Abstract
Background
In Huntington’s disease, 60% of variance in onset age is not explained by the huntingtin gene mutation 1. Huntington’s disease onset was earlier in caffeine users 2.
Objective
To assess the relationship of life style factors with motor phenoconversion among persons at risk for Huntington’s disease.
Methods
Associations of motor phenoconversion and exposure to selected life style and health factors were examined using Cox proportional hazards analyses adjusted for age, gender and repeat length.
Results
Thirty-six of 247 subjects (14.6%) phenoconverted. Mean follow-up was 4.2 years. Greater caffeinated soda use was associated with increased hazard of phenoconversion: moderate use Hazard Ratio 2.26 (95% Confidence Interval 0.59, 8.71), high use Hazard Ratio 4.05 (95% Confidence Interval 1.18, 13.96).
Conclusions
Huntington’s disease onset was earlier among consumers of caffeinated soda, but not other caffeinated beverages. This finding may be spurious, or not related to caffeine.
Keywords: Huntington’s Disease, Environment, CAG Repeat, Phenoconversion, Caffeine
Introduction
Huntington’s disease is a fatal, progressive neurodegenerative disorder resulting from a trinucleotide cytosine-adenine-guanine (CAG) expansion in the huntingtin gene (OMIM). Persons with ≥ 37 repeats invariably develop clinical features of Huntington’s disease (phenoconversion) during the course of a normal life span, but 30% – 60% of the variability in age at onset remains unexplained 1. In other chronic neurodegenerative disorders, such as Parkinson’s disease and Alzheimer’s disease, environmental factors can influence risk, and the interaction of genes and environment is important. Recent reports suggest that environmental factors may modulate neurodegeneration in Huntington’s disease 3.
We previously reported analyses of dietary behaviors and phenoconversion in adults at risk for Huntington’s disease in PHAROS 4–6. We now report the relationship of selected life style and health-related behaviors to the onset of Huntington’s disease (motor phenoconversion).
Methods
Study Population
Adults at 50% risk for Huntington’s disease who wished to remain unaware of their Huntington’s disease genotype but consented to provide a coded DNA sample for CAG analysis were enrolled in PHAROS between 1999 and 2004 and followed prospectively until 20106. Motor phenoconversion was determined by a rater, unaware of genotype, based on the motor component of the Unified Huntington’s Disease Rating Scale (UHDRS).
Assessment of Clinical Factors
The UHDRS was administered at baseline and follow-up visits. An investigator’s response to UHDRS question #17 that a subject’s motor abnormalities “are unequivocal signs of Huntington’s disease with ≥99% confidence” for the first time was defined as motor phenoconversion. Depression was assessed using the Beck Depression Inventory administered within +/− 14 days of the environmental survey. Depression was defined as a Beck Depression Inventory >10.
Assessment of Environmental Risk Factors
Information regarding life-long use of tobacco products, caffeine, alcohol, certain medications (non-steroidal anti-inflammatory drugs, corticosteroids and, in women, estrogen preparations) and head injury was collected using validated, closed-response questionnaires completed by the subjects7,8. Some subjects completed them at the study baseline and others completed them at a later visit.
Definitions of Exposure Variables
Exposure variables were defined categorically and cumulatively, for the time period prior to phenoconversion, as follows:
Tobacco: Ever exposed: subjects who smoked ≥100 cigarettes, ≥50 cigars, ≥50 pipes, or used ≥10 pouches of chewing tobacco or cans of snuff; cumulative exposure was calculated in pack-years, defined as one pack of cigarettes/day for one year.
Alcohol: Ever exposed: subjects who consumed alcohol at least once a month for at least six months; cumulative exposure was calculated as grams of alcohol/day times years of use using standard values of alcohol content for each beverage type (http://www.mayoclinic.com/health/alcohol/SC00024), with a standard drink equal to 13.7 grams of pure alcohol.
Caffeine: Ever exposed: subjects who consumed ≥ 8 oz. of caffeinated coffee, tea or soda at least once per month for at least six months. For each beverage type, cumulative use was calculated in mg of caffeine/day times years of caffeine use using standard values for caffeine content http://www.mayoclinic.com/health/caffeine/AN01211.
Medications: Ever exposed: Subjects who regularly used nonsteroidal anti-inflammatory drugs, corticosteroids or, in women, estrogen preparations daily for ≥ 2 weeks.
Head injury: Subjects who ever had a head injury resulting in loss of consciousness or amnesia for > 5 minutes.
Statistical Methods
Subjects with expanded repeats (CAG ≥ 37) who had not phenoconverted before or at “baseline” were included in these analyses. The “baseline” was the date of survey completion. Cox models to predict time to phenoconversion were run for environmental variables by usage, adjusting for age, gender and CAG repeat length (continuous).
Results
Description of Subjects
247 PHAROS participants with CAG ≥ 37 who completed at least one environmental survey are included. Mean follow-up time after survey completion was 4.2 (SD 1.8) years. Seventy-four percent of subjects were women. Median baseline values for demographic and clinical measures were age: 44, years of education: 16, UHDRS motor score: 3, UHDRS chorea score: 0, symbol digit test score: 54 and Beck depression score: 3.
Phenoconversion in CAG Expanded Group
Thirty-six (14.6%) of the 247 subjects in the CAG expanded group phenoconverted following completion of the environmental survey. Analyses of caffeinated soda showed that history of soda consumption (p=0.05), higher current soda exposure (p=0.0376), and higher cumulative soda exposure (p=0.06) were all significantly associated with phenoconversion, but use of other caffeinated beverages was not associated with phenoconversion (Table 1). Regular use of tobacco or alcohol (Table 2), nonsteroidal anti-inflammatory drugs, corticosteroids or, in women, estrogens (data not shown) were not associated with phenoconversion.
Table 1.
Relationship of Caffeine Use and Phenoconversion among Subjects with CAG ≥ 37
| Median (25th, 75th Percentiles) | Did Not Phenoconvert (N = 211) | Phenoconverted (N = 36) | Hazard Ratio (95% CI) | P-Value | |
|---|---|---|---|---|---|
|
| |||||
| History of Caffeine Use: | |||||
| Never/Former | 10 (83%) | 2 (17%) | 1.00 | 0.48 | |
| Current | 196 (86%) | 33 (14%) | 0.59 (0.14, 2.54) | ||
|
| |||||
| History of Coffee Use: | |||||
| Never | 66 (85%) | 12 (15%) | 1.00 | 0.12 | |
| Former | 24 (92%) | 2 (8%) | 0.21 (0.05, 0.95) | ||
| Current | 112 (84%) | 21 (16%) | 0.67 (0.31, 1.46) | ||
|
| |||||
| History of Soda Use: | |||||
| Never | 40 (91%) | 4 (9%) | 1.00 | 0.05 | |
| Former | 35 (85%) | 6 (15%) | 2.35 (0.59, 9.42) | ||
| Current | 128 (84%) | 24 (16%) | 4.13 (1.23, 13.84) | ||
|
| |||||
| Current Caffeine Exposure: mg caffeine/day | |||||
| None | 0.0 (0.0, 0.0) | 10 (83%) | 2 (17%) | 1.00 | 0.25 |
| Moderate | 84.2 (33.1, 124.5) | 88 (90%) | 10 (10%) | 0.39 (0.09, 1.83) | |
| High | 450.5 (284.5, 632.1) | 78 (81%) | 18 (19%) | 0.72 (0.16, 3.23) | |
|
| |||||
| Current Coffee Exposure: mg caffeine/day | |||||
| None | 0 (0, 0) | 90 (87%) | 14 (13%) | 1.00 | 0.20 |
| Moderate | 221.3 (79,0, 221.3) | 59 (89%) | 7 (11%) | 0.67 (0.26, 1.74) | |
| High | 442.5 (442.5, 885.0) | 49 (78%) | 14 (22%) | 1.59 (0.73, 3.46) | |
|
| |||||
| Current Soda Exposure: mg caffeine/day | |||||
| None | 0 (0,0) | 75 (88%) | 10 (12%) | 1.00 | 0.0376 |
| Moderate | 7.4 (7.4, 22.2) | 51 (86%) | 8 (14%) | 2.13 (0.80, 5.62) | |
| High | 103.5 (51.8, 207.0) | 61 (81%) | 14 (19%) | 3.22 (1.32, 7.90) | |
|
| |||||
| Cumulative Coffee Exposure: mg caffeine/day * years | |||||
| None | 0 (0, 0) | 68 (85%) | 12 (15%) | 1.00 | 0.50 |
| Moderate | 2213 (972, 3540) | 64 (89%) | 8 (11%) | 0.56 (0.21, 1.47) | |
| High | 11948 (9293, 19028) | 58 (81%) | 14 (19%) | 0.77 (0.32, 1.87) | |
|
| |||||
| Cumulative Soda Exposure: mg caffeine/day * years | |||||
| None | 0 (0, 0) | 43 (91%) | 4 (9%) | 1.00 | 0.06 |
| Moderate | 442 (182, 782) | 72 (90%) | 8 (10%) | 2.26 (0.59, 8.71) | |
| High | 2691 (1708, 4192) | 63 (80%) | 16 (20%) | 4.05 (1.18, 13.96) | |
Values shown are number (N, %) or medians (25th and 75th percentiles) and hazard ratios (95% confidence intervals). Probability (p) -values are from 2 degree of freedom (df) tests in separate models to predict phenoconversion, adjusted for age at time of environmental survey, gender, and CAG repeat length (continuous); the reference category is never or none. CI =confidence interval.
Table 2.
Relationship of Tobacco Use, Alcohol Use and Phenoconversion among Subjects with CAG ≥ 37
| TOBACCO | Median (25th, 75th Percentiles) | Did Not Phenoconvert (N = 211) | Phenoconverted (N = 36) | Hazard Ratio (95% CI) | P-Value |
|---|---|---|---|---|---|
|
| |||||
| History of Tobacco Use | |||||
| Never | 105 (85%) | 18 (15%) | 1.00 | 0.44 | |
| Former | 51 (89%) | 6 (11%) | 0.65 (0.25, 1.66) | ||
| Current | 46 (81%) | 11 (19%) | 1.28 (0.58, 2.86) | ||
|
| |||||
| Current Exposure: # Cigarettes/Day | |||||
| None | 0 (0, 0) | 167 (87%) | 24 (13%) | 1.00 | 0.35 |
| Current Smoker | 12 (5, 20) | 29 (78%) | 8 (22%) | 1.52 (0.64, 3.62) | |
|
| |||||
| Cumulative Exposure: Pack Years | |||||
| None | 0.0 (0.0, 0.0) | 113 (86%) | 19 (14%) | 1.00 | 0.64 |
| Current/Past Smoker | 9.8 (1.1, 19.0) | 77 (87%) | 12 (13%) | 0.84 (0.39, 1.78) | |
|
| |||||
| ALCOHOL | Median (25th, 75th Percentiles) | Did Not Phenoconvert (N = 211) | Phenoconverted (N = 36) | Hazard Ratio (95% CI) | P-Value |
|
| |||||
| History of Alcohol Consumption | |||||
| Never | 45 (82%) | 10 (18%) | 1.00 | 0.57 | |
| Former | 20 (91%) | 2 (9%) | 0.46 (0.10, 2.18) | ||
| Current | 136 (86%) | 22 (14%) | 1.02 (0.45, 2.29) | ||
|
| |||||
| Current Alcohol Exposure: grams alcohol/day | |||||
| None | 0.0 (0.0, 0.0) | 66 (85%) | 12 (15%) | 1.00 | 0.61 |
| Moderate | 3.1 (1.1, 3.9) | 48 (80%) | 12 (20%) | 1.50 (0.64, 3.53) | |
| High | 18.1 (12.2, 33.0) | 56 (92%) | 5 (8%) | 1.02 (0.34, 3.01) | |
|
| |||||
| Cumulative Beer Exposure: grams alcohol/Day * years | |||||
| None | 0 (0, 0) | 82 (81%) | 19 (19%) | 1.00 | 0.99 |
| Moderate | 39 (20, 82) | 50 (88%) | 7 (12%) | 1.03 (0.42, 2.55) | |
| High | 369 (235, 822) | 51 (91%) | 5 (9%) | 0.97 (0.30, 3.10) | |
|
| |||||
| Cumulative Wine Exposure: grams alcohol/Day * years | |||||
| None | 0 (0, 0) | 113 (86%) | 18 (14%) | 1.00 | 0.86 |
| Moderate | 25 (14, 37) | 34 (83%) | 7 (17%) | 1.28 (0.52, 3.13) | |
| High | 152 (88, 329) | 35 (83%) | 7 (17%) | 1.06 (0.42, 2.69) | |
|
| |||||
| Cumulative Liquor Exposure: grams alcohol/Day * years | |||||
| None | 0 (0, 0) | 121 (86%) | 19 (14%) | 1.00 | 0.81 |
| Moderate | 23 (11, 36) | 34 (85%) | 6 (15%) | 0.71 (0.24, 2.09) | |
| High | 171 (94, 386) | 35 (88%) | 5 (13%) | 0.85 (0.31, 2.32) | |
Values shown are number (N, %) or medians (25th and 75th percentiles) and hazard ratios (95% confidence intervals). Probability (p)-values are from 2 degree of freedom (df) tests in separate models to predict phenoconversion, adjusted for age at time of environmental survey, gender, and CAG repeat length (continuous); the reference category is never or none. CI = confidence interval.
Discussion
Lifestyle behaviors such as caffeine consumption, cigarette smoking and alcohol use were not associated with motor phenoconversion, with one exception. Drinking caffeinated soda, but not other caffeinated beverages, was associated with phenoconversion. Although this association may be spurious in the setting of multiple comparisons, it is interesting to note that Simonin 2, in a retrospective assessment of persons with established Huntington’s disease, also reported that caffeine intake was associated with an earlier age at onset. Although caffeine has been associated with lower risk of developing Parkinson’s disease in epidemiologic studies,9,10 in Parkinson’s disease patients taking creatine in a clinical trial, caffeine intake was associated with more rapid disease progression, possibly due to a complex interaction with GRIN2A genotype11,12. Chronic caffeine intake may reduce adenosine A2A receptor activity13. In the 3-NP model of Huntington’s disease, A2A receptor antagonism has been associated with worsening of signs 14. However, no other form of caffeine was associated with Huntington’s disease risk, nor was a combined caffeine dose associated.
Carbonated soda intake may have adverse health effects independent of caffeine. Sugar containing soda use can increase caloric intake. We previously found increased caloric intake to be associated with higher CAG repeat length and 5 year probability of Huntington’s disease onset 5. Use of carbonated soda is also associated with greater risk of metabolic syndrome and diabetes, conditions associated with increased systemic inflammatory processes that may in turn be associated with neurodegeneration 15,16. In rats, carbonated soft drink intake causes oxidative stress and alters mRNA expression in dopaminergic and serotonergic pathways 17. In a community-based investigation of stroke risk factors, diet soda intake was associated with increased risk of vascular events including stroke 18. Finally, drinking carbonated beverages may result in increased intake of aluminum 19. Any of these effects, or some combination of these, may plausibly have an adverse effect on the ongoing neurodegenerative processes of Huntington’s disease. Replication and laboratory investigation are needed.
No other lifestyle factor assessed in this report was associated with phenoconversion in the PHAROS population, although we previously reported dietary dairy intake and higher caloric intake to be associated with motor phenoconversion 4,5. In the COHORT HD study, ever smoking cigarettes was associated with greater risk of phenoconversion in 59 persons with intermediate length (36–39 CAGs) repeats20, but we found no increased risk associated with smoking in our analysis of those with ≥ 37 repeats. More years of education predicted an earlier age at Huntington’s disease onset in a retrospective registry-based analysis 21. However, in our analyses, adjustment for education did not significantly influence the results.
This study has limitations. We collected information on lifelong behavior at a single point in time, without corroboration of participants’ reports. Information may have been forgotten, or incorrectly reported. We found few differences in reported exposures when participants with expanded repeats were compared to those without expanded repeats, however, suggesting that reporting was not biased due to “at risk” status. In addition, we collected information on many different factors, and have not made corrections for multiple comparisons. We have chosen to report these for future investigation, recognizing that some of the associations we observed may have been by chance22.
Strengths of this study include the large sample size, prospective follow up, and collecting data from asymptomatic at-risk persons. Prior reports all used primarily retrospective data collection in persons with established Huntington’s disease. In PHAROS, participants were unaware of genotype, an additional strength, suggesting that awareness of risk status was not likely to have caused a behavioral change or a difference in reporting. However, we have not assessed other exposures, such as toxicant chemicals, that may be proposed to modulate Huntington’s disease gene expression. Genetic modifiers of Huntington’s disease age at onset have been identified in gene association studies, but large populations were required 23. Future investigations with larger population sizes investigating the individual and combined effects of genes and environment on Huntington’s disease phenoconversion may provide additional insights.
In summary, in PHAROS, motor phenoconversion was generally not affected by the life style factors that we investigated, although in this and our prior analyses, certain dietary patterns, namely, caffeinated soda use, dairy intake and greater caloric intake were all associated with phenoconversion. Because dietary patterns may be modified, further investigation of these is indicated, and, if verified, could lead to recommendations to delay motor phenoconversion. The considerable amount of the non-CAG variance accounting for age at onset remains unexplained.
Acknowledgments
Funding sources for the study: NIH (HG002449), National Human Genome Research Institute, National Institute of Neurological Disorders and Stroke
The following members of the Huntington Study Group are investigators in PHAROS (Prospective Huntington At-Risk Observational Study) and are authors of this report.
Steering Committee: University of Rochester, Rochester, NY, Ira Shoulson, MD (principal investigator; Massachusetts General Hospital, Charleston, MA, Anne Young, MD, PhD (co-principal investigator); University of Rochester, Rochester, NY, Karl Kieburtz, MD, MPH (director, Clinical Trials Coordination Center); David Oakes (chief biostatistician); Elise Kayson, MS, RNC (project coordinator); Hongwei Zhao, ScD, M. Aileen Shinaman, JD (HSG executive director), Megan Romer, MS; Johns Hopkins University, Baltimore, MD, Kevin Biglan, MD (medical monitor); Massachusetts General Hospital, Charleston, MA, Steven Hersch, MD, PHD, Jack Penney, MD, (deceased); Columbia University Medical Center, New York, NY, Karen Marder, MD MPH; University of Iowa, Iowa City, IA, Jane Paulsen, PhD; Indiana University School of Medicine, Indianapolis, IN, Kimberly Quaid, PhD; Lily Corporate Center, Indianapolis, IN, Eric Siemers, MD; University of California- San Francisco and San Francisco Veterans Affairs Medical Center, San Francisco, CA, Caroline Tanner, MD, PhD
Participating Investigators and Coordinators: Hereditary Neurological Disease Centre (HNDC), Wichita, KS: William Mallonee, MD, David Palmer, MD (deceased), Greg Suter, BA; University of Kansas Medical Center, Kansas City, KS: Richard Dubinsky, MD, Gary Gronseth, MD, R. Neil Schimke, MD, Carolyn Gray, RN; Hennepin County Medical Center/Minneapolis, Minneapolis, MN: Martha Nance, MD, Scott Bundlie, MD, Dawn Radtke, RN; Ohio State University, Columbus, OH: Sandra Kostyk, MD, PhD, George W. Paulson, MD, Karen Thomas, DO, Nonna Stepanov, MD, Corrine Baic, BS ; Wake Forest University School of Medicine, Winston Salem, NC: James Caress, MD, Francis Walker, MD, Vicki Hunt, RN; Hotel-Dieu Hospital-CHUM, Montreal, QC: Sylvain Chouinard, MD, Guy Rouleau, MD, PhD, Hubert Poiffaut, RN, Brigitte Rioux (deceased); Emory University School of Medicine, Atlanta, GA: Claudia Testa, MD, PhD, Timothy Greenamyre, MD, PhD, Joan Harrison, RN,; University of California, San Diego (UCSD), LaJolla, CA: Jody Corey-Bloom, MD, PhD, David Song, MD, Guerry Peavy, PhD, Jody Goldstein, BS; University of Iowa, Iowa City, IA: Jane Paulsen, PhD, Henry Paulson, MD, Robert L. Rodnitzky, MD, Ania Mikos, BA, Becky Reese, BS, Laura Stierman, BS, Katie Williams, BA, Lynn Vining, RN, MSN; Columbia University Medical Center, New York, NY: Karen Marder, MD, MPH, Elan Louis MD, MSc, Carol Moskowitz, RN; Indiana University School of Medicine, Indianapolis, IN: Kimberly Quaid, PhD, Joanne Wojcieszek, MD, Melissa Wesson, MS, University of Washington & VA Puget Sound Health Care System, Seattle, WA: Ali Samii, MD, Thomas Bird, MD, Hillary Lipe, ARNP; Medical College of Wisconsin, Milwaukee, WI: Norman Reynolds, MD, Karen Blindauer, MD, Jeannine Petit, ANP; University of Rochester, Rochester, NY: Peter Como, PhD, Frederick Marshall, MD, Timothy Counihan, MD, Kevin Biglan, MD, Carol Zimmerman, RN,; Oregon Health & Science University, Portland, OR: Penelope Hogarth, MD, John Nutt, MD, Pamela Andrews, BS, CCRC; Massachusetts General Hospital, Charleston, MA: Steven Hersch, MD, PhD, Leslie Shinobu, MD, PhD, Diana Rosas, MD, Yoshio Kaneko, BA, Sona Gevorkian, MS, Paula Sexton, BA, CCRA; Mayo Clinic Scottsdale, Scottsdale, AZ: John Caviness, MD, Charles Adler, MD, PhD,; University of California Davis, Sacramento, CA: Vicki Wheelock, MD, David Richman, MD, Teresa Tempkin, RNC, MSN; Brown University (Memorial Hospital of Rhode Island), Pawtucket, RI: Chuang-Kuo Wu, MD PhD, Hubert Fernandez, MD, Joseph H. Friedman, MD, Margaret Lannon, RN, MS; Colorado Neurological Institute, Englewood, CO: Lauren Seeberger, MD, Christopher O’Brien, MD, Sherrie Montellano, MA; University of Michigan, Ann Arbor, MI: Ninith Kartha, MD, Sharin Sakurai, MD, PhD, Susan Hickenbottom, MD, PhD, Roger Albin, MD, PhD, Kristine Wernette, RN, MS; Washington University, St. Louis, MO: Brad Racette, MD, Joel S. Perlmutter, MD, Laura Good, BA,; UCLA Medical Center, Los Angeles, CA: George Jackson, MD, PhD, Susan Perlman, MD, Shelley Segal, MD, Russell Carroll, MA, Laurie Carr, BS; University of Alberta, Edmonton, Alberta: Wayne Martin, MD, Ted Roberts, MD, Marguerite Wieler, BSC, PT; University of British Columbia, Vancouver, British Columbia: Blair Leavitt, MD, Lorne Clarke, MD, CM, Lynn Raymond, MD, PhD, Joji Decolongon, MSC, Vesna Popovska, MD, Elisabeth Almqvist, RN, PhD; Baylor College of Medicine, Houston, TX: William Ondo, MD, Madhavi Thomas, MD, Tetsuo Ashizawa, MD, Joseph Jankovic, MD,; University of South Florida, Tampa, FL: Robert Hauser, MD, Juan Sanchez-Ramos, MD, PhD, Karen Price, MA, Holly Delgado, RN; University of Calgary, Calgary, Alberta: Sarah Furtado, MD, PhD, Anne Louise LaFontaine, MD, Oksana Suchowersky, MD, Mary Lou Klimek, RN, MA,; Centre for Addiction and Mental Health, Markham, Ontario: Rustom Sethna, MD, Mark Guttman, MD, Sandra Russell, BSW, RSW, Sheryl Elliott, RN; North Shore University Hospital, Manhasset, NY: Marc Mentis, MB, CHB, Andrew Feigin, MD, Marie Cox, RN, BSN, Barbara Shannon, RN; University of Alabama at Birmingham, Birmingham, AL: Alan Percy, MD, Leon Dure, MD, Donna Pendley, RN, Jane Lane, RN, BSN; University of Virginia, Charlottesville, VA: Madaline Harrison, MD, Elke Rost-Ruffner, RN, BSN; UMDNJ Robert Wood Johnson Medical Center, Stratford, NJ: William Johnson, MD,; University of Pennsylvania, Philadelphia, PA: Amy Colcher, MD, Andrew Siderowf, MD, Mary Matthews, RN; Institute for Neurodegenerative Disorders, New Haven, CT: Danna Jennings, MD, Kenneth Marek, MD, Karen Caplan, MSW; Albany Medical College, Albany, NY: Stewart Factor, DO, Donald Higgins, MD, Eric Molho, MD, Constance Nickerson, LPN, Sharon Evans, LPN, Diane Brown, RN (deceased); Winnipeg Clinic, Winnipeg, Manitoba: Douglas Hobson, MD, Paul Shelton, MD, Shaun Hobson, RN; University of Miami, Miami, FL: Carlos Singer, MD, Nestor Galvez-Jimenez, MD, William Koller, MD (deceased), Doris Martin, DDS, Kelly Lyons, PhD, Dinorah Rodriguez, RN; Rush Presbyterian-St. Luke’s Medical Center, Chicago, IL: Kathleen Shannon, MD, Cynthia Comella, MD, Jean Jaglin, RN, CCRC; University of Maryland School of Medicine, Baltimore, MD: Karen Anderson, MD, William Weiner, MD, Kelly Dustin, RN, BSN; Johns Hopkins University, Baltimore, MD: Adam Rosenblatt, MD, Christopher Ross, MD, PhD, Deborah Pollard; Boston University, Boston, MA: Marie H. Saint-Hilaire, MD, Peter Novak, MD, J. Stephen Fink, MD, PhD (deceased), Bonnie Hersh, MD, Melissa Diggin, MS, RN, Leslie Vickers, RN, MS,; University of Connecticut, Hartford, CT: Wallace Deckel, PhD, James Duffy, MD, Mary Jane Fitzpatrick, APRN.
We recognize and thank our committees, consultants and sponsors as well as the PHAROS research participants and their families.
Event Monitoring Committee: Massachusetts General Hospital: Steven Hersch, MD, PhD (co-chair); Indiana University: Julie Stout, PhD (co-chair); James Calhoun; University of Iowa: William Coryell, MD, Cheryl Erwin, JD, PhD, Wake Forest University School of Medicine: Vicki Hunt, RN; Johns Hopkins University: Christopher Ross, MD, PhD; Minnesota Center for Health Care Ethics: Dorothy Vawter, PhD.
Ethics Committee: Chicago-Kent College of Law: Lori Andrews, JD; Debbie Bury; James Calhoun; Massachusetts General Hospital: Steven Hersch, MD, PhD (chair); Wake Forest University School of Medicine: Vicki Hunt, RN; Carl Leventhal, MD, Indiana University School of Medicine: Kimberly Quaid, PhD, University of Rochester: Aileen Shinaman, JD,; Minnesota Center for Health Care Ethics: Dorothy Vawter, PhD, Columbia University: Nancy Wexler, PhD.
Biostatistics and Clinical Trials Coordination Center: University of Rochester: Alicia Brocht, BA, Susan Daigneault, Karen Gerwitz, BS, Connie Orme, BA, Ruth Nobel, Victoria Ross, MA, Mary Slough, Arthur Watts, BS, Joe Weber, BS, Christine Weaver, Elaine Julian-Baros.
Genetic/Environmental Modifiers Committee: Massachusetts General Hospital: Anne Young, MD, PhD (chair); Columbia University Medical Center: Karen Marder, MD (co-chair); Indiana University School of Medicine: Tatiana Foroud, PhD; Massachusetts General Hospital: James Gusella, PhD; Massachusetts Institute of Technology: David Housman, PhD; Massachusetts General Hospital: Marcy MacDonald, PhD; Boston University: Richard Myers, PhD; University of California – San Francisco: Caroline Tanner, MD, PhD; Massachusetts General Hospital: Rudolph Tanzi, PhD
Independent Monitoring Committee: Columbia University: Stanley Fahn, MD; Indiana University: Michael Conneally, PhD; Columbia University: Weiu-Yann Tsai, PhD
Scientific Advisory Committee: New York Hospital Department of Neurology: Flint Beal, MD; Massachusetts Institute of Technology: David Housman, PhD; Johns Hopkins University: Christopher Ross, MD, PhD; Massachusetts General Hospital: Rudolph Tanzi, PhD; Anne Young, MD, PhD; University of California, Irvine: Claudia Kawas, MD; University of California Los Angeles: Marie Francoise-Chesselet, MD, PhD.
DNA Oversight Committee: Indiana University Medical Center: Michael Conneally, PhD; University of Minnesota/Minnesota VA Medical Center: Martha Nance, MD; University of California San Diego, Clifford Shults, MD*; The University of California – San Francisco: Caroline Tanner, MD, PhD.
Independent Rater Video Committee: Oregon Health & Science University: Penelope Hogarth, MD; Massachusetts General Hospital: Diana Rosas, MD; University of Rochester: Hongwei Zhao, ScD
Footnotes
Authors Roles: 1.Research project: A. Conception, B. Organization, C. Execution; 2. Statistical Analysis: A. Design, B. Execution, C. Review and Critique; 3. Manuscript: A. Writing of the first draft, B. Review and Critique
CMT: 1.A, B,C; 2.C; 3.A;
SE: 1.B,C; 2.A,B; 3.A,B;
KM: 1.A,B,C; 2.C; 3.B
KB:1.C; 2.C; 3.B;
DO: 2.A,B; 3.B;
IS:1.A,B,C; 2.C; 3.B
Financial Disclosure/Conflict of Interest:
Caroline M. Tanner, Karen Marder, Shirley Eberly, Kevin Biglan, David Oakes and Ira Shoulson have no financial disclosures and no conflicts of interest regarding the manuscript.
Caroline M. Tanner: Regarding the manuscript: None; Other disclosures, past 12 months: Dr. Tanner is an employee of the San Francisco Veterans Affairs Medical Center and the University of California – San Francisco. She receives grants from the Michael J. Fox Foundation, the Parkinson’s Disease Foundation, the Department of Defense, Sage Bionetworks and the National Institutes of Health, compensation for serving on Data Monitoring Committees from Biotie Therapeutics, Voyager Therapeutics and Intec Pharma and personal fees for consulting from Neurocrine Biosciences and Adamas Pharmaceuticals.
Karen Marder: Regarding the manuscript: None ; Other disclosures, past 12 months: K. Marder receives research support from, 1UL1 1UL1TR001873-01, NS100600-01, U10 NS077267-06 She receives research support from the Parkinson Disease Foundation, Huntington’s Disease Society of America, the Parkinson Study Group, CHDI, and the Michael J. Fox Foundation. She received compensation from Springer SBM LLC for serving on editorial board;
Shirley Eberly: Regarding the manuscript: None; Other disclosures, past 12 months: Support from a grant from Biogen Idec and from the Huntington Study Group on behalf of Auspex Pharmaceuticals (Teva);
Kevin Biglan: Regarding the manuscript: None ; Other disclosures, past 12 months: at the time of manuscript preparation was employed by the University of Rochester, received research funding from the NIH/NINDS, National Parkinson Foundation, Michael J. Fox Foundation, AMC Health, Huntington Disease Society of America and Teva Pharmaceuticals; Contracts for care with the Presbyterian Home of Central New York, The Susquehanna Nursing and Rehailiation Center; consulting support from Teva Pharmaceuticals and is currently employed by Eli Lilly and company;
David Oakes: Regarding the manuscript: None ; Other disclosures, past 12 months: Dr. Oakes is an employee of the University of Rochester. He has received grant support from the NIH, the Department of Defense, TEVA, Prana Biotechnology and Vaccinex Pharmaceuticals and compensation for serving on a Data Monitoring Committee for Voyager Therapeutics and for consulting services to Raptor Pharmaceuticals;Ira Shoulson: Regarding the manuscript: None; Other disclosures, past 12 months: Dr. Shoulson is an employee of Georgetown University. Dr. Shoulson receives grant funds from the Parkinson’s Disease Foundation, US Food and Drug Administration, National Institutes of Health (NHGRI, NINDS), and the Michael J. Fox Foundation for Parkinson’s Research.
Consulting and Advisory Board Membership with honoraria: AZTherapies Inc., Banner Health, Dart Neurosciences, Decibel Therapeutics, Huntington Study Group, JAMA Neurology, Jazz Pharmaceuticals, Lysosomal Therapeutics, Michael J. Fox Foundation, Northwestern University, Oxford Biomedica, Partners Health Care, Sarepta Therapeutics, and the University of California Irvine.
Dr. Shoulson has been a non-executive director of the Prana Biotechnology Ltd Board of Directors (Melbourne, Australia), since May 2014. This position is compensated for director and consulting services but without any equity positions, stock options, or other financial incentives. Dr Shoulson is also founder and principal of Grey Matter Technologies (Sarasota FL) since January 2017.
References
- 1.Ross CA, Tabrizi SJ. Huntington’s disease: from molecular pathogenesis to clinical treatment. Lancet Neurol. 2011;10(1):83–98. doi: 10.1016/S1474-4422(10)70245-3. [DOI] [PubMed] [Google Scholar]
- 2.Simonin C, Duru C, Salleron J, et al. Association between caffeine intake and age at onset in Huntington’s disease. Neurobiol Dis. 2013;58:179–182. doi: 10.1016/j.nbd.2013.05.013. [DOI] [PubMed] [Google Scholar]
- 3.Mo C, Hannan AJ, Renoir T. Environmental factors as modulators of neurodegeneration: insights from gene-environment interactions in Huntington’s disease. Neurosci Biobehav Rev. 2015;52:178–192. doi: 10.1016/j.neubiorev.2015.03.003. [DOI] [PubMed] [Google Scholar]
- 4.Marder K, Gu Y, Eberly S, et al. Relationship of Mediterranean diet and caloric intake to phenoconversion in Huntington disease. JAMA neurology. 2013;70(11):1382–1388. doi: 10.1001/jamaneurol.2013.3487. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Marder K, Zhao H, Eberly S, et al. Dietary intake in adults at risk for Huntington disease: analysis of PHAROS research participants. Neurology. 2009;73(5):385–392. doi: 10.1212/WNL.0b013e3181b04aa2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Huntington Study Group PI. Biglan KM, Shoulson I, et al. Clinical-Genetic Associations in the Prospective Huntington at Risk Observational Study (PHAROS): Implications for Clinical Trials. JAMA neurology. 2016;73(1):102–110. doi: 10.1001/jamaneurol.2015.2736. [DOI] [PubMed] [Google Scholar]
- 7.Tanner CM, Ross GW, Jewell SA, et al. Occupation and risk of parkinsonism: a multicenter case-control study. Arch Neurol. 2009;66(9):1106–1113. doi: 10.1001/archneurol.2009.195. [DOI] [PubMed] [Google Scholar]
- 8.Goldman SM, Tanner CM, Oakes D, Bhudhikanok GS, Gupta A, Langston JW. Head injury and Parkinson’s disease risk in twins. Ann Neurol. 2006;60(1):65–72. doi: 10.1002/ana.20882. [DOI] [PubMed] [Google Scholar]
- 9.Ross GW, Abbott RD, Petrovitch H, et al. Association of coffee and caffeine intake with the risk of Parkinson disease.[see comment] JAMA. 2000;283(20):2674–2679. doi: 10.1001/jama.283.20.2674. [DOI] [PubMed] [Google Scholar]
- 10.Palacios N, Gao X, McCullough ML, et al. Caffeine and risk of Parkinson’s disease in a large cohort of men and women. Mov Disord. 2012;27(10):1276–1282. doi: 10.1002/mds.25076. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Simon DK, Wu C, Tilley BC, et al. Caffeine and Progression of Parkinson Disease: A Deleterious Interaction With Creatine. Clin Neuropharmacol. 2015;38(5):163–169. doi: 10.1097/WNF.0000000000000102. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Simon DK, Wu C, Tilley BC, et al. Caffeine, creatine, GRIN2A and Parkinson’s disease progression. J Neurol Sci. 2017;375:355–359. doi: 10.1016/j.jns.2017.02.032. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 13.Schwarzschild MA, Agnati L, Fuxe K, Chen JF, Morelli M. Targeting adenosine A2A receptors in Parkinson’s disease. Trends Neurosci. 2006;29(11):647–654. doi: 10.1016/j.tins.2006.09.004. [DOI] [PubMed] [Google Scholar]
- 14.Blum D, Hourez R, Galas MC, Popoli P, Schiffmann SN. Adenosine receptors and Huntington’s disease: implications for pathogenesis and therapeutics. Lancet Neurol. 2003;2(6):366–374. doi: 10.1016/s1474-4422(03)00411-3. [DOI] [PubMed] [Google Scholar]
- 15.Fowler SP. Low-calorie sweetener use and energy balance: Results from experimental studies in animals, and large-scale prospective studies in humans. Physiol Behav. 2016;164(Pt B):517–523. doi: 10.1016/j.physbeh.2016.04.047. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Crotti A, Glass CK. The choreography of neuroinflammation in Huntington’s disease. Trends Immunol. 2015;36(6):364–373. doi: 10.1016/j.it.2015.04.007. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.El-Terras A, Soliman MM, Alkhedaide A, Attia HF, Alharthy A, Banaja AE. Carbonated soft drinks induce oxidative stress and alter the expression of certain genes in the brains of Wistar rats. Mol Med Rep. 2016;13(4):3147–3154. doi: 10.3892/mmr.2016.4903. [DOI] [PubMed] [Google Scholar]
- 18.Gardener H, Rundek T, Markert M, Wright CB, Elkind MS, Sacco RL. Diet soft drink consumption is associated with an increased risk of vascular events in the Northern Manhattan Study. Journal of general internal medicine. 2012;27(9):1120–1126. doi: 10.1007/s11606-011-1968-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Duggan JM, Dickeson JE, Tynan PF, Houghton A, Flynn JE. Aluminium beverage cans as a dietary source of aluminium. Med J Aust. 1992;156(9):604–605. doi: 10.5694/j.1326-5377.1992.tb121455.x. [DOI] [PubMed] [Google Scholar]
- 20.Panegyres PK, Shu CC, Chen HY, Paulsen JS. Factors influencing the clinical expression of intermediate CAG repeat length mutations of the Huntington’s disease gene. J Neurol. 2015;262(2):277–284. doi: 10.1007/s00415-014-7559-5. [DOI] [PubMed] [Google Scholar]
- 21.Lopez-Sendon JL, Royuela A, Trigo P, et al. What is the impact of education on Huntington’s disease? Mov Disord. 2011;26(8):1489–1495. doi: 10.1002/mds.23385. [DOI] [PubMed] [Google Scholar]
- 22.Rothman KJ. No adjustments are needed for multiple comparisons. Epidemiology. 1990;1(1):43–46. [PubMed] [Google Scholar]
- 23.Genetic Modifiers of Huntington’s Disease C. Identification of Genetic Factors that Modify Clinical Onset of Huntington’s Disease. Cell. 2015;162(3):516–526. doi: 10.1016/j.cell.2015.07.003. [DOI] [PMC free article] [PubMed] [Google Scholar]