During the first hours after stroke onset neurological deficits can be highly unstable: some patients rapidly improve, while others deteriorate. This early neurological instability has a major impact on long-term outcome. Here, we aimed to determine the genetic architecture of early neurological instability measured by the difference between NIH stroke scale (NIHSS) within six hours of stroke onset and NIHSS at 24 h (ΔNIHSS). A total of 5,876 individuals from seven countries (Spain, Finland, Poland, United States, Costa Rica, Mexico and Korea) were studied using a multi-ancestry meta-analyses. We found that 8.7% of ΔNIHSS variance was explained by common genetic variations, and also that early neurological instability has a different genetic architecture than that of stroke risk. Eight loci (1p21.1, 1q42.2, 2p25.1, 2q31.2, 2q33.3, 5q33.2, 7p21.2,and 13q31.1) were genome-wide significant and explained 1.8% of the variability suggesting that additional variants influence early change in neurological deficits. We used functional genomics and bioinformatic annotation to identify the genes driving the association from each loci. eQTL mapping and SMR indicate that ADAM23 (log Bayes Factor (LBF) = 5.41) was driving the association for 2q33.3. Gene based analyses suggested that GRIA1 (LBF = 5.19), which is predominantly expressed in brain, is the gene driving the association for the 5q33.2 locus. These analyses also nominated GNPAT (LBF = 7.64)ABCB5 (LBF = 5.97) for the 1p21.1 and 7p21.1 loci. Human brain single nuclei RNA-seq indicates that the gene expression of ADAM23 and GRIA1 is enriched in neurons. ADAM23, a pre-synaptic protein, and GRIA1, a protein subunit of the AMPA receptor, are part of a synaptic protein complex that modulates neuronal excitability. These data provides the first genetic evidence in humans that excitotoxicity may contribute to early neurological instability after acute ischemic stroke.
Objective: To determine whether the genetic architecture of sporadic late--onset Alzheimer's Disease (sLOAD) has an effect on familial late--onset AD (fLOAD), sporadic early--onset (sEOAD) and autosomal dominant early--onset (eADAD).Methods: Polygenic risk scores (PRS) were constructed using previously identified 21 genome--wide significant loci for LOAD risk.Results: We found that there is an overlap in the genetic architecture among sEOAD, fLOAD, and sLOAD. sEOAD showed the highest odds for the PRS (OR=2.27; p=1.29×10 --7 ), followed by fLOAD (OR=1.75; p=1.12×10 --7 ) and sLOAD (OR=1.40; p=1.21×10 --3 ). PRS is associated with cerebrospinal fluid ptau 181 --Aβ 42 on eADAD.Conclusion: Our analysis confirms that the genetic factors identified for sLOAD also modulate risk in fLOAD and sEOAD cohorts. Furthermore, our results suggest that the burden of these risk variants is associated with familial clustering and earlier--onset of AD. Although these variants are not associated with risk in the eADAD, they may be modulating age at onset.peer-reviewed)
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