A data-driven disease progression model of fluid biomarkers in genetic frontotemporal dementia

Abstract

Several CSF and blood biomarkers for genetic frontotemporal dementia have been proposed, including those reflecting neuroaxonal loss (neurofilament light chain and phosphorylated neurofilament heavy chain), synapse dysfunction [neuronal pentraxin 2 (NPTX2)], astrogliosis (glial fibrillary acidic protein) and complement activation (C1q, C3b). Determining the sequence in which biomarkers become abnormal over the course of disease could facilitate disease staging and help identify mutation carriers with prodromal or early-stage frontotemporal dementia, which is especially important as pharmaceutical trials emerge. We aimed to model the sequence of biomarker abnormalities in presymptomatic and symptomatic genetic frontotemporal dementia using cross-sectional data from the Genetic Frontotemporal dementia Initiative (GENFI), a longitudinal cohort study. Two-hundred and seventy-five presymptomatic and 127 symptomatic carriers of mutations in GRN, C9orf72 or MAPT, as well as 247 non-carriers, were selected from the GENFI cohort based on availability of one or more of the aforementioned biomarkers. Nine presymptomatic carriers developed symptoms within 18 months of sample collection ('converters'). Sequences of biomarker abnormalities were modelled for the entire group using discriminative event-based modelling (DEBM) and for each genetic subgroup using co-initialized DEBM. These models estimate probabilistic biomarker abnormalities in a data-driven way and do not rely on previous diagnostic information or biomarker cut-off points. Using cross-validation, subjects were subsequently assigned a disease stage based on their position along the disease progression timeline. CSF NPTX2 was the first biomarker to become abnormal, followed by blood and CSF neurofilament light chain, blood phosphorylated neurofilament heavy chain, blood glial fibrillary acidic protein and finally CSF C3b and C1q. Biomarker orderings did not differ significantly between genetic subgroups, but more uncertainty was noted in the C9orf72 and MAPT groups than for GRN. Estimated disease stages could distinguish symptomatic from presymptomatic carriers and non-carriers with areas under the curve of 0.84 (95% confidence interval 0.80-0.89) and 0.90 (0.86-0.94) respectively. The areas under the curve to distinguish converters from non-converting presymptomatic carriers was 0.85 (0.75-0.95). Our data-driven model of genetic frontotemporal dementia revealed that NPTX2 and neurofilament light chain are the earliest to change among the selected biomarkers. Further research should investigate their utility as candidate selection tools for pharmaceutical trials. The model's ability to accurately estimate individual disease stages could improve patient stratification and track the efficacy of therapeutic interventions.

Keywords: biomarker; disease progression model; event-based modelling; frontotemporal dementia; neurofilament light chain.

Figure 1

GMM distributions for each biomarker. Histogram bins are shown for non-carriers (blue), presymptomatic carriers (orange) and symptomatic carriers (dark pink). The blue Gaussian represents the distribution of normal biomarker values based on non-carriers, whereas the dark pink Gaussian shows the distribution for abnormal biomarker values, as estimated by GMM. The amplitudes of these Gaussians are based on an estimated mixing parameter. Black curves show the total estimated biomarker distribution, i.e. the summation of blue and dark pink Gaussians, and indicate the overall fit of the estimated Gaussians to the observed data. All biomarker values were log-transformed.

Figure 2

Positional variance diagram showing the sequence of biomarker abnormalities. The colour intensity of each of the squares represents the number of bootstrap resampling iterations in which the biomarker was placed at a certain position. The darkest square for each biomarker therefore signifies the mode, i.e. the position where the biomarker was placed most frequently. The spread obtained from bootstrap resampling represents the standard error of the distribution and signifies uncertainty in the estimation of the ordering. The ordering of biomarkers is based on their position in the entire dataset (without bootstrap resampling), which is akin to mean position.

Figure 3

Estimated disease stages per clinical group. Disease stages were obtained using 10-fold cross-validation. (A) Histogram showing the frequency of occurrence of each of the disease stages per clinical group, normalized for each clinical group. Estimated disease stages are a continuous measure and were discretized for visualization purposes only. (B) Box plots of estimated disease stages for each clinical group. Box plots indicate median ± IQR; whiskers indicate median ±1.5× IQR. Symptomatic carriers and converters had higher estimated disease stages than presymptomatic non-converters (P < 0.001 and P = 0.004 respectively), but no difference was found between symptomatic carriers and converters (P = 0.712) (by Kruskal–Wallis tests).

Figure 4

Relationship between estimated disease stage and disease severity measures in mutation carriers. (A) MMSE score (r_s = −0.467, P < 0.001); (B) CDR^® + NACC FTLD-SB score (r_s = 0.530, P < 0.001); (C) disease duration in years (r_s = −0.124, P = 0.127) and (D) whole brain volume (r_s = −0.392, P < 0.001). Whole brain volume was expressed as a percentage of total intracranial volume. Presymptomatic carriers are shown in orange, and symptomatic carriers in dark pink. The regression lines were fit using splines; dotted lines indicate 95% prediction intervals.

Figure 5

Estimated disease stages for each genetic subgroup. Disease stages were obtained using co-initialized DEBM with 10-fold cross-validation. Histograms show the relative frequency of occurrence of each disease stage and box plots show the estimated disease stages per clinical group in (A) GRN, (B) C9orf72 and (C) MAPT mutation carriers. Estimated disease stages are a continuous measure and were discretized for visualization purposes only. Box plots indicate median ± IQR; whiskers indicate median ±1.5× IQR. Symptomatic carriers had significantly higher disease stages than presymptomatic carriers in all genetic subgroups (GRN and C9orf72: P < 0.001; MAPT: P = 0.004 by Mann–Whitney U-tests).