Project Details
Projekt
Frequency of cerebral energy-metabolic anomalies in autism spectrum disorder - a tool for subgroup definition?
Subject Area
Biological Psychiatry
Term
from 2017 to 2022
Project identifier
Deutsche Forschungsgemeinschaft (DFG) - Project number 392072482
Individuals diagnosed with Autism Spectrum Disorder (ASD) are severely challenged in situations of social communication and interaction. Behavioral inflexibility together with problems in social communication often cause severe distress affecting various areas of their lives. ASD is regarded as a severe neurodevelopmental condition of organic origin that has strong genetic influences. But, in spite of the high number of studies reporting differences in magnetic-resonance (MR), genetic, and physiological signals, no common etiological factors or at least biological markers of ASD could be identified so far. Definite etiologies of the ASD syndrome have only been described for miscellaneous, but very small subgroups mostly of rare genetic variants. In most ASD cases, however, the genetic influence is very complex and diverse, which led to the view of ASD as the behavioral manifestation of hundreds of genetic and genomic conditions, often in interaction with mostly unknown environmental determinants. This heterogeneity of etiologies is thought to converge down-stream into an autistic connectivity pattern of information processing affecting the communication between remote neuronal circuits, which finally manifests in the autistic phenotype. Input about the question how the autistic connectivity pattern emerges arrives from various scientific fields, reporting anatomical, metabolic, immunologic, and neurotransmitter anomalies to compromise cerebral information processing. Most of these signals apply only to subgroups and are not very specific. Nevertheless, they constitute an important tool in the endeavor to relate different pathogenetic pathways to the underlying genetic variants. Similar to the definition of diagnostic subtypes, commonalities on the genetic, molecular, neuronal, and behavioral levels should lead to the definition of respective subgroups. Such subgroups, which are ideally defined by objective marker signals, can build the basis to link etiological upstream factors to downstream symptoms. For this linkage, midstream markers at a level where several different pathomechanistic pathways of different etiologies converge play an important role. One promising converging midstream marker defining a putative pathogenetic subgroup of ASD is energy metabolism. The objective of the proposed study is to measure both cerebral and serum lactate concentrations as a proxy-measure of perturbed energy metabolism in individuals with ASD and to evaluate its potential as a marker of insufficient mitochondrial functioning in a subpopulation of adults with ASD. We will employ the method of 3D MEGA- spectroscopic imaging (MEGA-SI), which allows the in vivo assessment of cerebral lactate with unprecedented sensitivity across various brain areas. Specifically, we will investigate whether MEGA-SI is a clinically feasible tool for identifying subgroups of ASD patients with evidence of disturbed energy metabolism.
DFG Programme
Research Grants
