Abstract
Objective:
Apathy is common in Huntington’s disease (HD) and difficult to treat. There have been multiple recent calls to increase understanding of apathy across the spectrum of HD severity. Functional status is an important outcome in HD trials, but there is currently no consensus regarding the impact of apathy on functional status in HD. The aim of this study was to identify correlates of apathy and effects on functional status in a primarily early-stage HD sample.
Methods:
This study included secondary analyses of data from a study of neuropsychiatric symptoms in a clinical HD sample. Spearman correlation analyses were used to assess the relationships between apathy (Frontal Systems Behavior Scale-Apathy Subscore, FrSBe-Apathy), clinical variables, and patient-reported outcome measures. To assess the association of apathy with functional status, two multiple regression analyses were performed, with a different functional status measure (Adult Functional Adaptive Behavior or Total Functional Capacity) used as the dependent variable in each analysis.
Results:
Statistically significant correlates of apathy included NeuroQoL Satisfaction with Social Roles and Activities and NeuroQoL Positive Affect and Well-being scores (N=70). Univariate correlation analyses also revealed statistically significant associations of FrSBe-Apathy scores with both functional status measures (p<.001 for both). In the multiple regression analyses, apathy significantly contributed to variability in functional status as measured by both Adult Functional Adaptive Behavior (N=49) and Total Functional Capacity (N=56).
Conclusions:
Results underscore the need to address apathy as a target for improving functional status, social satisfaction, and well-being in HD, even for individuals with early-stage disease.
Introduction
Apathy is one of the most common behavioral manifestations of Huntington’s disease (HD). The definition of apathy has evolved over the past several decades but has most recently been proposed as a decrease in goal-directed behavior in multiple domains (emotional, behavioral/cognitive or social) (1). In HD populations, the prevalence of apathy increases as the disease progresses. In a large retrospective analysis of 6,316 HD gene carriers, lifetime incidence of apathy was noted in over half the study population, and average age of apathy onset was later than for other HD manifestations including motor symptoms (2). In accord with this, apathy has been frequently correlated with cognitive decline in HD (3). Despite its association with more advanced disease, apathy is also evident in pre-motor manifest HD populations, with prevalence estimates ranging from 10%–33% (4). Thus, apathy appears to manifest across the spectrum of HD.
Although prevalent in HD populations, apathy remains under-recognized and poorly understood. In a recent systematic review, Matmati et al. (2022) noted that conceptual and measurement inconsistencies (e.g., measurement of apathy as a symptom of DSM-5 diagnoses like depression) may lead to inaccurate assessment of apathy in people with HD (3). Apathy has been linked to negative outcomes for patients and caregivers, such as social withdrawal, decreased social satisfaction, and worse quality of life (5, 6). Unfortunately, apathy is notoriously difficult to treat. Given the prevalence and impact of this phenomenon in HD, there have been multiple recent calls to improve our understanding of apathy in this population (3, 4).
While apathy has been associated with negative outcomes, its influence on functional status is unclear. Researchers assess functional status to gauge impact of a given symptom or intervention on a patient’s day-to-day functioning, and functional status is used as an outcome in HD clinical trials (e.g., NCT04556656 and NCT05358821). The Unified Huntington’s Disease Rating Scale (UHDRS) Total Functional Capacity (TFC) is most commonly used to quantify functional status in HD, though limitations of this measure have been noted by us and others, particularly for individuals with early-stage HD (7–9). Despite the prevalence of apathy in HD and the importance of functional status as an outcome, there is currently no consensus regarding the effects of apathy on functional status (7). This may be due to limitations in instrumentation for both apathy and functional status measures (3, 7, 10).
More research is needed to understand the nature of apathy in HD and how it impacts functional status in this population. In the present study, we aimed to assess the relationship between apathy and other clinical variables, including functional status, in a primarily early-stage HD sample. Instruments used to measure variables of interest (apathy and functional status) addressed concerns previously raised by our team and others.
Methods
We performed secondary data analyses using baseline data collected for a study of neuropsychiatric symptoms in HD. Participants for the study were recruited from an HD specialty clinic in the southeast United States. Participants needed to be adults (18 years or older), have a clinical diagnosis of HD, and have at least one psychiatric symptom according to their HD clinician. They also needed to have a family member or caregiver willing to complete informant-report measures. We excluded individuals who had HD symptoms that would preclude them from completing patient-reported outcome measures (e.g., inability to communicate). The original study was approved by the Institutional Review Board at Vanderbilt University Medical Center, and participants and caregivers provided written informed consent. Data were recorded using REDCap electronic data capture tools (11, 12). For the current study, data were de-identified prior to analyses, and we only included participants who had complete data for our chosen apathy outcome measure at their baseline visit.
Instruments
To measure apathy, we used the apathy subscale of the Frontal Systems Behavior Assessment Scale-Family Version (FrSBe-Apathy) (13, 14). Psychiatrist assessment of apathy as a multi-dimensional construct is the gold standard for identifying apathy in HD. Caregiver-completed FrSBe-Apathy demonstrates reasonable convergent validity, as evidenced by its moderate correlation with psychiatrist apathy rating, and superior sensitivity compared to the Problem Behaviors Assessment-Short Version (10, 15), which is more commonly used (4). FrSBe-Apathy includes 14 items, with each item rated by caregivers on a 5-point Likert scale (item score range: 1–5). Raw scores (used here for consistency with our prior analysis (10)) range from 14–70, where higher scores indicate greater apathy severity. Cronbach’s alpha of FrSBe-Apathy in our sample was 0.89 (N=70).
To measure functional status, we used the Adult Functional Adaptive Behavior (AFAB) scale (16). AFAB involves a semi-structured interview with a caregiver and includes 14 items rated between 0.0 and 1.5. Total scores range from 0–21, with higher scores indicating higher levels of adaptive functioning. Cronbach’s alpha in our sample was 0.93 (N=61). Because the UHDRS TFC (17) is much more commonly used to measure functional status in HD, we also administered the TFC and include exploratory analyses with TFC for purposes of comparison with prior studies. TFC is administered via semi-structured interview with the patient (and caregiver if available). It includes 5 items with total scores ranging from 0–13, where higher scores indicate better functional status (Cronbach’s alpha= 0.79 in our sample, N=70).
Depressive symptoms were measured using Problem Behaviors Assessment-Short Version severity scores, with collapsed severity ratings (item score range: 0–3) as recommended by McNally et al (2015) (15, 18). Motor symptoms were measured using the UHDRS Total Motor Score (TMS) (17). Cognitive function was measured using the Montreal Cognitive Assessment (MoCA) (19).
Anosognosia was measured using the Anosognosia Rating Scale (20). For this scale, patients and clinicians separately rank a patient’s ability to ambulate, coordinate hand movement, concentrate/attend, speak, remember, retrieve words, control emotions, and sit still and quietly on a 5-point Likert scale from “very impaired” (−2) to “excellent” (+2). A difference score is calculated by subtracting clinician scores from patient scores. Higher anosognosia difference scores indicate patient overestimation of their abilities, whereas negative scores indicate patient underestimation of their abilities.
Patient-reported outcome measures included short forms of PROMIS Emotional Distress-Anger, PROMIS Sleep-Related Impairment, NeuroQoL Anxiety, NeuroQoL Satisfaction with Social Roles and Activities, and NeuroQoL Positive Affect and Well-being (21–24).
Data Analyses
Categorical variables were summarized using percentages, and continuous variables were summarized using median and interquartile range (IQR). To assess correlates of apathy in our sample, we conducted Spearman correlation analyses. Independent t-tests were used to assess differences in apathy according to sex.
To assess how apathy impacts functional status in HD, we performed multiple regression analyses with functional status (as indexed by AFAB score) as the dependent variable. Besides apathy, prespecified independent variables were selected based on previously reported or hypothesized relationships with functional status (7, 8, 25, 26). These included anosognosia difference score, standardized CAG Age-Product (CAP) score (using constants proposed by Warner et al., 2022 (27), where CAP=100 at time of diagnosis), and scores from FrSBe-Apathy, PBA-s Depression severity, MoCA, and UHDRS TMS. We specifically included depressive symptoms as a predictor variable to increase the likelihood that apathy’s relationship with functional status reflected distinct apathy symptoms, rather than apathy as a feature of depression. We then repeated the multiple regression analyses in the sample with TFC, rather than AFAB, as the functional status outcome variable. For both multiple regression analyses, we included only participants with complete data for the variables analyzed. Regression model assumptions (linearity, normality, lack of collinearity, homoscedasticity) were met, and statistical significance was based on a type I error rate of 0.05. SPSS version 28 was used for all analyses.
Results
We consented 108 participants, but six participants did not complete baseline measures after consenting and were removed from the analyses. Of the remaining 102 participants with baseline data, 70 had complete FrSBe-Apathy data and were included in the present analyses. There were no significant differences in age or CAG repeat length between the included and excluded groups (p>.05; see supplement for characteristics of excluded individuals). Fewer participants had complete data for inclusion in each of the multiple regression analyses (see Tables 3 and 4). Sample characteristics are summarized in Table 1. Our sample was majority male (53%) and Caucasian (94%). Most participants reported having motor symptoms of HD (82%), and median standardized CAP score was 105.84.
Table 3.
Summary of multivariate associations with AFAB (N=49)
| Characteristic | Beta (standardized) | p-value |
|---|---|---|
| Standardized CAP Score | .06 | .586 |
| Anosognosia Difference Score | .17 | .029 |
| FrSBe-Apathy Raw Score | −.24 | .006 |
| PBA-s Depression Severity (revised) | −.06 | .524 |
| MoCA Total Score | .39 | <.001 |
| UHDRS Total Motor Score | −.49 | <.001 |
Multiple R = .878, p <.001; R2 = .772 (Adjusted R2 = .739)
Table 4.
Summary of multivariate associations with TFC (N=56)
| Characteristic | Beta (standardized) | p-value |
|---|---|---|
| Standardized CAP Score | −.08 | .503 |
| Anosognosia Difference Score | .11 | .199 |
| FrSBe-Apathy Raw Score | −.26 | .003 |
| PBA-s Depression Severity (revised) | −.02 | .821 |
| MoCA Total Score | .24 | .039 |
| UHDRS Total Motor Score | −.48 | <.001 |
Multiple R = .838, p <.001; R2 = .701 (Adjusted R2 = .665)
Table 1.
Descriptive summaries of participant characteristics (N=70)
| Characteristic | |||
|---|---|---|---|
| Total N | Median | IQR | |
| Age in years | 48 | 37.3–57.7 | |
| CAG repeat | 65 | 44 | 42–46.25 |
| Standardized CAP score | 65 | 105.84 | 92.76–113.85 |
| N | % | ||
| Sex | 70 | ||
| Female | 33 | 47% | |
| Male | 37 | 53% | |
| Race/ethnicity * | 70 | ||
| Black or African American | 3 | 4% | |
| White or Caucasian | 66 | 94% | |
| Hispanic or Latino | 2 | 3% | |
| Participants with self-reported motor symptoms | 68 | 56 | 82% |
| Highest education | 67 | ||
| No formal education | 0 | 0% | |
| High School | 25 | 37% | |
| College | 1 | 2% | |
| Vocational training | 12 | 18% | |
| University | 24 | 36% | |
| Master’s degree | 5 | 8% | |
| Doctorate/PhD | 0 | 0% |
Participants could select multiple options for race and ethnicity
Apathy correlates
Descriptive statistics for apathy scores and other scale scores are summarized in Table 2. Histograms of FrSBe-Apathy, AFAB, and TFC scores are located in the supplement. Statistically significant correlates of apathy included NeuroQoL Satisfaction with Social Roles and Activities and NeuroQoL Positive Affect and Well-being scores.
Table 2.
Descriptive statistics and correlations with apathy scores (N=70)
| Descriptive statistics | Correlation with FrSBe-Apathy Score | ||||
|---|---|---|---|---|---|
| N | Median | IQR | Spearman’s ρ | p-value | |
| FrSBe-Apathy Raw Score | 70 | 39.5 | 31–47 | -- | -- |
| MoCA Total Score | 68 | 22 | 18–26 | −.21 | .092 |
| UHDRS Total Motor Score | 68 | 28 | 15–37.5 | .21 | .090 |
| Anosognosia Difference Score | 65 | 3 | 0–7 | −.12 | .354 |
| Standardized CAP Score | 65 | 105.84 | 92.76–113.85 | .15 | .233 |
| PBA-s Depression Severity (revised) | 68 | 1 | 0–2 | .15 | .215 |
| NeuroQoL Anxiety Raw Score | 67 | 17 | 12–24 | .12 | .318 |
| PROMIS Emotional Distress-Anger Raw Score | 65 | 15 | 10–21 | .06 | .619 |
| PROMIS Sleep-Related Impairment Raw Score | 67 | 18 | 14–24 | .20 | .111 |
| NeuroQoL Satisfaction with Social Roles and Activities Raw Score | 66 | 26.5 | 21–32 | −.46 | <.001 |
| NeuroQoL Positive Affect and Well-being Raw Score | 64 | 31.5 | 27–37.75 | −.26 | .036 |
There were no significant differences in FrSBe-Apathy scores between male and female participants (p=.243).
Effect of apathy on functional status
Univariate correlation analyses revealed statistically significant associations of FrSBe-Apathy scores with functional status as measured by both AFAB (ρ = −.55) and TFC (ρ = −.50; p < .001 for both; see supplement for scatter plots).
The multiple correlation of all six explanatory variables with AFAB was statistically significant (Multiple R = .878, p < .001), accounting for approximately 77% of the variability in AFAB score (adjusted R2 = .739). After controlling for all six explanatory variables, FrSBe-Apathy, MoCA, UHDRS TMS, and anosognosia scores were statistically significant contributors to variability in AFAB score (see Table 3).
The multiple correlation of all six explanatory variables with TFC was also statistically significant (Multiple R = .838, p < .001), accounting for approximately 70% of the variability in TFC score (adjusted R2 = .665). After controlling for all six explanatory variables, FrSBe-Apathy, MoCA, and UHDRS TMS were statistically significant contributors to variability in TFC score (see Table 4).
Discussion
In our predominantly early-stage HD cohort, patients with more apathy exhibited poorer functional status. Notably, apathy contributed uniquely to variance in functional status, regardless of functional status measure used (AFAB or TFC). We also found that apathy was correlated with less social satisfaction and less positive affect and well-being, though not with other patient-reported outcomes, in our sample.
Of all variables included in the univariate correlation analyses, functional status measures were most strongly correlated with apathy. In our multivariate models, apathy uniquely contributed to variability in functional status, regardless of functional status measure used. In the past, apathy has been consistently associated with progression of HD (3), but its association with functional status has been less clear. In our sample of primarily early-stage individuals (median standardized CAP score = 105.84), the association between apathy and functional status was relatively large. This is the only known study in HD to measure apathy using FrSBe-Apathy scores and functional status using AFAB. These measures address some of the limitations of more commonly used measures, such as PBA-s and TFC.
Motor, cognitive, and apathy scores significantly contributed to unique variance in functional status in both multivariate models. Interventions that address motor symptoms, cognitive symptoms, and apathy may improve functional status in HD. Currently, there are multiple available pharmacological options for treating motor symptoms in HD. Unfortunately, effective treatments for apathy and cognitive changes are lacking. We posit that effective treatment of apathy in HD is a critical line of inquiry to improve functioning and quality of life in people with HD. Further, clinical trials in HD often use functional status as a primary or secondary outcome measure. Given the important and unique contributions of apathy to functional status scores in our sample, clinical trial investigators should consider including apathy as covariate in planned efficacy analyses.
Anosognosia did contribute to the variability in AFAB scores, though the effect was small. Anosognosia did not significantly affect TFC scores in the multiple regression analysis. We have previously argued that AFAB may be a better measure of functional status in HD because it accounts for aspects of social functioning that may be missed by TFC (8). Our current findings suggest that AFAB is also more sensitive to detect anosognosia-related effects on functional status. Caregivers are generally included in the semi-structured interviews to complete AFAB and TFC, and we used the informant version of FrSBe to measure apathy, which should mitigate effects of anosognosia on reporting for these measures. Instead, we suspect that because AFAB has a greater number of questions and response options, its broader score range, compared to TFC, allows for more sensitivity in detecting linear effects on functional status.
In addition to effects on functional status, our analyses revealed other apathy correlates of interest. We found that greater apathy was correlated with decreased social satisfaction and, to a lesser extent, with positive affect and well-being. We consider this a particularly intriguing finding. It is logical that someone who has a decrease in goal-directed behavior would participate less in social activities (i.e., social withdrawal). On the other hand, it could be presumed that someone who is apathetic may not want to participate in social activities. In our previous qualitative work, several HD participants reported that they no longer wanted to engage with unfamiliar people or situations (5). Thus, we were surprised to find that apathy was related to decreased social satisfaction in the current study. These findings could indicate that although individuals with HD withdraw socially due to apathy, they may still desire to be socially engaged, and this mismatch results in less social satisfaction. Future studies should investigate the mechanisms underlying this relationship between apathy and social dissatisfaction.
We did not find a statistically significant relationship between apathy and MoCA scores in our sample. In general, prior studies have supported the link between apathy and cognition in HD (28–30). However, Fritz et al. (2018) also reported that apathy in their sample was not correlated with clinician-rated cognitive performance (6). The difference in findings between studies could be related to the divergent cognitive domains assessed, as Fritz et al. (2018) proposed. For example, in a large study of prodromal HD patients, apathy was related to a cognitive control cluster (i.e., measures of inhibition) but not language or memory clusters (29). In MoCA, executive function and attention account for only 11 points out of a possible 30 points, whereas recall, orientation, and language-related domains account for the majority of the score. Had our cognitive measure assessed cognitive control rather than global cognitive performance, we may have found different results. (However, Fritz et al. used a composite score of UHDRS measures of cognitive control [Verbal Fluency, SDMT, Stroop] and still did not find a statistically significant relationship with apathy in their sample (6).) Another consideration is that our sample was relatively cognitively intact (median MoCA 22 out of 30), which may have diminished our ability to detect a significant correlation. A future study using MoCA and UHDRS cognitive measures, as well as FrSBe to measure apathy, could shed additional light on potential differences related to instrumentation.
Limitations of this study include a small sample size, particularly for the multiple regression analyses. A larger sample would lend the opportunity to include additional potential covariates in our multivariate model. Additionally, we excluded people who could not complete patient-reported outcome measures (with or without caregiver assistance), which limits generalizability of these results for those with later-stage HD. However, this is unlikely to have significantly affected our findings given that we aimed to assess apathy’s effects in early-stage HD.
Conclusion
Apathy is a common feature of HD, and there have been several recent calls to better understand this phenomenon. Using measures that address some of the conceptual concerns raised by us and others, we found that apathy uniquely and significantly contributed to variance in functional status in an early-stage HD sample. Further, apathy was correlated with patient-reported social satisfaction and well-being in our sample. Future clinical trials should consider apathy’s role as a target or moderator for functional status outcomes.
Supplementary Material
Funding:
This study was funded by an investigator-initiated grant from Teva Neuroscience. JSG receives funding from the National Institute of Nursing Research (K23NR020210–01A1) and authored this manuscript while appointed as an iTHRIV Scholar at University of Virginia (UL1TR00315/KL2TR003016). DAI receives funding from the National Institute of Neurological Disorders and Stroke (K23NS131592) and from Teva Neuroscience. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health or the authors’ institutions.
Footnotes
Disclosures of potential competing interests:
JSG: JSG has received personal fees for consulting from Teva Pharmaceuticals.
KRH: KRH reports no financial relationships with commercial interests.
DOC: DOC has received research support from the NIH/NINDS/NIA/NICHD/NCCIH, Department of Defense, Griffin Family Foundation, and Huntington Disease Society of America; he has received pharmaceutical grant support from AbbVie, Alterity, Acadia, Biogen, BMS, Cerecour, Eli Lilly, Genentech-Roche, Lundbeck, Jazz Pharmaceuticals, Neurocrine, Teva Neuroscience, Wave Life Sciences, UniQure, and Vaccinex. He has received personal fees for consulting from Acadia, Alterity, Adamas, Anexon, Ceruvel, Lundbeck, Neurocrine, Spark, Uniqure, and Teva Neuroscience.
KEM: KEM reports no financial relationships with commercial interests.
AEB: AEB received compensation from Orphalan for an advisory board. AEB is in contracted studies with Alterity Therapeutics, Neurocrine Biosciences. Sage Therapeutics, Teva Pharmaceutical, and participates in contracted studies with AbbVie, CHDI Foundation, Hoffman-La Roche, Novarti, PTC Therapeutics, and UniQure.
AW: AW reports no financial relationships with commercial interests.
JJ: JJ reports no financial relationships with commercial interests.
DAI: DAI reports no financial relationships with commercial interests.
Contributor Information
Jessie S. Gibson, University of Virginia School of Nursing.
Kaitlyn R. Hay, Vanderbilt University Medical Center.
Daniel O. Claassen, Vanderbilt University Medical Center.
Katherine E. McDonell, Vanderbilt University Medical Center.
Amy E. Brown, Vanderbilt University Medical Center.
Amy Wynn, Vanderbilt University Medical Center.
Jessica Jiang, University of Virginia School of Nursing.
David A. Isaacs, Vanderbilt University Medical Center.
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