Imaging genomics discovery of a new risk variant for Alzheimer's disease in the postsynaptic SHARPIN gene

Abstract

Molecular mechanisms underlying Alzheimer's disease (AD) are difficult to investigate, partly because diagnosis lags behind the insidious pathological processes. Therefore, identifying AD neuroimaging markers and their genetic modifiers may help study early mechanisms of neurodegeneration. We aimed to identify brain regions of the highest vulnerability to AD using a data‐driven search in the AD Neuroimaging Initiative (ADNI, n = 1,100 subjects), and further explored genetic variants affecting this critical brain trait using both ADNI and the younger UK Biobank cohort ( n = 8,428 subjects). Tensor‐Based Morphometry (TBM) and Independent Component Analysis (ICA) identified the limbic system and its interconnecting white‐matter as the most AD‐vulnerable brain feature. Whole‐genome analysis revealed a common variant in SHARPIN that was associated with this imaging feature (rs34173062, p = 2.1 × 10 −10 ). This genetic association was validated in the UK Biobank, where it was correlated with entorhinal cortical thickness bilaterally ( p = .002 left and p = 8.6 × 10 −4 right), and with parental history of AD ( p = 2.3 × 10 −6 ). Our findings suggest that neuroanatomical variation in the limbic system and AD risk are associated with a novel variant in SHARPIN. The role of this postsynaptic density gene product in β1‐integrin adhesion is in line with the amyloid precursor protein (APP) intracellular signaling pathway and the recent genome‐wide evidence.

Multivariate Analysis and Modelling of multiple Brain endOphenotypes: Let’s MAMBO!

“…The latent variables are assumed non-gaussian and mutually independent and they are called the independent components of the observed data. ICA is suitable to extract independent components from multiple phenotype measurements and it is extensively used in IG studies [21] , [22] , [23] . [22] performed a large scale multivariate ICA identifying significant imaging-genetic relationships for Alzheimer’s Disease (AD).…”

Reduced fronto-striatal volume in attention-deficit/hyperactivity disorder in two cohorts across the lifespan

“…Preprocessing for TBM was performed similar to previous analyses by our group ( Soheili‐Nezhad et al, 2020 ). All T1-weighted images were corrected for magnetic field bias using the N4 algorithm ( Tustison et al, 2010 ), and the brain field of view was cropped using the FSL standard_space_roi tool.…”

“…The Jacobian determinant maps of the NeuroIMAGE cohort (n = 890) were decomposed into spatially independent components using MELODIC, a probabilistic ICA method ( Beckmann, 2012 ), similar to previous studies by our group ( Llera et al, 2019 , Soheili‐Nezhad et al, 2020 ). Four decompositions were performed with varying dimensionality (25, 50, 100 and 200 components) to allow the identification of independent spatial sources in the Jacobian fields at various levels of spatial specificity.…”

Long genes are more frequently affected by somatic mutations and show reduced expression in Alzheimer's disease: Implications for disease etiology

“…The relevance of impaired synaptic processes in AD is further corroborated by the fact that synaptic loss is the strongest neuropathological correlate of cognitive decline in AD 28–30 . Of interest, genes that have been associated through GWASs with AD‐related brain phenotypes—for example, hippocampal volume and cerebrospinal fluid levels of phosphorylated tau—are also enriched for processes such as synaptic plasticity 31,32 . In addition, the familial AD genes APP and PSEN1/2 have roles in synaptogenesis, synaptic adhesion, and neurotransmission 27 .…”