Extended Data Fig. 2: Association between NEFL or NEFM brain protein and cerebral atherosclerosis, AD.
From: Shared proteomic effects of cerebral atherosclerosis and Alzheimer’s disease on the human brain
(a) Boxplot of dorsolateral prefrontal cortex NEFL protein level for each level of CA (that is, none to severe). NEFL protein levels were identified as associated with CA using linear regression adjusted for relevant covariates and 8 other pathologies (N = 375; p = 0.0002; adjusted p = 0.034; Fig. 1). (b) Boxplot of dorsolateral prefrontal cortex NEFL protein level by clinical diagnosis (that is, cognitive normal control [control], mild cognitive impairment [MCI], and AD). MCI is generally regarded as an intermediate stage between cognitively normal and AD. NEFL protein levels were identified as associated with AD by logistic regression adjusted for relevant covariates (N = 383; p = 0.0025; adjusted p = 0.0322; Fig. 1). (c) Boxplot of dorsolateral prefrontal cortex NEFM protein level for each level of CA (that is, none to severe). NEFM protein levels were identified as associated with CA using linear regression adjusted for relevant covariates and 8 other pathologies (N = 375; p = 0.0006; adjusted p = 0.045). (d) Boxplot of dorsolateral prefrontal cortex NEFM protein level by clinical diagnosis (that is, cognitive normal control [control], mild cognitive impairment [MCI], and AD). NEFM protein levels were identified as associated with AD by logistic regression adjusted for relevant covariates (N = 383; p = 0.0019; adjusted p = 0.028). For each boxplot, the box reflects the first and third quartile, the dark horizontal line reflects the median, the vertical lines extending from the boxes show the 1.5x the interquartile range, and points beyond the lines are outliers. (e) Proteome-wide adjusted p-values for associations between NEFL and NEFM brain protein levels and each of the 9 measured pathologies adjusting for the remaining 8 measured pathologies. Associations were tested with regression and the provided p-values were adjusted for multiple testing using Benjamin-Hochberg false discovery rate.
