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Journal of Clinical and Experimental Neuropsychology

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The impact of oculomotor functioning onneuropsychological performance in Huntingtondisease

Janessa O. Carvalho, Jeffrey D. Long, Holly J. Westervelt, Megan M. Smith,Jared M. Bruce, Ji-In Kim, James A. Mills, Jane S. Paulsen & the PREDICT-HDInvestigators and Coordinators of the Huntington Study Group

To cite this article: Janessa O. Carvalho, Jeffrey D. Long, Holly J. Westervelt, Megan M. Smith,Jared M. Bruce, Ji-In Kim, James A. Mills, Jane S. Paulsen & the PREDICT-HD Investigators andCoordinators of the Huntington Study Group (2016) The impact of oculomotor functioning onneuropsychological performance in Huntington disease, Journal of Clinical and ExperimentalNeuropsychology, 38:2, 217-226, DOI: 10.1080/13803395.2015.1101054

To link to this article: http://dx.doi.org/10.1080/13803395.2015.1101054

Published online: 08 Jan 2016.

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The impact of oculomotor functioning on neuropsychologicalperformance in Huntington diseaseJanessa O. Carvalhoa, Jeffrey D. Longb,c, Holly J. Westerveltd, Megan M. Smithe, Jared M. Brucef,Ji-In Kimb, James A. Millsb, Jane S. Paulsenb,g,h and the PREDICT-HD Investigators and Coordinators ofthe Huntington Study Group

aDepartment of Psychology, Bridgewater State University, Bridgewater, MA, USA; bDepartment of Psychiatry, Carver College ofMedicine, University of Iowa, Iowa City, IA, USA; cDepartment of Biostatistics, College of Public Health, University of Iowa, IowaCity, IA, USA; dDepartment of Neurology, Vanderbilt University Medical Center, Nashville, TN, USA; eDepartment ofNeuropsychology, VA Maryland Healthcare System, Baltimore, MD, USA; fDepartment of Psychology, University of Missouri-Kansas City, Kansas City, MO, USA; gDepartment of Neurology, Carver College of Medicine, The University of Iowa, Iowa City, IA,USA; hDepartment of Psychology, University of Iowa, Iowa City, IA, USA

ABSTRACTHuntington disease (HD) is a neurodegenerative condition with prominent motor(including oculomotor), cognitive, and psychiatric effects. While neuropsychologicaldeficits are present in HD, motor impairments may impact performance on neuropsy-chological measures, especially those requiring a speeded response, as has beendemonstrated in multiple sclerosis and schizophrenia. The current study is the first toexplore associations between oculomotor functions and neuropsychological perfor-mance in HD. Participants with impaired oculomotor functioning performed worsethan those with normal oculomotor functioning on cognitive tasks requiring oculomo-tor involvement, particularly on psychomotor speed tasks, controlling for covariates.Consideration of oculomotor dysfunction on neuropsychological performance is critical,particularly for populations with motor deficits.

ARTICLE HISTORYReceived 15 October 2014Accepted 21 September2015

KEYWORDSHuntington disease;PREDICT-HD; oculomotorfunctioning;neuropsychology;processing speed

CONTACT Jane S. Paulsen predict-publications@uiowa.edu 500 Newton Road MEB 1-305, Iowa City, IA 52242-1000, USA.PREDICT-HD Investigators, Coordinators, Motor Raters, Cognitive Raters: Isabella De Soriano, Courtney Shadrick, and Amanda Miller (University of Iowa,Iowa City, Iowa, USA); Edmond Chiu, Joy Preston, Anita Goh, Stephanie Antonopoulos, and Samantha Loi (St. Vincent’s Hospital, The University ofMelbourne, Kew, Victoria, Australia); Phyllis Chua, and Angela Komiti (The University of Melbourne, Royal Melbourne Hospital, Melbourne, Victoria,Australia); Lynn Raymond, Joji Decolongon, Mannie Fan, and Allison Coleman (University of British Columbia, Vancouver, British Columbia, Canada);Christopher A. Ross, Mark Varvaris, Maryjane Ong, and Nadine Yoritomo (Johns Hopkins University, Baltimore, Maryland, USA); William M. Mallonee andGreg Suter (Hereditary Neurological Disease Centre, Wichita, Kansas, USA); Ali Samii, Emily P. Freney, and Alma Macaraeg (University of Washington andVA Puget Sound Health Care System, Seattle, Washington, USA); Randi Jones, Cathy Wood-Siverio, and Stewart A. Factor (Emory University School ofMedicine, Atlanta, Georgia, USA); Roger A. Barker, Sarah Mason, and Natalie Valle Guzman (John van Geest Centre for Brain Repair, Cambridge, UK);Elizabeth McCusker, Jane Griffith, Clement Loy, Jillian McMillan, and David Gunn (Westmead Hospital, Sydney, New South Wales, Australia); Michael Orth,Sigurd Süβmuth, Katrin Barth, Sonja Trautmann, Daniela Schwenk, and Carolin Eschenbach (University of Ulm, Ulm, Germany); Kimberly Quaid, MelissaWesson, and Joanne Wojcieszek (Indiana University School of Medicine, Indianapolis, IN, USA); Mark Guttman, Alanna Sheinberg, Albie Law, and IritaKarmalkar (Centre for Addiction and Mental Health, University of Toronto, Markham, Ontario, Canada); Susan Perlman and Brian Clemente (UCLA MedicalCenter, Los Angeles, California, USA); Michael D. Geschwind, Sharon Sha, Joseph Winer, and Gabriela Satris (University of California, San Francisco,California, USA); TomWarner and Maggie Burrows (National Hospital for Neurology and Neurosurgery, London, UK); Anne Rosser, Kathy Price, and SarahHunt (Cardiff University, Cardiff, Wales, UK); Frederick Marshall, Amy Chesire, MaryWodarski, and Charlyne Hickey (University of Rochester, Rochester, NewYork, USA); Peter Panegyres, Joseph Lee, Maria Tedesco, and Brenton Maxwell (Neurosciences Unit, Graylands, Selby-Lemnos & Special Care HealthServices, Perth, Western Australia, Australia); Joel Perlmutter, Stacey Barton, and Shineeka Smith (Washington University, St. Louis, Missouri, USA); ZosiaMiedzybrodzka, Daniela Rae, Vivien Vaughan, and Mariella D’Alessandro (Clinical Genetics Centre, Aberdeen, Scotland, UK); David Craufurd, Judith Bek,and Elizabeth Howard (University of Manchester, Manchester, UK); Pietro Mazzoni, Karen Marder, and Paula Wasserman (Columbia University MedicalCenter, New York, New York, USA); Rajeev Kumar, Diane Erickson, Christina Reeves, and Breanna Nickels (Colorado Neurological Institute, Englewood,Colorado, USA); Vicki Wheelock, Lisa Kjer, Amanda Martin, and Sarah Farias (University of California, Davis, Sacramento, California, USA); Wayne Martin,Oksana Suchowersky, Pamela King, Marguerite Wieler, and Satwinder Sran (University of Alberta, Edmonton, Alberta, Canada); Anwar Ahmed, StephenRao, Christine Reece, Alex Bura, and Lyla Mourany (Cleveland Clinic Foundation, Cleveland, Ohio, USA). Executive Committee: Principal Investigator Jane S.Paulsen, Jeffrey D. Long, Hans J. Johnson, Thomas Brashers-Krug, Phil Danzer, Amanda Miller, H. Jeremy Bockholt, and Kelsey Montross. ScientificConsultants: Deborah Harrington (University of California, San Diego); Holly Westervelt (Rhode Island Hospital/Alpert Medical School of Brown University);Elizabeth Aylward (Seattle Children’s Research Institute); Stephen Rao (Cleveland Clinic); David J. Moser, Janet Williams, Nancy Downing, Vincent A.Magnotta, Hans J. Johnson, Thomas Brashers-Krug, Jatin Vaidya, Daniel O’Leary, and Eun Young Kim (University of Iowa). Core Sections: Biostatistics. JeffreyD. Long, Ji-In Kim, Spencer Lourens (University of Iowa); Ying Zhang and Wenjing Lu (University of Indiana). Ethics. Cheryl Erwin (Texas Tech UniversityHealth Sciences Center); Thomas Brashers-Krug, JanetWilliams (University of Iowa); andMartha Nance (University of Minnesota). Biomedical Informatics. H.Jeremy Bockholt, Jason Evans, and Roland Zschiegner (University of Iowa).

JOURNAL OF CLINICAL AND EXPERIMENTAL NEUROPSYCHOLOGY, 2016VOL. 38, NO. 2, 217–226http://dx.doi.org/10.1080/13803395.2015.1101054

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Huntington disease (HD) is an autosomal domi-nant progressive neurodegenerative disorder witha trinucleotide cytosine–adenine–guanine (CAG)expansion in the gene coding for huntingtin,found on chromosome 4 (Huntington’s DiseaseCollaborative Research Group, 1993). IncreasedCAG repeat length is associated with earlier ageof HD diagnosis (Duyao et al., 1993; Lee et al.,2012; Stine et al., 1993). HD onset typically occursin adulthood, although persons with the geneexpansions can be affected at any time, with docu-mented onset ages between 1 and 80 years(Walker, 2007).

While HD patients can present with a range ofcognitive, behavioral, and functional impairments,the presence of unequivocal motor signs such aschorea, dystonia, rigidity, bradykinesia, and gaitinstability is required in order for a patient to receivea clinical diagnosis of HD (Huntington Study Group,1996). The main neuroanatomical feature of HD isatrophy of the caudate nucleus and putamen(Folstein, 1989; Gutekunst, Norflus, & Hersch,2002; Rubinsztein, 2003; Schwarcz & Shoulson,1987; Tobin, 1990; Vonsattel & DiFiglia, 1998). Ingenetically confirmed but nonclinically diagnosedpatients, subtle motor abnormalities, including sac-cade initiation, was associated with smaller striatalvolumes using volumetric magnetic resonance ima-ging (MRI) measurements (Biglan et al., 2009).However, motor abnormalities can manifest priorto clinical diagnosis. The stage known as prodromalHD is the period in which the patient may exhibitsome signs, but not sufficient in severity or quantityto meet criteria for a formal clinical diagnosis (Biglanet al., 2009; Paulsen et al., 2006; Paulsen et al., 2008).Research has established that HD signs can precedeformal motor diagnosis by as much as 15 years(Paulsen et al., 2006; Paulsen et al., 2008).

Chorea and oculomotor impairment are amongthe first signs that discriminate individuals withCAG expansions in the prodromal phase fromnon-gene-expanded individuals (Biglan et al.,2009; Paulsen, 2010). Oculomotor functions areclassified into several different categories (Leigh& Zee, 1999) and typically include ocular pursuitand saccades, both of which are commonlyaffected in prodromal and early HD patients.Ocular pursuit and saccades involve bringing orholding images on the fovea and stabilizing one’sgaze (Leigh & Zee, 1999). Oculomotor impair-ments are found consistently in diagnosed HDpatients (Blekher et al., 2006; Blekher et al., 2004;

Dursun, Burke, Andrews, Mlynik-Szmid, &Reveley, 2000; Golding, Danchaivijitr, Hodgson,Tabrizi, & Kennard, 2006; Hicks, Robert,Golding, Tabrizi, & Kennard, 2008; Lasker & Zee,1997; Tabrizi et al., 2009; Turner et al., 2011).

Cognitive deficits also are well documented inprodromal and diagnosed HD patients (Paulsen,Smith, & Long, 2013), and in prodromal HD itmay be a stronger indicator of future disease pro-gression than motor signs. In a sample of prodro-mal HD participants, cognitive dysfunctionaccounted for a greater amount of variance(34.0%) than motor abnormalities (11.7%) whenpredicting a probability of diagnosis within 5years (Stout et al., 2011). Cognitive impairmentsin prodromal HD participants include difficultieswith psychomotor/processing speed, episodicmemory, visuospatial processing, and executivefunctioning (Harrington et al., 2012; Paulsenet al., 2013; Stout et al., 2011). This pattern ofdeficits is similar to that observed in clinicallydiagnosed HD patients, where established deficitsin attention, verbal fluency, processing speed,executive functioning, memory, and visuospatialabilities are well described (Beglinger et al., 2005;Montoya et al., 2006; Paulsen & Conybeare, 2005;Stout & Johnson, 2005).

Assessment of many cognitive abilities relies ona motor response, including rapid writtenresponses and eye movements. While intactmotor abilities are required to complete neuropsy-chological tasks normally, these functions may notreflect the cognitive ability intended to be mea-sured by the task. For example, tasks that assessprocessing speed tend also to include a motorcomponent (e.g., visual scanning, providing rapidwritten or verbal responses). As such, motor defi-cits in persons with HD may interfere with perfor-mance on select cognitive measures. That is, inaddition to assessing the primary domain of inter-est, these measures may unavoidably be capturingdysfunction in secondary domains, such as motorimpairments.

While not thoroughly explored in HD patients,associations between oculomotor functions andneuropsychological performance have been docu-mented in other clinical populations. For example,a sample of medicated schizophrenia patients, whoare known to have documented oculomotorchanges, showed significantly greater associationsbetween oculomotor pursuit speed and most neu-ropsychological measures of processing speed,

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executive functioning, and motor speed than did amatched sample of healthy controls (Radant,Claypoole, Wingerson, Cowley, & Roy-Byrne,1997). Further, in patients with multiple sclerosis(MS), preliminary results show that patients withslower eye movements on an eye-tracking testdemonstrated associations with neuropsychologi-cal tasks that included a visuomotor component(Glusman et al., 2013).

The current study is the first study to examinerelationships between a global qualitative mea-sure of oculomotor functioning and neuropsy-chological test performances. Specifically, weexamined the impact of oculomotor abnormal-ities on neuropsychological performance in asample of participants with prodromal HD,adjusting for other motor impairments and addi-tional demographic covariates. We explored theeffects of oculomotor functioning (ocular pur-suit, saccade initiation, and saccade velocity) onneuropsychological measures in participants withprodromal HD and non-gene-expanded partici-pants. We expected significant partial associa-tions between oculomotor abilities andperformance on timed neuropsychological tasksthat involve speeded visual scanning, but modestor no relationships between oculomotor tasksand untimed cognitive tasks.

Method

Participants

Data in this study were collected from N = 1054participants in the Neurobiological Predictors ofHuntington’s Disease (PREDICT-HD) study(Paulsen et al., 2008). There were 821 gene-expanded and 233 non-gene-expanded partici-pants at 32 worldwide sites. All participantshad completed genetic testing for HD prior to(and independent from) study enrollment. Geneexpansion status and CAG repeat length wereconfirmed at the initial study visit. Participantswere considered to have prodromal HD if theirCAG repeat expansion was equal to or greaterthan 36, and they had a diagnostic confidencelevel of <4 (Huntington Study Group, 1996).Those with repeats less than 36 served as genemutation negative comparisons (controls). Atstudy enrollment, participants were required tobe 18 years of age or older and could not yet bediagnosed with manifest HD according to

traditional motor criteria. Exclusion criteriaincluded a history of a significant developmentalcognitive disorder, other central nervous systemdisease or injury, evidence of an unstable medi-cal or psychiatric illness (including substanceabuse), a pacemaker or metallic implants, orhaving taken prescribed antipsychotic medica-tion in the last six months or phenothiazinederivative antiemetic medication in the threemonths prior to enrollment. All participants pro-vided informed consent (reviewed and approvedby the Institutional Review Board at their respec-tive sites) and were treated in accordance withthe ethical standards of the AmericanPsychological Association.

Progression groupsIt is necessary to index the stage of progression atstudy entry in order to make proper inferences.Progression groups were based on the CAG–ageproduct (CAP) score (Zhang et al., 2011), whichis computed as CAP = (age at entry) × (CAG −33.66). CAP is similar to the “disease burden”score of Penney, Vonsattel, MacDonald, Gusella,and Myers (1997) and reflects the cumulativetoxicity of mutant huntingtin at the time ofstudy entry. There are CAP cutoffs that can beused to form progression groups (Zhang et al.,2011). The low group had CAP < 290, the med-ium group had 290 ≤ CAP ≤ 368, and the highgroup had CAP > 368. Based on this stratifica-tion, the estimated time to diagnosis for eachCAP group was >12.78 years for the low group,between 12.78 and 7.59 for the medium group,and <7.59 years for the high group.

Mean years in the study was 4.42 (SD = 2.79), witha range of 1 to 10. Furthermore, 9.59% of the samplehad only one year in the study, 14.79% had two years,and 75.63% had three or more years. Table 1 showsdemographic information by CAP group.

Procedure

All participants underwent comprehensive baselinescreening and annual visits at local study sites.Visits included blood draw, cognitive testing, aneurological evaluation, completion of psychiatricand psychological questionnaires, and brain MRI.All cognitive data were sent to a centralized loca-tion for quality control, including double or triplescoring of all protocols and double data entry toensure accuracy.

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Measures

The motor assessment portion of the UnifiedHuntington’s Disease Rating Scale (UHDRS;Huntington Study Group, 1996) was rated by atrained motor examiner as part of a neurologicexamination. The motor assessment portion consistsof the subdomains of oculomotor examination (sixitems), chorea (seven items), dystonia (five items),bradykinesia (11 items), and rigidity (two items;Marder et al., 2000). The primary UHDRS measuresof interest for the current study are the oculomotoritems of ocular pursuit (horizontal and vertical),saccade initiation (horizontal and vertical), and sac-cade velocity (horizontal and vertical). Ocular pur-suit measures smooth eye movements while theparticipant pursues a stimulus. Saccade initiationexamines the amount of time it takes a participantto initiate an eye movement to a designated stimu-lus. Saccade velocity indicates the strength and speedof a shifting gaze to a stimulus. Each task was ratedfor horizontal and vertical performance using a scaleranging from 0 (normal) to 4 (most severe impair-ment). The six items were summed to derive a totaloculomotor score (possible range of 0 to 24; seeTable 2 for distribution of oculomotor variable bygroup). Similar composites were computed for theother four motor domains of bradykinesia, rigidity,chorea, and dystonia (see Long et al., 2014, foradditional details).

A number of commonly used neuropsychologi-cal measures with and without visual motor or finemotor components were used in the current ana-lyses. Tasks that involve timed visual scanning anda rapid motor response included the Symbol Digit

Modalities Test (total correct; Smith, 1991), a mea-sure of processing speed and working memorymeasured through pairing symbols with digits;Trail Making Test A (time in seconds; Reitan,1958), a measure of psychomotor speed in whichparticipants connect circles containing numbers inascending order; Stroop Color Naming, WordReading, and Interference (total correct responsesin 45 seconds; Stroop, 1935), measures of proces-sing speed and executive functioning in whichparticipants are asked to rapidly name colors,read words, and name color-words provided line-arly and written in an incongruent color (e.g., theword “green” written in blue ink); and Buttons(the time between the release of one button andthe depression of the next; Georgiou-Karistianiset al., 2014),1 an experimental computerized mea-sure of cued movement sequencing.

Tasks with minimal motor speed demandsincluded the Wechsler Abbreviated Scale ofIntelligence (WASI) Matrix Reasoning (total cor-rect; Wechsler, 1999), an untimed visual abstractreasoning task, and the Hopkins Verbal LearningTest–Revised (HVLT) Delayed Recall (total wordsrecalled after a delay; Brandt & Benedict, 2001), ameasure of verbal list memory.

Statistical analysis

Linear mixed effects regression (LMER; Verbeke& Molenberghs, 2013) was used to address theprimary research question of whether oculomotorimpairment predicted cognitive performance overtime controlling for the four other domains ofmotor impairment (chorea, dystonia, bradykine-sia, rigidity), baseline progression (as indexed byCAP groups), and the demographic variables of

Table 1. Demographic information by CAP group.Demographics Control Low Medium High

N 233 215 288 318Femalea 148 (63.52) 146 (67.91) 188 (65.28) 187 (58.80)Age 44.36 (11.41) 34.98 (7.92) 41.67 (9.56) 44.93 (10.09)Educ 14.87 (2.56) 14.57 (2.44) 14.54 (2.61) 14.33 (2.75)Years in

study4.39 (2.29) 4.41 (2.68) 4.64 (2.61) 4.98 (2.52)

CAG 20.27 (3.49) 40.91 (1.62) 42.02 (2.04) 43.58 (2.74)CAP NA 243.97 (34.55) 330.50 (23.05) 423.19 (51.25)

Note. CAP = CAG–age product; CAG = cytosine–adenine–guanine;educ = years of education. Means, with standard deviations inparentheses, unless otherwise indicated.

aPercentages in parentheses, based on group total.

Table 2. Demographics for oculomotor and nonoculomo-tor functioning by CAP group.Oculomotorperformance Control Low Medium High

Oculomotorfunctioning

0.75 (1.43) 1.07 (1.83) 1.59 (2.32) 2.96 (3.28)

Nonoculomotorfunctioning

1.89 (2.22) 2.44 (3.39) 4.03 (4.53) 7.67 (7.53)

Note. CAP = CAG–age product; CAG = cytosine–adenine–guanine.Means, with standard deviations in parentheses.

1On the Buttons task, a touch screen computer monitor displayed a series of “buttons” arranged in 10 vertical pairs, with the pairs arranged in a lineacross the screen, along with additional buttons at the left and right of the rows to indicate the start and finish positions. The buttons were bluewhen depressed and turned white when pressed. Each participant was instructed to touch the white button in each pair as quickly and asaccurately as possible. When each button was touched, a sound was produced to indicate the correct response. The participant continued to toucheach illuminated white button down the sequence until the last column was depressed. The computer recorded the time for which each button washeld down and the time between the release of one button and the depression of the next.

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gender, years of education, and age at studyentry. The time metric for the LMER analysiswas duration, defined as the number of years inthe study since entry. CAP group membershipwas represented by dummy codes (1 = in-group,0 = otherwise), and each appeared in the modelas a main effect and as an interaction term withduration (i.e., the product of a dummy code andyears in study). The main effects represent overallCAP group level differences, and the interactionsrepresent CAP group differences in linear changeover time. All motor impairment variables weretime-varying predictors specified as main effects(overall level differences) and time interactions(slope differences). Based on previous research(see e.g., Paulsen et al., 2013), only the maineffects of the demographic variables were speci-fied. Individual variability and dependency due torepeated measures were modeled by randomintercepts and slopes in all models. Maximumlikelihood (ML) was used for estimation, whichyields unbiased parameter estimates with missingdata under the widely applicable assumption ofan ignorable missing data mechanism (Little &Rubin, 2002). (Additional details of the LMERmodels are presented in the Appendix.)

Eight outcome variables were examined sepa-rately: Symbol Digit Modalities Test (SDMT), TrailMaking Test A (time to completion), ButtonsCondition 1 mean movement time, Stroop ColorNaming total, Stroop Word Reading total, StroopInterference total, WASI Matrix Reasoning, andHVLT Delayed Recall. For each outcome, the fol-lowing LMER models were fit: (a) a model with nooculomotor effects, (b) a model with main effects foroculomotor functioning, and (c) a model with maineffects and time interactions (slope differences) foroculomotor functioning. All models were adjustedfor nonoculomotor functioning (chorea, dystonia,bradykinesia, rigidity), CAP group, and demo-graphic variables.

Models were compared in pairs (Model 1 vs.Model 2, Model 2 vs. Model 3) using a one-degree-of-freedom (df) likelihood ratio test (LRT). The nullhypothesis evaluated by the LRT is that the simplermodel (e.g., Model 1) has an equal statistical fit tothe more complex model (e.g., Model 2). Rejectionof the null hypothesis indicates that the more com-plex model should be adopted. Thus, the first LRTtested for the need of the oculomotor main effect,and the second LRT tested for the need of theoculomotor by time interaction.

Results

Results of the LMER model comparisons are shownin Table 3, along with the number of participants(N) and the number of time points (N*; i.e., allrepeated measures among all participants). Missingdata varied by variable due to timing of administra-tion and other site and protocol perturbations.

Table 2 shows that all outcomes except WASIMatrix Reasoning had a statistically significantmain effect for oculomotor impairments (second tolast column). The main effect was such that higheroculomotor scores were associated with worse per-formance. The last column of Table 3 shows that theoculomotor by time interaction was significant forthe Trail Making Test A, χ2(1) = 15.85, p < .001. Thesignificant interaction for Trail Making Test A indi-cates that the rate of change over time was condi-tional on oculomotor impairments, controlling forthe other variables. The nature of the effect is illu-strated in Figure 1, which shows fitted curves basedon Model 3 paneled by CAP group. The graphdepicts fitted curves for a zero oculomotor score,representing no impairment (“none”), and a scoreof 3, presenting moderate impairment (“moderate”);the dichotomy was used only for graphing purposeswith the continuous distribution used in the ana-lysis (see above). These values were chosen to bethe 50th and 75th percentile, respectively, of theempirical oculomotor distribution (note that 50%of the sample observations represented “normal”).In each panel, the blue line indicates normaloculomotor functioning (“none”), and the redline indicates moderately impaired functioning(note that the continuous variable was used forthe analysis, and the binary grouping is used onlyfor graphing). As the figure shows, there was an

Table 3. Linear mixed model regression results by cogni-tive variable.

Variable N N*

LRT

1 vs. 2(Main effect)

2 vs. 3(Interaction)

Symbol Digit Total 1050 4114 12.13*** 0.77Trail Making Test A 1047 2601 21.11*** 15.85***Buttons 1041 2560 38.82*** 0.88Stroop Color Reading 1050 4104 18.1*** 2.26Stroop Word Reading 1050 4113 16.7*** 1.99Stroop Interference 1050 4107 18.64*** 0.89WASI Matrix Reasoning 880 1412 0.50 1.94HVLT Delayed Recall 1049 2092 12.13*** 2.41

Note. N = sample size; N* = number of data points; LRT = likelihoodratio test (each test based on df = 1); Symbol Digit Total = total ofSymbol Digit Modalities Test; WASI = Wechsler Abbreviated Scale ofIntelligence; HVLT = Hopkins Verbal Learning Test–Revised.

***p < .001.

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expected CAP group effect, such that time tocompletion increased as number of visits in theindividual progression groups increased. The ocu-lomotor effect is seen in each panel with themoderately impaired curve having a greaterslope than the normal curve. Thus, impaired ocu-lomotor functioning was associated with a fasterrate of deterioration, controlling for nonoculomo-tor functioning and the covariates (see above).Detailed results not shown indicate that the rateof change for the unimpaired in the high CAPgroup was a decrease of 0.08 seconds per year onTrail Making Test A, whereas the impaired hadan increase of 0.53 seconds per year.

Discussion

The current study sought to examine the impact ofoculomotor abnormalities on neuropsychologicalperformance in a sample of individuals with pro-dromal HD. We found that on a test requiringquick visual scanning (Trail Making A), diseaseprogression was related to oculomotor function-ing. That is, oculomotor functioning predictedboth overall level (main effect) and change over

time (interaction), such that greater oculomotorsigns were associated with worse performance onTrail Making Test A (Figure 1). The association ofgreater oculomotor impairments with deteriora-tion in Trail Making Test A performance overtime occurred for all progression groups (low,medium, and high CAP groups). Notably, ourfinding was significant despite controlling forseverity of nonoculomotor dysfunction.

Further, we found expected associationsbetween oculomotor dysfunction and cognitivedeficits on tasks that required rapid oculomotoractivity. That is, the main effects indicate that forall the variables except WASI Matrix Reasoning,worse cognitive functioning was associated withgreater oculomotor impairments. This is consistentwith expectations as most neuropsychological tasksthat showed an association with oculomotor func-tioning required oculomotor involvement/speededresponses.

Also consistent with expectations, oculomotorperformance was not associated with a visualabstract reasoning task that requires no rapid ocu-lomotor response (WASI Matrix Reasoning). Thisabsence of associations between oculomotor effects

Figure 1. Fitted Trail Making Test A curves for two hypothetical impairment groups paneled by progression (one genenegative and three gene positive). To view a color version of this figure, please see the online issue of the Journal.

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and an untimed visual reasoning task providessome support for the sensitivity of our study.That is, effects were found on the expected tasksthat required oculomotor activity, and a lack of anassociation was found on the aforementioned taskthat did not require a rapid oculomotor response.

We also had an unexpected finding of oculomo-tor effects on a verbal learning task (HVLT delayedrecall). Associations between cognitive perfor-mance and oculomotor functioning may reflectoverall motor dysfunction or disease burden ratherthan oculomotor abilities per se. However, theabsence of an association between untimed visualreasoning and oculomotor performance, as well asthe fact that we controlled for disease burden andnonoculomotor function, argues against these gen-eralized motor effects (although the reason for thisassociation with the verbal memory task remainsunclear).

As previously discussed, there was a statisticallysignificant decline in Trail Making Test A perfor-mance over time as oculomotor impairments wor-sened. That is, in Figure 1, it is evident that thosewithout oculomotor impairment completed theTrail Making Test A faster after each evaluation(lower completion times), whereas those withimpairment did not improve their completiontimes after each evaluation. While the size of theTrail Making Test A decline may appear minimalin regard to clinical significance, it may haveimportant research implications. Though 0.81 sec-onds per year may not appear to be a very strongeffect in some contexts, some clinical trials in HDrely on cognitive outcomes (e.g., Kieburtz et al.,2010), and even very small changes may suggestimportant treatment effects, particularly if thetreatment group has an increasing slope (i.e.,improved performance) while the untreatedgroup has decreasing slope. This may be especiallytrue in trials involving degenerative conditions likeHD, where the ability to measure stability orimprovement in a condition that progresses overtime can be particularly challenging. As such, anydegree of change (or lack thereof) that is not accu-rately accounted for by the formal intervention canresult in erroneous conclusions about the utility ofthe intervention.

The current study has limitations. The gene-negative controls also included participants withoculomotor impairment of unclear etiologies, andgene-positive participants also had a wide range ofoculomotor performance. Thus, while our controls

are confirmed to be negative for HD and did notmeet exclusion criteria of other central nervoussystem disease or injury, we could not rule outthe possibility of some of our controls havingother early neurologic conditions that had notbeen diagnosed (though this suggests that ourresults are conservative). In addition, 75% of par-ticipants with abnormal impairments had a totaloculomotor score of 5 or less, indicating that theoverall dysfunction of our sample was somewhatmild. Therefore, our results may not generalize to amore severely oculomotor impaired sample.Further, the sample is composed of participantswith gene-positive prodromal HD and gene-nega-tive controls, all individuals who agreed to partici-pate in this longitudinal study (though the currentsample represents the largest group of prodromalHD participants ever studied). There is some evi-dence that HD patients who choose to undergogenetic testing may have better coping strategiesthan those who do not (Codori, Hanson, & Brandt,1994). Therefore, we are uncertain whether ourfindings would generalize to HD patients whowould not elect to undergo genetic testing, noropt to participate in studies of this kind. Ourresults revealed an association between oculomotorfunction and a verbal memory task, a finding thatwas not expected (though consistent with ourhypothesis, we found no association between ocu-lomotor function and nonverbal reasoning). Whilewe did control for disease burden in our analyses,this raises some question as to whether our resultsin part are capturing overall disease burden.Finally, the longitudinal nature of the study alsoraises concern about practice effects on all cogni-tive tasks, which may have minimized the measur-able impact of cognitive change over time. Futurestudies may consider also looking at other motoreffects on cognitive dysfunction such as dysarthria,which was not conducted in the current studygiven the low variability of this motor sign in oursample.

The current study was the first to explore asso-ciations between oculomotor functions and cogni-tive performance in HD. However, effects ofoculomotor performance on cognitive tasks havebeen documented in schizophrenia patients, inwhich associations between oculomotor function-ing and gross motor speed, visual scanning, andexecutive functioning have been observed (Radantet al., 1997), and in MS patients in which associa-tions were found between oculomotor functioning

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and neuropsychological tasks that included avisuomotor component (Glusman et al., 2013). Inour study, increases in oculomotor impairmentwere associated with a faster decline on a cognitivetask requiring rapid visual scanning, and we foundan association between oculomotor impairmentand neuropsychological tasks that require a rapidvisual response. The clinical implications of thisdecline depend on the extent of oculomotorimpairment and the length of time over whichindividuals are examined. Researchers conductingclinical trials and other research studies, particu-larly in samples with concern about oculomotorinvolvement, should be aware of oculomotoreffects when measuring cognitive performanceover time.

Acknowledgements

We thank the PREDICT-HD sites, the study participants,the National Research Roster for Huntington DiseasePatients and Families, the Huntington’s Disease Societyof America, and the Huntington Study Group.

Disclosure statement

Janessa Carvalho has no interests to declare. JeffreyLong has a consulting agreement with NeuroPhage,LLC. Megan Smith has no interests to declare. JaredBruce has no interests to declare. James Mills has nointerests to declare. Ji-In Kim has no interests to declare.Jane Paulsen has served on an advisory board forLundbeck, LLC and has a consulting agreement withProPhase, LLC.

Funding

This work was supported by the National Institutes forHealth, National Institute of Neurological Disorders andStroke [grant number 5R01NS040068] awarded to JanePaulsen; CHDI Foundation, Inc. [grant number A6266],[grant number A2015] awarded to Jane Paulsen; andCognitive and Functional Brain Changes in PreclinicalHuntington’s Disease (HD) [grant numberR01NS054893] awarded to Jane Paulsen.

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AppendixLinear mixed effects regression (LMER)

Suppose yij is the cognitive variable score for the ithparticipant (i = 1, . . ., N) at the jth time point (j = 1, . . .,ni). Then the LMER model for the analysis can bewritten in matrix notation as

yi ¼ X Durð Þi αþ X CAPð Þ

i βþ X Motorð Þi γ

þ X Demoð Þi δþ X Oculoð Þ

i ηþ X Durð Þi ai þ εi (A1)

where yi is the ni × 1 vector of cognitive variable scoresover time; X Durð Þ

i is the ni × 2 duration design matrix,with the first column a vector of 1s and the secondcolumn a vector of duration values indicating the yearin the study at which the measurement was taken (i.e.,

yearij); XCAPð Þi is the ni × 6 CAP design matrix containing

time-invariant dummy variables for the CAP groups (1= in the group, 0 = otherwise) and the product of thedummy variables and duration (CAP by time interac-

tion); X Motorð Þi is the ni × 8 motor design matrix contain-

ing the main effect of each of the four motor domains

other than oculomotor (bradykinesia, rigidity, dystonia,chorea), and their product with duration; X Demoð Þ

i is theni × 3 demographics design matrix with column values

of gender, years of education, and age at entry; X Oculoð Þi is

the ni × 2 oculomotor design matrix with the firstcolumn being the main effect of oculomotor and thesecond column being the product with duration, with arow of the relevant matrix product beingη1oculoij þ η2oculoij � yearij. The fixed effects vectorsare α; β; γ; δ; η, the random effects vector is ai, and therandom error vector is εi. We make the typical assump-tions, ai,N 0;Gð Þ?εij,N 0; σ2e

� �. Equation (A1) is

Model 3 discussed in the text (see Table 3), Model 2omits η2oculoij � yearij leaving the oculomotor maineffect, and Model 1 omits all oculomotor effects. Thus,the likelihood ratio test (LRT) of Model 1 versus Model2 is a test of H0: η1 = 0 (i.e., no oculomotor main effect),and the LRT of Model 2 versus Model 3 is a test of H0:η2 = 0 (i.e., no oculomotor by time effect).

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