Disease state fingerprint in frontotemporal degeneration with reference to alzheimer's disease and mild cognitive impairment

Miguel Ángel Muñoz-Ruiz, Päivi Hartikainen, Annette Hall, Jussi Mattila, Juha Koikkalainen, Sanna-Kaisa Herukka, Valtteri Julkunen, Ritva Vanninen, Yawu Liu, Jyrki Lötjönen, Hilkka Soininen (Corresponding Author)

Research output: Contribution to journalArticleScientificpeer-review

16 Citations (Scopus)

Abstract

Background: Disease State Index and Disease State Fingerprint represent a novel tool which collates data information from different sources, helping the clinician in the diagnosis and follow-up of dementia diseases. It has been demonstrated that it is applicable in the diagnosis of Alzheimer’s disease (AD). Objective: We applied this novel tool to classify frontotemporal dementia (FTD) cases in comparison with controls, AD, and mild cognitive impairment (MCI) subjects. Methods: Thirty seven patients with FTD, 35 patients with AD, 26 control subjects, and 64 subjects with MCI were included in the study. The Disease State Index encompassed data from cognitive performance assessed by Mini-Mental State Examination, cerebrospinal fluid biomarkers, MRI volumetric and morphometric parameters as well as APOE genotype. Results: We applied the Disease State Index for comparisons at the group level. The data showed that FTD patients could be differentiated with a high accuracy, sensitivity, and specificity from controls (0.84, 0.84, 0.83) and from MCI (0.79, 0.78, 0.80). However, the correct accuracy was lower in the FTD versus AD comparison (0.69, 0.70, 0.71). In addition, we demonstrated the use of Disease State Fingerprint by comparing one particular FTD case with control, AD, and MCI population data. Conclusion: The results suggest that the Disease State Fingerprint and the underlying Disease State Index are particularly useful in differentiating between normal status and disease in patients with dementia, but it may also help to distinguish between the two dementia diseases, FTD and AD.
Original languageEnglish
Pages (from-to)727-739
JournalJournal of Alzheimer's Disease
Volume35
Issue number4
DOIs
Publication statusPublished - 2013
MoE publication typeA1 Journal article-refereed

Fingerprint

Dermatoglyphics
Alzheimer Disease
Frontotemporal Dementia
Dementia
Cognitive Dysfunction
Cerebrospinal Fluid
Biomarkers
Genotype
Sensitivity and Specificity

Keywords

  • Alzheimer's disease
  • cognition
  • frontotemporal dementia
  • memory
  • mild cognitive imparirment

Cite this

Muñoz-Ruiz, M. Á., Hartikainen, P., Hall, A., Mattila, J., Koikkalainen, J., Herukka, S-K., ... Soininen, H. (2013). Disease state fingerprint in frontotemporal degeneration with reference to alzheimer's disease and mild cognitive impairment. Journal of Alzheimer's Disease, 35(4), 727-739. https://doi.org/10.3233/JAD-122260
Muñoz-Ruiz, Miguel Ángel ; Hartikainen, Päivi ; Hall, Annette ; Mattila, Jussi ; Koikkalainen, Juha ; Herukka, Sanna-Kaisa ; Julkunen, Valtteri ; Vanninen, Ritva ; Liu, Yawu ; Lötjönen, Jyrki ; Soininen, Hilkka. / Disease state fingerprint in frontotemporal degeneration with reference to alzheimer's disease and mild cognitive impairment. In: Journal of Alzheimer's Disease. 2013 ; Vol. 35, No. 4. pp. 727-739.
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abstract = "Background: Disease State Index and Disease State Fingerprint represent a novel tool which collates data information from different sources, helping the clinician in the diagnosis and follow-up of dementia diseases. It has been demonstrated that it is applicable in the diagnosis of Alzheimer’s disease (AD). Objective: We applied this novel tool to classify frontotemporal dementia (FTD) cases in comparison with controls, AD, and mild cognitive impairment (MCI) subjects. Methods: Thirty seven patients with FTD, 35 patients with AD, 26 control subjects, and 64 subjects with MCI were included in the study. The Disease State Index encompassed data from cognitive performance assessed by Mini-Mental State Examination, cerebrospinal fluid biomarkers, MRI volumetric and morphometric parameters as well as APOE genotype. Results: We applied the Disease State Index for comparisons at the group level. The data showed that FTD patients could be differentiated with a high accuracy, sensitivity, and specificity from controls (0.84, 0.84, 0.83) and from MCI (0.79, 0.78, 0.80). However, the correct accuracy was lower in the FTD versus AD comparison (0.69, 0.70, 0.71). In addition, we demonstrated the use of Disease State Fingerprint by comparing one particular FTD case with control, AD, and MCI population data. Conclusion: The results suggest that the Disease State Fingerprint and the underlying Disease State Index are particularly useful in differentiating between normal status and disease in patients with dementia, but it may also help to distinguish between the two dementia diseases, FTD and AD.",
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Muñoz-Ruiz, MÁ, Hartikainen, P, Hall, A, Mattila, J, Koikkalainen, J, Herukka, S-K, Julkunen, V, Vanninen, R, Liu, Y, Lötjönen, J & Soininen, H 2013, 'Disease state fingerprint in frontotemporal degeneration with reference to alzheimer's disease and mild cognitive impairment', Journal of Alzheimer's Disease, vol. 35, no. 4, pp. 727-739. https://doi.org/10.3233/JAD-122260

Disease state fingerprint in frontotemporal degeneration with reference to alzheimer's disease and mild cognitive impairment. / Muñoz-Ruiz, Miguel Ángel; Hartikainen, Päivi; Hall, Annette; Mattila, Jussi; Koikkalainen, Juha; Herukka, Sanna-Kaisa; Julkunen, Valtteri; Vanninen, Ritva; Liu, Yawu; Lötjönen, Jyrki; Soininen, Hilkka (Corresponding Author).

In: Journal of Alzheimer's Disease, Vol. 35, No. 4, 2013, p. 727-739.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Disease state fingerprint in frontotemporal degeneration with reference to alzheimer's disease and mild cognitive impairment

AU - Muñoz-Ruiz, Miguel Ángel

AU - Hartikainen, Päivi

AU - Hall, Annette

AU - Mattila, Jussi

AU - Koikkalainen, Juha

AU - Herukka, Sanna-Kaisa

AU - Julkunen, Valtteri

AU - Vanninen, Ritva

AU - Liu, Yawu

AU - Lötjönen, Jyrki

AU - Soininen, Hilkka

PY - 2013

Y1 - 2013

N2 - Background: Disease State Index and Disease State Fingerprint represent a novel tool which collates data information from different sources, helping the clinician in the diagnosis and follow-up of dementia diseases. It has been demonstrated that it is applicable in the diagnosis of Alzheimer’s disease (AD). Objective: We applied this novel tool to classify frontotemporal dementia (FTD) cases in comparison with controls, AD, and mild cognitive impairment (MCI) subjects. Methods: Thirty seven patients with FTD, 35 patients with AD, 26 control subjects, and 64 subjects with MCI were included in the study. The Disease State Index encompassed data from cognitive performance assessed by Mini-Mental State Examination, cerebrospinal fluid biomarkers, MRI volumetric and morphometric parameters as well as APOE genotype. Results: We applied the Disease State Index for comparisons at the group level. The data showed that FTD patients could be differentiated with a high accuracy, sensitivity, and specificity from controls (0.84, 0.84, 0.83) and from MCI (0.79, 0.78, 0.80). However, the correct accuracy was lower in the FTD versus AD comparison (0.69, 0.70, 0.71). In addition, we demonstrated the use of Disease State Fingerprint by comparing one particular FTD case with control, AD, and MCI population data. Conclusion: The results suggest that the Disease State Fingerprint and the underlying Disease State Index are particularly useful in differentiating between normal status and disease in patients with dementia, but it may also help to distinguish between the two dementia diseases, FTD and AD.

AB - Background: Disease State Index and Disease State Fingerprint represent a novel tool which collates data information from different sources, helping the clinician in the diagnosis and follow-up of dementia diseases. It has been demonstrated that it is applicable in the diagnosis of Alzheimer’s disease (AD). Objective: We applied this novel tool to classify frontotemporal dementia (FTD) cases in comparison with controls, AD, and mild cognitive impairment (MCI) subjects. Methods: Thirty seven patients with FTD, 35 patients with AD, 26 control subjects, and 64 subjects with MCI were included in the study. The Disease State Index encompassed data from cognitive performance assessed by Mini-Mental State Examination, cerebrospinal fluid biomarkers, MRI volumetric and morphometric parameters as well as APOE genotype. Results: We applied the Disease State Index for comparisons at the group level. The data showed that FTD patients could be differentiated with a high accuracy, sensitivity, and specificity from controls (0.84, 0.84, 0.83) and from MCI (0.79, 0.78, 0.80). However, the correct accuracy was lower in the FTD versus AD comparison (0.69, 0.70, 0.71). In addition, we demonstrated the use of Disease State Fingerprint by comparing one particular FTD case with control, AD, and MCI population data. Conclusion: The results suggest that the Disease State Fingerprint and the underlying Disease State Index are particularly useful in differentiating between normal status and disease in patients with dementia, but it may also help to distinguish between the two dementia diseases, FTD and AD.

KW - Alzheimer's disease

KW - cognition

KW - frontotemporal dementia

KW - memory

KW - mild cognitive imparirment

U2 - 10.3233/JAD-122260

DO - 10.3233/JAD-122260

M3 - Article

VL - 35

SP - 727

EP - 739

JO - Journal of Alzheimer's Disease

JF - Journal of Alzheimer's Disease

SN - 1387-2877

IS - 4

ER -