In　this　paper,　we　use　the　structural　parameters　of　the　gene　correlation　network　to　study　the　pathogenesis.　Based　on　the　data　of　gene　expression　profile　(experimental　group　and　control　group),　their　correlation　networks　are　established,　and　the　structural　parameters　of　networks　under　different　thresholds　are　analyzed,　in　order　to　find　that　the　structural　parameters　of　the　control　group　(C)　and　the　experimental　group　(E)　are　significantly　different　within　the　full　threshold.　This　indicates　that　there　are　clear　differences　in　the　gene　network　structure　between　C　and　E,　and　also　reveales　that　the　differences　are　related　to　the　mechanism　of　the　disease.　Furthermore,　the　genes　with　the　greatest　contribution　to　structural　parameters　are　selected　as　the　key　genes,　and　their　functional　mechanism　could　be　obtained　by　analyzing　their　annotation.　As　an　example,　this　paper　mainly　establishes　two　kinds　of　Pearson　correlation　networks　based　on　the　gene　expression　profile　data　of　30　patients　with　idiopathic　pulmonary　hypertension　(PAH)　(the　experimental　group,　E)　and　41　healthy　people　(the　control　group,　C)　from　GSE33463　in　NCBI　database,　analyzes　the　average　clustering　coefficient　of　the　two　kinds　of　networks　under　different　thresholds.　By　annotating　the　first　50　genes　(structural　key　genes)　that　contribute　greatly　to　the　difference　of　the　average　clustering　coefficient,　we　find　that　they　are　mainly　related　to　cancer,　blood　vessels,　immunity　and　apoptosis,　which　are　consistent　with　the　conclusion　of　pathological　research　literature.　Therefore,　it　is　of　great　significance　to　study　the　mechanism　of　gene　level　of　pulmonary　hypertension　by　network　structure　parameter　analysis.