Medical studies have confirmed the causal relationship between autism and brain areas. Such relationship can effectively promote the early diagnosis and timely intervention of autism. However, existing experiment-driven methods discovering such relationships are costly while machine-learning-based methods are ineffective, because they do not fully utilize the domain knowledge. In this paper, we propose a reasoning-reuse method to construct a Brain Areas-Autism (BAA) ontology to support the domain knowledge discovery, i.e., discovering inherent relationships between autism and brain areas based on BAA ontology. In our method, domain experts first design the schema of the ontology. Then, we use NLP techniques to extract and fuse knowledge from scientific literatures. Rule-based reasoning is performed to expand the scale of ontology. Finally, the ontology is evaluated using the qualitative and quantitative analysis. This paper constructs the BAA ontology with 929 entities and 1129 relationships. Based on this ontology, 130 potential relationships between brain areas and autism were inferred by rule-based reasoning. Experiments demonstrate that the proposed reasoning-reuse method can effectively construct BAA ontology which supports intelligent and efficient knowledge discovery and exploration in domain research.