Effects of single-session repetitive transcranial magnetic stimulation to identify the optimal brain target in primary progressive aphasia

Abstract

Background

Non-invasive brain stimulation has shown positive results in maximizing the effects of language therapy in primary progressive aphasia (PPA). Due to the different patterns of brain damage in each aphasia variant, we hypothesized that patients with non-fluent and semantic variants would show a differential response to transcranial magnetic stimulation (TMS).

Objective

We aimed to compare the clinical responses after a single session of repetitive TMS in the left inferior frontal gyrus (IFG) and the left dorsolateral prefrontal cortex (DLPC).

Methodology

Twenty patients with PPA (14 with non-fluent and 6 with semantic variants) were assessed before and after repetitive TMS over the IFG, DLPC, and vertex with several language tasks, connected speech, and a subjective impression of change scale.

Results

IFG stimulation was associated with an improvement in words per minute and the subjective assessment in the non-fluent variant, but no effects were found in the semantic variant. DLPC stimulation was associated with an improvement in words per minute, repetition, and naming latency in the non-fluent variant, and in naming and subjective impression of change in the semantic variant.

Conclusions

Our study showed a differential effect of one session of brain stimulation over the IFG and DLPC in patients with non-fluent and semantic PPA variants. These findings suggest that the selection of the target of stimulation may be relevant for the success of brain stimulation and favor the use of DLPC over the IFG.

Keywords

Alzheimer's disease brain stimulation frontotemporal dementia primary progressive aphasia transcranial magnetic stimulation

Introduction

Primary progressive aphasia (PPA) is a clinical syndrome characterized by the gradual loss of language capabilities due to a neurodegenerative disorder. In the last years, three main variants have been recognized.¹ Each clinical variant is associated with different neurodegenerative diseases.² The non-fluent/agrammatic variant (nfvPPA) is characterized by laborious, halting speech production due to the involvement of the left frontal lobe and may be the onset of tauopathies and TDP-43 proteinopathies.

The semantic variant is a consequence of the progressive atrophy of the anterior temporal lobe (especially the left side) and is highly associated with type C TDP-43 proteinopathy. Finally, the logopenic variant (lvPPA) is associated with left parieto-temporal involvement and is considered an atypical form of Alzheimer's disease (AD).³

There are no curative therapies for PPA, and the disease produces devastating effects on communication abilities, functional independence, and quality of life of patients and their families. Age of onset is generally earlier than in other common causes of dementia, and the patient's insight may be more preserved than other forms of FTD or AD.³ In the last years, several non-pharmacological therapies have been investigated. Among them, non-invasive brain stimulation (and specifically transcranial magnetic stimulation, TMS, and transcranial electrical stimulation, tES) have shown promising results, maximizing the effects of language therapy in some preliminary investigations.^4–8

TMS is a focal brain stimulation technique. Repetitive protocols (rTMS) modulate the processes of long-term potentiation and depression, according to the frequency of stimulation. Although the effects are mainly local at the cortical regions of the brain surface in which the stimuli are concentrated, this technique has demonstrated to produce effects in distant areas that are structurally and functionally connected.⁹ One of the open questions in the field of brain stimulation in neurodegenerative disorders is the selection of the optimal target. The different patterns of brain damage and the evolving changes in brain structure and function suggest that the optimal target could be different depending on the specific syndrome and clinical stage. In this regard, previous studies of non-brain stimulation have used different brain targets and protocols, and a previous research combining tES and MRI showed that brain volumes and white matter integrity are associated with the response to tES over the left inferior frontal gyrus in patients with PPA.¹⁰ Overall, this suggests that examining different brain targets of brain stimulation may be relevant for maximizing the success of brain stimulation. In this regard, PPA could be a good model to evaluate the effect of different targets and the impact of anatomical differences, due to the existence of three main clinical phenotypes with differentiated regional features. These clinical and anatomical differences are especially evident when comparing nfvPPA and svPPA, because they are associated with a differential involvement in the dorsal and ventral language pathways.¹¹

The most common targeted region in rTMS for any indication is the dorsolateral prefrontal cortex (DLPC). This region is crucial in attention and executive functions like planning, and organization, and the enhancement of the neural circuits supporting these cognitive processes may help explain its therapeutic benefits. Additionally, rTMS stimulation of the left DLPC may modulate reward- and emotion-related dopamine and serotonin circuits,^12,13 which seem also impaired in patients with nfvPPA and svPPA.¹⁴ Although the DLPC does not seem to have a direct action on language function, the effects on working memory, reaction times, and inhibitory control could favorably impact on speech and language performance.^15,16 Another relevant target is the stimulation of the left inferior frontal gyrus (IFG) or Broca's area. The role of this region in language is beyond doubt,¹⁷ and it is a key region in nfvPPA.¹

In this study, we hypothesized that nfvPPA and svPPA show a differential response to brain stimulation in the left IFG and left DLPC. We aimed to compare the different clinical responses after a single-session of rTMS delivered over three brain targets: IFG and DLPC, considered as active targets; and vertex, used as control. All patients received rTMS over these three targets in different days and they were assessed immediately after each brain stimulation session using several language tasks and connected speech.

Methods

Study design and participants

This study is part of a clinical trial whose main results have already been published.⁶ It was a double-blind, single-center pilot study of 20 patients with PPA (non-fluent and semantic variants) who were treated with 15 sessions of personalized rTMS. Before the randomization, patients conducted a pre- treatment phase in which several brain targets were assessed with a single session of rTMS for the selection of the optimal target individually, as shown in Figure 1. According to the individual analysis of several targets, 9 cases with nfvPPA the stimulation were treated over the IFG, 4 over the superior frontal gyrus, and one over DLPF. In patients with svPPA, 5 received therapy over the DLPC, and 1 over the left anterior temporal lobe.

Figure 1.

Stimulation and clinical assessment pipeline.

In this study, we report the findings comparing the three targets that were examined in all the patients: IFG, DLPC, and vertex. Thus, we analyzed the changes produced after single-session rTMS in the pre-treatment phase of the trial. The main sociodemographic characteristics of the participants are shown in Table 1. At the time of study inclusion, the patients were assessed with the Addenbrooke's Cognitive Examination III¹⁸ and Neuropsychiatric Inventory.¹⁹ A significant depression was considered when the score in the depression domain (frequency x severity) was at least 4 points. The study was performed according to the guidelines of the Declaration of Helsinki and approved by the local ethics committee.

Table 1.

Main clinical and demographic characteristics.

	PPA	nfvPPA	svPPA
Number of participants	20	14 (70%)	6 (30%)
Women	12 (60%)	8 (57.1%)	4 (66.7%)
Age	66.9 ± 7.2	68.2 ± 7.4	63.8 ± 6.3
Age of onset	63.1 ± 6.2	64.7 ± 6.2	59.3 ± 4.5
Years of education	13.4 ± 4.4	13.6 ± 4.6	13 ± 4.1
ACE-III	64.8 ± 22.9	72.2 ± 18.1	47.5 ± 25.0
NPI-total score	13.4 ± 16.4	9.7 ± 14.9	22.0 ± 17.9
NPI (number of patients with depression)	2 (10%)	1 (7.1%)	1 (16.6%)

rTMS protocol

Brain stimulation was applied under neuronavigation using a Magstim Rapid2 stimulator (Magstim, Whitland, UK) with a figure-of-eight coil. Brain targets were chosen using anatomical coordinates according to the structural MRI of each patient. The following protocols were used: a) For IFG and DLPC, 1500 pulses of 20 Hz rTMS trains with an interval of 20 s at 100% of the resting motor threshold; b) for vertex, 600 pulses at 1 Hz, with an interval of 10 s, at 25% of the resting motor threshold. All the sessions were conducted under online neuronavigation. A washout period of at least 7 days was observed between sessions.

Language assessment

The patients were assessed with the following tasks and scores in order to cover some of the most relevant aspects of language impaired in PPA:

Number of words per minute using wordless children's books Frog Stories by Mercer Mayer. The patient was asked to describe the story for a maximum of 3 min. This variable was selected as one of the main outcomes, considering that it has been considered a reliable connected speech measure significantly impaired in PPA variants.²⁰

Naming accuracy (number of correct items) and naming latency (time since stimuli presentation and correct response). An object naming task of 12 items was used. Each item was shown to the patient. A maximum latency of 15 s was allowed. If the patient gave an incorrect response, the examiner responded “No, this object has another name” and allowed two additional attempts. The time between the object presentation and the correct response was registered in seconds. This implies that if the patient responded on the second attempt, the answer was considered correct, and one point was awarded for that response. However, since it took more time, it negatively affected the naming latency.

Dysdiadochokinesia (“Pa-ta-ka”, “Gracias-Gracias”, “Tic-Tac”, “Cinco-cinco”). The patient was asked to repeat each sequence as soon as possible. The number of correct repetitions of the sequence in a period of 5 s each one was registered.

Reading accuracy and efficiency. The patient read a text of 100 words and we calculated the accuracy (defined as the number of words correctly read) and the efficiency (the result of multiplying accuracy × 100 and divided by the time in seconds to complete the reading).

Repetition. The task included the repetition of 5 non-words (e.g. “hospitel”, “verfama”) and a sentence of 6 words. It was scored as 1 point for each non-word repeated correctly and 6 points for the whole sentence (1 point was discounted in this case if the patient repeated a word erroneously or changed the order of the sentence).

Parallel versions of all the tasks (except for dysdiadochokinesia) were used to reduce learning effects. The object naming tasks and the repetition tasks were matched for word frequency, age of acquisition and number of syllables. The reading task was matched for number of words, mean syllables/word and the Flesch-Fernández-Huerta score, calculated with the INFLESZ program. All the versions were administered at baseline and a specific one was randomly chosen for each session. All the assessments were audiotaped and were later transcribed for analysis by an independent researcher that was blind to the brain stimulation protocol.

Additionally, a clinical (subjective) impression of change was rated by the family. The family was asked: “Compared with the patient's condition at baseline before the last session, how do you rate his/her change?” (rated from 0 = very much worse to 10 = very much improved, being 5 = no change from baseline). The clinical impression was assessed between 5 to 7 days after the session by phone or in presence and referring to the first 1–3 days after the TMS session.

Connected speech assessment

Speech samples were obtained during the description of the wordless books. Participants were audiotaped with a Zoom H4n voice recorder and an Audix HT2P headset dynamic microphone. Audio recordings were processed using Praat²¹ and SALT software packages.²² In addition to the number of words per minute described above, which was the main variable for spontaneous speech, we also conducted a comprehensive assessment of connected speech, as described elsewhere.²³ Specifically, we evaluated the variables described in Supplemental Table 1. The selection of these variables was motivated by our previous study analyzing connected speech in PPA variants.²³

Statistical analysis

Statistical analysis was conducted using R software (version 4.1.2) and the packages nlme (version 4.1.3), MASS (version 7.3-54) and psych (version 2.2.5). Descriptive results are showing as mean ± standard deviation or frequency (percentages). Normality was checked using Q-Q plots.

For the analysis of the response to rTMS to the general language assessment, we first examined the existence of differences between baseline and after each rTMS session using a paired t-test. This analysis was applied for each target and PPA variant. Then, we used a Generalized Linear Mixed Model (GLMM) to evaluate the effect of time, PPA subtype and stimulation predictors on the dependent variable, using a quasipoisson distribution of errors. The patient identity was included as random effect.

Regarding GLMM assumptions, we checked the linearity and homoscedasticity of residuals using plots of residuals against fitted values, normality of the residuals using Q-Q plot graphs and outliers identifying all values exceeding Q3 + 3xIQR or less than Q1 − 3xIQR.²⁴ Sphericity was also checked, and we applied the Greenhouse-Geisser correction when it was violated.

For the analysis of connected speech, we used first exploratory Factor Analysis (EFA) to reduce the dimensionality of the connected speech variables, given that several of these parameters are correlated. We removed high correlated variables (Pearson correlation with coefficients higher than 0.9) and then we applied factor analysis using ‘MinRes’ method to find the best solution and ‘varimax’ as rotation parameter. Regarding the number of factors to be selected, we applied parallel analysis. Parameters with coefficients 0.6 were considered meaningful to interpret the component. Additionally, scores obtained with regression analysis from each factor were used for statistical analysis using GLMMs, as described in the previous paragraph.

For all the analyses, a p-value < 0.05 was considered statistically significant.

Results

General language assessment

In nfvPPA (Table 2), we found a significant improvement in the words per minute and the clinical impression of change variables for the IFG, and in the words per minute, repetition, naming latency and the clinical impression of change variables for DLPC. No significant changes were detected after vertex stimulation (Figures 2 and 3).

Figure 2.

Effect of brain stimulation of IFG, DLPC and vertex in nfvPPA and svPPA in main variables (1). T1: baseline assessment; T2: assessment immediately after rTMS session. (a) Words per minute – nfvPPA, (b) Words per minute – svPPA, (c) Naming accuracy – nfvPPA, (d) Naming accuracy – svPPA, (e) Naming latency – nfvPPA, (f) Naming latency – svPPA, (g) Dysdiadochokinesia – nfvPPA, (h) Dysdiadochokinesia – svPPA.

Figure 3.

Effect of brain stimulation of IFG, DLPC and vertex in nfvPPA and svPPA in main variables (2). T1: baseline assessment; T2: assessment immediately after rTMS session. (a) Reading accuracy – nfvPPA, (b) Reading accuracy – svPPA, (c) Reading efficiency – nfvPPA, (d) Reading efficiency – svPPA, (e) Repetition – nfvPPA, (f) Repetition – svPPA, (g) Clinical impression of change – nfvPPA, (h) Clinical impression of change – svPPA.

Table 2.

Paired t-tests comparing the changes in the main variables for each target in patients.

Area	Variable	PPAnfv	PPAsv
Area	Variable	p	p
IFG	Words per minute	0 . 001	0.284
	Naming accuracy	0.846	0.444
	Naming latency	0.581	0.299
	Dysdiadochokinesia	0.750	1
	Reading accuracy	0.552	0.142
	Reading efficiency	0.231	0.678
	Repetition	0.205	0.374
	Clinical imp. of change	0.001	0.084
DLPC	Words per minute	0.010	0.112
	Naming accuracy	0.280	0.854
	Naming latency	0.011	0.099
	Dysdiadochokinesia	0.497	0.689
	Reading accuracy	0.135	0.034
	Reading efficiency	0.098	0.665
	Repetition	0.016	0.778
	Clinical imp. of change	0.001	0.012
Vertex	Words per minute	0.123	0.095
	Naming accuracy	0.143	1
	Naming latency	0.265	0.482
	Dysdiadochokinesia	0.487	0.660
	Reading accuracy	0.364	0.208
	Reading efficiency	0.881	0.659
	Repetition	0.187	0.178
	Clinical imp. of change	0.336	0.178

Statistically significant p-values are shown in bold.

In svPPA (Table 2), we found no significant changes after IFG stimulation. There was an improvement in the reading accuracy and the clinical impression of change variables with DLPC stimulation. There were no significant changes using vertex stimulation (Figures 2 and 3).

In the GLMM analysis (Table 3), we found significant changes in the words per minute variable for nfvPPA in IFG and DLPC, while it was significant only in DLPC area for svPPA. The clinical impression of change variable was found significant for IFG and DLPC for both svPPA and nfvPPA. There were also two more significant variables in DLPC for nfvPPA in naming (latency) and repetition. In the case of svPPA, we also found significant changes in reading accuracy in IFG and DLPC areas.

Table 3.

GLMM analysis for patients.

Area	Variable	PPAnfv	PPAsv
Area	Variable	p	p
IFG	Words per minute	0 . 002	0.087
	Naming accuracy	0.929	0.952
	Latency denomination	0.478	0.296
	Dysdiadochokinesia	0.731	1
	Reading accuracy	0.737	0.007
	Reading efficiency	0.436	0.826
	Repetition	0.178	0.620
	Clinical imp. of change	0.0001	0.036
DLPC	Words per minute	0.005	0.019
	Naming accuracy	0.458	0.986
	Latency denomination	0.031	0.534
	Dysdiadochokinesia	0.701	0.908
	Reading accuracy	0.374	0.01
	Reading efficiency	0.129	0.91
	Repetition	0.002	0.752
	Clinical imp. of change	0.0001	0.001
Vertex	Words per minute	0.037	0.055
	Naming accuracy	0.148	1
	Latency denomination	0.102	0.685
	Dysdiadochokinesia	0.210	0.818
	Reading accuracy	0.433	0.405
	Reading efficiency	0.870	0.879
	Repetition	0.250	0.615
	Clinical imp. of change	0.684	0.142

Statistically significant p-values are shown in bold.

Connected speech analysis

The Kaiser-Meyer-Olkin measure of sampling adequacy was 0.6. Bartlett’ test of sphericity yielded a statistically significant value (4967.69, p < 0.001). Regarding EFA, the Tucker-Lewis index value was 0.328, root mean squared residuals (RMSR) was 0.04, with a mean item complexity of 2.1. According to the parallel analysis scree plot, we retained 3 factors, which explained 56% of the variance. The first factor (productivity) included the percentage of speech, the number of words with mazes and without mazes, R Guiraud, the number and duration of pauses, and the number of periphrasis. This factor explained 27.85% of the variance. The second component (lexical access) loaded on the percentage of false starts and reformulations, use of fillers, and the number of repetitions. This factor accounted for 19.79% of the variance. The third factor (verb production) comprised the number of verbs (copulatives, predicatives, and the percentage of copulative verbs), and explained 13.32% of variance.

For the first factor, we found a statistically significant improvement in svPPA after DLPC stimulation. For the second factor, there was a significant effect in the nfvPPA for DLPC stimulation. Finally, for the third factor, we found significant changes when stimulating the three targets in the svPPA (IFG, DLPC, and vertex) (Table 4).

Table 4.

Results from the GLMM applied to the factor analysis on the second dataset.

Area	Variable	PPAnfv	PPAsv
Area	Variable	p	p
IFG	Factor 1	0.443	0.093
	Factor 2	0.444	0.403
	Factor 3	0.898	0 . 005
DLPC	Factor 1	0.475	0.048
	Factor 2	0.044	0.414
	Factor 3	0.099	0.002
Vertex	Factor 1	0.974	0.066
	Factor 2	0.464	0.351
	Factor 3	0.356	0.030

The table illustrates the significance of each factor across different areas and PPA subtypes. Statistically significant p-values are shown in bold.

Discussion

In this study, we evaluated the effects of a single session of excitatory rTMS over the left IFG and the left DLPC, aiming to contribute to the characterization of the best brain targets in patients with PPA. Patients were evaluated using several language tasks (connected speech, naming, repetition, reading and diadochokinesia) and a clinical scale of subjective change. According to our hypothesis, we found a different response to rTMS over the IFG and DLPC in nfvPPA and svPPA. Specifically, IFG produced only significant changes in patients with nfvPPA (in words per minute and in the clinical impression of change), but not in svPPA. Regarding DLPC, we found an improvement in naming latency and in the clinical impression of change in svPPA, and in words per minute, repetition, and naming latency for nfvPPA. These changes were not elicited by vertex stimulation, which confirmed the effects of active stimulation compared with the control site. The analysis of connected speech also revealed differential effects in each target and according to each variant.

These findings have implications for the selection of brain targets for brain stimulation. In PPA, most of the studies with brain stimulation have used tES, with different protocols (e.g. anodal stimulation over the inferior frontal gyrus, left parietotemporal junction, or anterior temporal lobe).^5,25 In the case of TMS, this decision could be even more important due to the characteristics of the technique. TMS is a more focal and precise technique than tDCS. It uses magnetic fields to induce electrical currents, and the main effect is thought to be produced by the activation of the cortex located beneath the coil, followed by secondary activation of pathways connected through the white matter.^26,27 In our study using 15 sessions of TMS,⁶ we tried to personalize the target. However, this pre-treatment phase according to the immediate behavioral effects may be challenging to implement in practice, and for this reason, the knowledge of the general response as a group analyzed in this study may be of more interest. In this regard, our study suggests that DLPC could be an adequate target independently of the variant of PPA. However, at the same time, due to the clinical and topographical heterogeneity of PPA and the various factors that could impact the success of therapy (e.g. the extent and staging of the neurodegenerative process), the preference for DLPC should be regarded only as a general guideline in PPA. The search for the personalization of the therapy, the factors impacting on the response and the best methods for implementing the individualization of the treatment (e.g. neuroimaging or neurophysiological analysis, brain mapping with TMS,²⁸ electric field computation, brain twins, etc.²⁹) would be of interest in order to maximize the effect of brain stimulation. Additionally, the more positive results with DLPC in both PPA variants raise the question about the optimal target considering the lesion location. Our study could suggest that perilesional or even distant targets to the most affected regions may be more useful in PPA, because the DLPC is not early involved in nfvPPA and svPPA.

We performed an EFA to reduce the dimensionality of the connected speech variables, because many of them are highly correlated. In this analysis, the first factor was mainly associated with productivity in terms of quantity (percentage of speech, number of words, pause duration) and quality (lexical diversity, periphrasis); the second factor was more associated with the ability to access to the phonological lexicon (false starts, fillers, repetitions) and fluency; and the third factor was more related with the number of verbs, which is related to the number of sentences. According to this analysis, the main changes occurred with DLPC, having some effects for the first component in svPPA, and the second component in the nfvPPA. The differential effect observed in the nfvPPA and svPPA is consistent with the language characteristics expected in these disorders. On the one hand, brain stimulation would improve productivity and lexical diversity in svPPA patients, which show an impairment in the ventral (lexical-semantic) pathways. On the other hand, it would promote phonological processing, which is impaired in nfvPPA. Regarding the third component, the number of verbs is more associated with the number of sentences, and it is not a measure of the complexity of the sentences. Although we cannot draw clear conclusions, because there was a general effect for the three targets including the vertex, the effect could be caused by some learning effects.

Our findings have also interest in terms of knowing the effects of rTMS in each clinical variant. On the one hand, nfvPPA showed a response mainly in words per minute (spontaneous speech), repetition of non-words (as a measure of phonology), and naming latency. Other tasks such as naming accuracy, which is more preserved in nfvPPA, or dysdiadochokinesia, which is only affected in a subgroup of patients with nfvPPA, showed no significant changes. On the other hand, svPPA showed a positive effect on confrontation naming, which is one of the most impaired functions. Due to the differential impairment in language functions between PPA variants, and even the heterogeneity between patients,³⁰ these results have interest in the selection of outcomes to evaluate the efficacy of the interventions in PPA.

In this regard, one interesting finding was the significant effect on the subjective impression of change. As the changes in the clinical impression of change seems to be greater than in the individual language tasks, this may suggest that rTMS is producing other effects beyond language. For instance, the effects on behavioral (e.g. apathy) or other cognitive domains could also be relevant.^6,31 Indeed, the use of this type of scales capturing the perception of family and caregivers has been emphasized and recommended and may have favorable ecological properties. Considering the well-known effects of rTMS in depression, this could be another mechanism of improvement. However, due to the low frequency of significant depression in our sample, this does not seem to be the main reason. Nevertheless, a more comprehensive examination of the depressive symptoms and the relationship between behavioral changes and clinical improvement may be of interest to further know the mechanisms associated with clinical change.

Our study has some limitations. First, due to the low frequency of PPA, our study included a relatively small sample size. Due to this fact and the normal variability in the behavioral responses in patients, we cannot exclude a type II error. Additionally, we did not include patients with lvPPA. Second, although these patients were also tested for other brain targets, we included only those that were examined in all the patients. However, both the DLPC and the IFG are considered the most relevant in the previous literature, while the use of the other targets (e.g. left superior frontal gyrus, anterior temporal lobe) was more anecdotical. Third, although these findings are suggestive of the responsiveness of each brain region to the effects of rTMS, specific studies using complete protocols of several sessions of brain stimulation should be done to confirm the best target. In addition, it is important to emphasize the heterogeneity of PPA and the existence of mixed phenotypes not meeting the specific criteria of one of the three main variants.³² Future studies searching for individual markers of response beyond the specific variant should also be of interest.

In conclusion, our study showed a differential effect of one session of brain stimulation over two different targets in patients with nfvPPA and svPPA. These findings suggest that the selection of the target of stimulation may have important implications for the success of the technique. Among IFG and DLPC, the latter seems to elicit a more important effect in both PPA variants, suggesting that this could be a more adequate target for clinical trials.

Supplemental Material

sj-docx-1-alz-10.1177_13872877251315182 - Supplemental material for Effects of single-session repetitive transcranial magnetic stimulation to identify the optimal brain target in primary progressive aphasia

Supplemental material, sj-docx-1-alz-10.1177_13872877251315182 for Effects of single-session repetitive transcranial magnetic stimulation to identify the optimal brain target in primary progressive aphasia by Carlos Moral-Rubio, Paz Suárez-Coalla, Lucia Fernandez-Romero, Carlos Pérez-Izquierdo, Alfonso Delgado-Alvarez, Cristina Delgado-Alonso, Maria Jose Gil-Moreno, Jorge Matias-Guiu, Vanesa Pytel, José L Ayala and Jordi A Matias-Guiu in Journal of Alzheimer's Disease

Footnotes

Acknowledgements

We are grateful to all the participants and their caregivers for their interest in our study.

ORCID iDs

Carlos Moral-Rubio

Paz Suárez-Coalla

Lucia Fernandez-Romero

Carlos Pérez-Izquierdo

Alfonso Delgado-Alvarez

Cristina Delgado-Alonso

Jorge Matias-Guiu

Vanesa Pytel

José L Ayala

Jordi A Matias-Guiu

Author contribution(s)

Carlos Moral-Rubio: Formal analysis; Investigation; Methodology; Visualization; Writing – original draft; Writing – review & editing.

Paz Suarez-Coalla: Data curation; Investigation; Writing – review & editing.

Lucia Fernandez-Romero: Data curation; Investigation; Writing – review & editing.

Carlos Perez-Izquierdo: Investigation; Methodology; Software; Writing – review & editing.

Alfonso Delgado-Alvarez: Data curation; Investigation; Writing – review & editing.

Cristina Delgado-Alonso: Data curation; Investigation; Writing – review & editing.

Maria Jose Gil-Moreno: Investigation; Writing – review & editing.

Jorge Matias-Guiu: Funding acquisition; Resources; Writing – review & editing.

Vanesa Pytel: Conceptualization; Data curation; Investigation; Project administration; Writing – review & editing.

Jose L Ayala: Conceptualization; Formal analysis; Methodology; Supervision; Writing – review & editing.

Jordi A Matias-Guiu: Conceptualization; Data curation; Funding acquisition; Investigation; Methodology; Project administration; Writing – original draft; Writing – review & editing.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: Jordi A. Matias-Guiu is supported by Instituto de Salud Car- los III through the project INT20/00079 and INT23/00017 (co-funded by European Regional Development Fund “A way to make Europe”). The research group was provided with a research Salud Carlos III during the execution of the project (PTA 17/13618).

Declaration of conflicting interests

The authors declared the following potential conflicts of interestwith respect to the research, authorship, and/or publication of this article: Jordi A Matias-Guiu is an Editorial Board member of this journal but was not involved in the peer-review process of this article nor had access to any information regarding its peer-review. The remaining authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

The dataset is available from the corresponding author upon reasonable request.

Supplemental material

Supplemental material for this article is available online.

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