Mutant huntingtin and neurofilament light have distinct longitudinal dynamics in Huntington's disease

Abstract

The longitudinal dynamics of the most promising biofluid biomarker candidates for Huntington's disease (HD)-mutant huntingtin (mHTT) and neurofilament light (NfL)-are incompletely defined. Characterizing changes in these candidates during disease progression could increase our understanding of disease pathophysiology and help the identification of effective therapies. In an 80-participant cohort over 24 months, mHTT in cerebrospinal fluid (CSF), as well as NfL in CSF and blood, had distinct longitudinal trajectories in HD mutation carriers compared with controls. Baseline analyte values predicted clinical disease status, subsequent clinical progression, and brain atrophy, better than did the rate of change in analytes. Overall, NfL was a stronger monitoring and prognostic biomarker for HD than mHTT. Nonetheless, mHTT has prognostic value and might be a valuable pharmacodynamic marker for huntingtin-lowering trials.

Fig. 1. HD-CSF study participant disposition.

Baseline visit (n = 80) was performed 24 months (± 3 months) before the follow-up visit (n = 74). Optional repeat sampling visits occurred 6 to 8 weeks after baseline. A more detailed version including all study assessments is provided in fig. S1.

Fig. 2. Longitudinal dynamics of mHTT and NfL over 24 months.

(A to C) Individual participant trajectories. Connected dots are measurements within the same participant. Disease groups are color-coded as per (J). (D to F) Modeled biomarker trajectories. Model (solid lines), 95% (colored areas), and 99% (dashed lines) bias-corrected accelerated confidence intervals were generated from generalized mixed-effects models. For CSF mHTT, age was used as first-order fixed effect, whereas for HD mutation carriers for NfL, there was a first- and second-order fixed effect for age. All models included CAG repeat count and had a random intercept for participant and corresponding random slopes for age. Dots represent the observed values. For ease of visual interpretation, two individual data points (>6000 pg/ml) were included in the model but excluded from the figure. (G to I) Modeling genetic dose-response relationships to show associations between biomarkers, age, and CAG repeat count. Solid lines were produced from our observations using the models above; dashed lines are predictions outside the range of our observations. Separate figures with individual data points for each individual CAG repeat count are provided in fig. S2, and the distribution of age and CAG within the cohort are supplied in fig. S3. Gray diamonds show the age of predicted onset for each CAG length [as per (35)]. Colored diamonds show the age at which HD mutation carrier trajectories are most likely to depart from healthy control trajectories for each CAG repeat count, generated by change-point analysis. (J) Annualized rates of change and 95% confidence intervals. For each biomarker, estimates were computed as the average of the rate of change in 1000 simulations per group of study participants (healthy controls, preHD, and manifest HD). Note that (A), (D), and (G) referring to mHTT do not depict values for controls. For CSF mHTT, shaded areas mark the limits of detection (LoD, 8 fM) and quantification (LoQ, 25 fM) of the assay. CSF, cerebrospinal fluid; mHTT, mutant huntingtin; N/A, not applicable; NfL, neurofilament light.

Fig. 3. Longitudinal associations of mHTT and NfL with disease progression quantified by cUHDRS.

Associations between (A to C) baseline values or (D to F) annualized rate of change in each analyte and the annualized rate of change in the cUHDRS. Pearson’s partial correlation coefficient adjusted for age and P values are presented. Gray figures were estimated including CAG in the model. Dashed horizontal lines mark no change in cUHDRS, with negative values representing deterioration. Dashed vertical lines mark no change in the biomarker. The baseline values (G to I) and annualized rate of change (J to L) for each biomarker compared between fast (n = 24) and slow progressors (n = 30), defined as participants with an absolute decrease in cUHDRS greater than or equal to 1.2 over the follow-up period. (M) Random forest plot for prediction of annualized rate of change in cUHDRS including baseline and rate of change of biofluid biomarkers as predictors. Higher relative importance score indicates a greater relative importance of the variable in predicting worsening cUHDRS score. Relative importance scores were based on the mean decrease in Gini score. Distributions were generated from rerunning the model 100 times. The boxes show the median and 25 and 75% percentiles, whereas whiskers are the lower and upper adjacent values (1.5 times the interquartile range minus the 25% percentile or plus the 75% percentile). Dots are values under and above the adjacent values. Violin plots represent ranking distributions. Black diamonds represent the median. cUHDRS, composite Unified Huntington’s Disease Rating Scale; DBS, disease burden score; Δ, annualized rate of change.

Fig. 4. Comparison of prognostic abilities of mHTT and NfL for clinical and imaging measures.

Matrices show the Pearson’s partial correlation coefficients adjusted for age only for associations between baseline values or annualized rate of change (Δ) of each analyte and the annualized rate of change in clinical and imaging measures, each expressed such that higher positive values denote clinical worsening. Color coding displays the magnitude and the direction of the association. Coefficients with corresponding confidence intervals and P values for each combination are provided in table S2. Scatter plots with individual data points for each association are provided in fig. S7. r, Pearson’s partial correlation coefficient; SDMT, symbol digit modalities test; SCN, Stroop color naming; SWR, Stroop word reading; TFC, UHDRS total functional capacity; TMS, UHDRS total motor score; VFC, verbal fluency—categorical.

Fig. 5. Associations of baseline markers with clinical progression.

Random forest plot for prediction of annualized rate of change in cUHDRS including baseline biofluid and imaging biomarkers as predictors. Higher relative importance score indicates a greater relative importance of the variable in predicting worsening cUHDRS score. Note that this figure uses the same technique as Fig. 3M but this model examines a different set of variables. Relative importance scores were based on the mean decrease in Gini score. Distributions were generated from rerunning the model 100 times. Violin plots represent ranking distributions.

Fig. 6. Discriminatory ability of mHTT and NfL for disease state.

ROC curves comparing the discriminatory ability of baseline values for each analyte and its annualized rate of change to distinguish (A) between healthy controls and HD mutation carriers and (B) between preHD and manifest HD. P values are for comparison between the baseline AUC and rate of change AUC. AUC, area under the curve; HD, manifest Huntington’s disease; preHD, premanifest Huntington’s disease.

Fig. 7. Statistical power, sample size, and trial duration.

Monte Carlo simulations predicting the statistical power of using (A) CSF mHTT, (B) CSF NfL, and (C) plasma NfL in the clinical trial context, contingent on sample size per arm, and trial duration in months. Two-arm parallel design clinical trials with no attrition or placebo effect with a constant effect size of 20% reduction in each analyte per year were simulated. Each pixel represents 1000 simulated clinical trials, generated using generalized mixed-effects models shaped to estimate the longitudinal trajectories of each biomarker (as in Fig. 2). The main effect in each simulation repetition was calculated as the interarm mean difference in the mean change from baseline, using generalized linear models adjusted for CAG. Statistical power was calculated as the proportion of trial simulations with a P < 0.05 for the main effect.

Fig. 8. Time in freezer and comparison of remeasurement of baseline samples.

(A to C) Time in freezer and analyte of interest. (D to F) Associations between repeated baseline measurements for CSF mHTT (purple; D and G), CSF NfL (blue; B and E), and plasma NfL (red; C and F) within controls (n = 20) and HD mutation carriers (n = 60; table S3). (G to I) Bland-Altman plots for remeasurement of baseline samples. The difference between the two measurements is plotted against the mean of the two measurements. Mean difference is represented by the black solid horizontal lines (table S3). The upper and lower 95% confidence intervals are designated with dashed horizontal lines. Each point represents one participant.