Student)

Katherine Breedlove, Ph.D. (Postdoctoral Research Fellow)

Eduardo Coello, Ph.D. (Postdoctoral Research Fellow)

Michael J. Coleman, M.A. (Senior Scientist)

Leonhard Jung, (Ph.D. Student)

Huijun Liao, B.S. (Study Coordinator)

Maria Loy, M.B.A., M.P.H. (Senior Program Coordinator)

Elizabeth Rizzoni, B.A. (Research Assistant)

Vivian Schultz, M.D. (Postdoctoral Research Fellow)

Annelise Silva, B.S. (Research Assistant) *

Brynn Vessey, B.S. (Research Assistant)

Tim L.T. Wiegand, (Ph.D. Student)

Cleveland Clinic Lou Ruvo Center for Brain Health

Investigators

Sarah Banks, Ph.D. (Now at University of California, San Diego)

Charles Bernick, M.D. (Now at University of Washington)

Justin Miller, Ph.D.

Aaron Ritter, M.D.

Marwan Sabbagh, M.D. *

Non-Investigators

Raelynn de la Cruz, (Psychometrician)*

Jan Durant, (Psychometrician)*

Morgan Golceker (Site Coordinator)

Nicolette Harmon, (Site Coordinator) *

Kaeson Kaylegian, (Psychometrician)*

Rachelle Long, (Site Coordinator) *

Christin Nance, (Psychometrician)*

Priscilla Sandoval (Site Coordinator) *

George Washington University School of Medicine and Health Sciences

Investigator

Robert W. Turner, Ph.D.

Invicro (formerly Molecular NeuroImaging)

Investigator

Kenneth L. Marek, M.D.

Non-Investigator

Andrew Serrano, M.B.A.

Mayo Clinic Arizona

Investigators

Charles H. Adler, M.D., Ph.D.,

David W. Dodick, M.D.

Yonas Geda, M.D., MSc (Now at Barrow Neurological Institute)

Jennifer V. Wethe, Ph.D.

Non-Investigators

Bryce Falk, R.N.

Amy Duffy, (Site Coordinator) *

Marci Howard, (Psychometrician)*

Michelle Montague, (Psychometrician)*

Thomas Osgood, (Site Coordinator)

National Institute of Neurological Disorders and Stroke (NINDS)

Debra Babcock, M.D., Ph.D. (Scientific Program Official)

Patrick Bellgowan, Ph.D. (Administrative Program Official)*

New York University:

Investigators

Laura Balcer, M.D., M.S.C.E.

William Barr, PhD.

Judith Goldberg, Sc.D.

Thomas Wisniewski, M.D. *

Ivan Kirov, Ph.D.

Yvonne Lui, M.D.

Charles Marmar, M.D.

Non-Investigators

Lisena Hasanaj (Site Coordinator)

Liliana Serrano

Alhassan Al-Kharafi (Psychometrician)*

Allan George (Psychometrician)*

Sammie Martin (Psychometrician)*

Edward Riley (Psychometrician)*

William Runge (Psychometrician)*

University of Nevada, Las Vegas

Jeffrey L. Cummings, M.D., ScD (Co-PI)

University of Washington and VA Puget Sound

Investigator

Elaine R. Peskind, M.D.

Non-Investigator

Elizabeth Colasurdo (Lab Manager)

Washington University (CNDA)

Investigators

Daniel S. Marcus, Ph.D.

Non-Investigator

Jenny Gurney, M.S.

Consultants

Richard Greenwald, Ph.D. (Simbex)*

Keith A. Johnson, M.D. (Massachusetts General Hospital)

*No longer involved in project.

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