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Biomarkers identification in Alzheimer’s disease using effective connectivity analysis from electroencephalography recordings
Identificación de biomarcadores en la enfermedad de Alzheimer usando análisis de conectividad efectiva a partir de registros de electroencefalografía
Keywords:
Familial Alzheimer disease, Electroencephalography, Effective connectivity, Brain graphs (en)Enfermedad de Alzheimer familiar, Electroencefalografía, Conectividad efectiva, Grafos cerebrales (es)
Alzheimer’s disease (AD) is the most common cause of dementia, which generally affects people over 65 years old. Some genetic mutations induce early onset of AD and help to track the evolution of the symptoms and the physiological changes at different stages of the disease. In Colombia there is a large family group with the PSEN1 E280A mutation with a median age of 46,8 years old for onset of symptoms. AD has been defined as a disconnection syndrome; consequently, network approaches could help to capture different features of the disease. The aim of the current work is to identify a biomarker in AD that helps in the tracking of the neurodegenerative process. Electroencephalography (EEG) was recorded during the encoding of visual information for four groups of individuals: asymptomatic and mild cognitive impairment carriers of the PSEN1 E280A mutation, and two non-carrier control groups. For each individual, the effective connectivity was estimated using the direct Directed Transfer Function and three measurements from graph theory were extracted: input strength, output strength and total strength. A relation between the cognitive status and age of the participants with the connectivity features was calculated. For those connectivity measures in which there is a relation with the age or the clinical scale, the performance as a diagnostic feature was evaluated. We found that output strength connectivity in the right occipito-parietal region is related to age of the carrier groups (r=−0,54, p=0,0036) and has a high sensitivity and high specificity to distinguish between carriers and non-carriers (67% sensitivity and 80% specificity in asymptomatic cases, and 83% sensitivity and 67% specificity in symptomatic cases). This relationship indicates that output strength connectivity could be related to the neurodegenerative process of the disease and could help to track the conversion from the asymptomatic stage to dementia.
La enfermedad de Alzheimer (EA) es la causa más común de demencia, la cual afecta generalmente a personas después de los 65 años de edad. Algunas mutaciones genéticas inducen la aparición temprana de EA ayudando a monitorear la evolución de los síntomas y los cambios fisiológicos en diferentes etapas de la enfermedad. En Colombia existe un gran grupo familiar con la mutación PSEN1 E280A, con una edad media de aparición de los síntomas de 46,8 años. La EA ha sido definida como un síndrome de desconexión; en consecuencia, enfoques de redes podrían ayudar a capturar diferentes características de la enfermedad. El objetivo del presente trabajo es identificar un biomarcador en la EA que permita realizar el seguimiento del proceso neurodegenerativo. Se registró una electroencefalografía (EEG) durante la codificación de información visual en cuatro grupos de sujetos: portadores de la mutación PSEN1 E280A asintomáticos y con deterioro cognitivo leve y dos grupos control de no portadores. Para cada sujeto se estimó la conectividad efectiva utilizando la Función de Transferencia Directa dirigida y se extrajeron tres medidas de grafos: fuerza de entrada, fuerza de salida y fuerza total. Se calculó una relación entre el estado cognitivo y la edad de los participantes con las características de conectividad.Para aquellas medidas de conectividad que tuvieran una relación con la edad o la escala clínica, se evaluó su desempeño como variable de diagnóstico. Se encontró que la fuerza de conectividad saliente en la región parieto-occipital derecha está relacionada con la edad del grupo de los portadores (r=−0,54, p=0,0036), y que tiene alta sensibilidad y especificidad para distinguir entre portadores y no portadores (67% de sensibilidad y 80% de especificidad en casos asintomáticos, y 83% de sensibilidad y 67% de especificidad en casos sintomáticos). Esta relación indica que la fuerza de conectividad saliente podría estar relacionada con el proceso neurodegenerativo de la enfermedad y podría ayudar a realizar un seguimiento de la conversión desde la etapa asintomática hacia la demencia.
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