Identifying causal genes for migraine by integrating the proteome and transcriptome.

BACKGROUND: While previous genome-wide association studies (GWAS) have identified multiple risk variants for migraine, there is a lack of evidence about how these variants contribute to the development of migraine. We employed an integrative pipeline to efficiently transform genetic associations to identify causal genes for migraine. METHODS: We conducted a proteome-wide association study (PWAS) by combining data from the migraine GWAS data with proteomic data from the human brain and plasma to identify proteins that may play a role in the risk of developing migraine. We also combined data from GWAS of migraine with a novel joint-tissue imputation (JTI) prediction model of 17 migraine-related human tissues to conduct transcriptome-wide association studies (TWAS) together with the fine mapping method FOCUS to identify disease-associated genes. RESULTS: We identified 13 genes in the human brain and plasma proteome that modulate migraine risk by regulating protein abundance. In addition, 62 associated genes not reported in previous migraine TWAS studies were identified by our analysis of migraine using TWAS and fine mapping. Five genes including ICA1L, TREX1, STAT6, UFL1, and B3GNT8 showed significant associations with migraine at both the proteome and transcriptome, these genes are mainly expressed in ependymal cells, neurons, and glial cells, and are potential target genes for prevention of neuronal signaling and inflammatory responses in the pathogenesis of migraine. CONCLUSIONS: Our proteomic and transcriptome findings have identified disease-associated genes that may give new insights into the pathogenesis and potential therapeutic targets for migraine.

[Validation of ABCD3 score in the predication of stroke risk after transient ischemic attack].

UNLABELLED: Objective To explore the evaluation of ABCD(3) score in the prediction of stroke risk after transient ischemic attack and the influencing factors of early stroke risks. METHODS: From October 2010 to September 2012, the data were prospectively collected from patients with transient ischemic attack according to the World Health Organization time-based criteria. ABCD(2) and ABCD(3) scores were available within 7 days of index transient ischemic attack. The predictive outcome was stroke occurrence at 90 days. Risks of stroke stratified according to the score were analysed by Logistic regression. And ABCD(2) and ABCD(3) model were compared by AUROCC. RESULTS: Among 321 eligible patients, 4 cases were lost to follow-up. There were 38(11.8%) patients with ischemic stroke during a 90-day follow-up, including 22(57.9%) males, 16(42.1%) females. There were no occurrence of death, no hemorrhagic stroke. Multivariate analysis revealed that dual TIA (OR = 4.116, 95%CI 1.284-3.195) , history of stroke (OR = 4.022, 95%CI 1.472-10.944) and unilateral weakness (OR = 3.117, 95%CI 1.222-7.948) were the risk factors of early stroke. The ABCD(3) score (0.733, 95% CI,0.0.681-0.780) was statistically higher than that of ABCD(2) score (0.674, 95%CI, 0.619-0.725) (P < 0.05). CONCLUSION: ABCD(3) may effectively predict early risk of stroke after TIA.