Characteristics of Participants in CABLE Study
We included 651 non-demented elders from the CABLE study consisting of 457 CN controls (238 women, 60.54 ± 10.46 years) and 194 MCI patients (109 women, 63.6 ± 9.72 years) (Table 1). CN individuals were younger and more educated. CSF p-tau and t-tau levels were higher in MCI patients than CN individuals.
CSF α-synuclein and Established AD Biomarkers in CABLE Study
In CABLE study, we examined the concentrations of CSF α-synuclein and other established AD biomarkers (CSF Aβ, p-tau and t-tau) and tested their relationships (Table 2). We found that high CSF α-synuclein level is associated with high CSF t-tau (β = 0.56, P < 0.001) and p-tau (β = 0.35, P < 0.001) among nondemented subjects. However, there were no associations between CSF α-synuclein and CSF Aβ level at baseline. We also tested these relationships in subgroups. The results were the same in the CN group (CSF t-tau: β = 0.38, P < 0.001, CSF p-tau: β = 0.27, P < 0.001) and MCI group (CSF t-tau: β = 0.67, P < 0.001, CSF p-tau: β = 0.4, P < 0.001).
Characteristics of Participants in ADNI
Three hundred and eighty-two subjects from the ADNI database were included (Table 3). This cohort consisted of 109 CN controls (54 women, 75.63 ± 5.22 years), 117 sMCI patients (37 women, 74.34±7.60 years), 66 pMCI patients (25 women, 74.21± 7.58 years) and 90 AD patients (39 women, 74.89±7.72 years). According to the new “ATN” scheme, 258 A+ (220 A+T+) patients and 124 A- (96 A-T-) controls were included. As expected, the AD group had the highest frequency of the ε4 allele within APOE gene (69.23%) and the CN controls group had the lowest frequency (23.85%). There was no significant difference in educational level (P = 0.16) and age (P = 0.53) among these four groups. Furthermore, AD patients had lower MMSE scores compare with MCI patients and CN controls (P < 0.01).
CSF α-synuclein and Established AD Biomarkers in ADNI
In ADNI database, we found that high CSF α-synuclein levels were associated with high CSF t-tau (β = 0.27, P < 0.001) and p-tau (β = 0.36, P < 0.001) in the whole cohort. However, there was no association between CSF α-synuclein and CSF Aβ level at baseline. The same results were obtained in the MCI group (CSF t-tau: β = 0.29, P = < 0.001, CSF p-tau: β = 0.33, P < 0.001) and CN controls (CSF t-tau: β = 0.2, P = < 0.001, CSF p-tau: β = 0.32, P < 0.001). We also tested the association between CSF α-synuclein and CSF/plasma NFL concentration. As a result, CSF α-synuclein concentration was associated with CSF NFL concentration in non-demented elders (β= 0.12, P <0.001). However, there was no association between CSF α-synuclein and plasma NFL (Table 4, Fig. S1).
CSF α-synuclein in Different Diagnostic Groups in ADNI
With the advance of the disease stage, the level of CSF α-synuclein showed a rising trend. The CSF α-synuclein concentration was significantly higher in the AD and pMCI groups compared with CN controls (P < 0.0001 and P < 0.001 respectively). Higher CSF α-synuclein levels were also detected in the AD and pMCI groups compared with the sMCI group (P = 0.02 and P = 0.04, respectively) (Fig. 1A). We continued to compare CSF α-synuclein concentration among A- controls, A+ controls, A- patients with MCI, A+ patients with MCI and A+ patients with AD dementia (Fig. 1B). The A+ AD group had higher CSF α-synuclein levels than those of A- controls (P < 0.001), A+ controls (P < 0.001), and A- MCI group (P < 0.001). The A+ MCI had higher CSF α-synuclein levels than those of A- controls (P < 0.01), A+ controls (P < 0.01), and A- MCI group (P = 0.02). We further compared the CSF α-synuclein level between the A+T+ group with the A-T- group, which showed differences with more significant statistical power (P < 0.0001) (Fig. 1C).
We performed receiver-operating curves based on the logistic regression models adjusted for age at baseline, gender, educational level and APOE ε4 genotype to assess the predictive value of CSF α-synuclein and its combination with other established AD biomarkers in the risk of conversion to AD. The area under the curve (AUC) of the base model containing CSF α-synuclein, age at baseline, gender, educational level and APOE ε4 genotype was 0.76 in predicting the onset of AD among CN controls, and AUC was increased by the inclusion of CSF tau/Aβ ratio (AUC = 0.88) (Fig. S2). Consistent with expectation, the base model showed similar predicting value in the onset of pMCI among CN controls (Fig. S3). In the A- group, this base model showed pretty good predictive value in the risk of conversion to A+ status (AUC = 0.77). This value became greater when combined with CSF t-tau (AUC = 0.88) and p-tau (AUC = 0.92) (Fig. S4). Furthermore, when the participants were grouped according to both Aβ deposition and pathology, the base model showed the best performance (AUC = 0.84). We also detected that CSF α-synuclein added value in diagnosis prediction (Fig. S5).
CSF α-synuclein and Longitudinal Neuroimaging Change and Progression in ADNI
Next, the linear mixed-effects models were utilized to test the associations between baseline CSF α-synuclein concentration and subsequent disease progression adjusted for age, gender, educational level, diagnosis, and APOE ε4 genotype. A Significant association of baseline CSF α-synuclein concentration with hippocampus volume was identified (β = -0.008, P = 0.001 longitudinally) (Table 4, Fig. 2A).
Fig. 2B presents the results of a Kaplan-Meier analysis. The cox proportional hazards model was developed to estimate the predictive value of CSF α-synuclein in the conversion risk from MCI to incident AD dementia, controlling for baseline age, gender and years of education. MCI individuals with high CSF α-synuclein levels would satisfy the diagnostic criteria for AD at a comparatively earlier interval (HR 2.79, 95% CI 1.14 to 6.9, P = 0.03) (Table 4).