Genetic discoveries of Alzheimer’s disease are the drivers of our understanding, and together with polygenetic risk stratification can contribute towards planning of feasible and efficient preventive and curative clinical trials. We first perform a large genetic association study by merging all available case-control datasets and by-proxy study results (discovery n = 409,435 and validation size n = 58,190). Here, we add six variants associated with Alzheimer’s disease risk (near APP, CHRNE, PRKD3/NDUFAF7, PLCG2 and two exonic variants in the SHARPIN gene). Assessment of the polygenic risk score and stratifying by APOE reveal a 4 to 5.5 years difference in median age at onset of Alzheimer’s disease patients in APOE ɛ4 carriers. Because of this study, the underlying mechanisms of APP can be studied to refine the amyloid cascade and the polygenic risk score provides a tool to select individuals at high risk of Alzheimer’s disease.

Introduction: Large variability among Alzheimer's disease (AD) cases might impact genetic discoveries and complicate dissection of underlying biological pathways. Methods: Genome Research at Fundacio ACE (GR@ACE) is a genome-wide study of dementia and its clinical endophenotypes, defined based on AD's clinical certainty and vascular burden. We assessed the impact of known AD loci across endophenotypes to generate loci categories. We incorporated gene coexpression data and conducted pathway analysis per category. Finally, to evaluate the effect of heterogeneity in genetic studies, GR@ACE series were meta-analyzed with additional genome-wide association study data sets. Results: We classified known AD loci into three categories, which might reflect the disease clinical heterogeneity. Vascular processes were only detected as a causal mechanism in probable AD. The meta-analysis strategy revealed the ANKRD31-rs4704171 and NDUFAF6-rs10098778 and confirmed SCIMP-rs7225151 and CD33-rs3865444. Discussion: The regulation of vasculature is a prominent causal component of probable AD. GR@ACE meta-analysis revealed novel AD genetic signals, strongly driven by the presence of clinical heterogeneity in the AD series.

Type 2 diabetes is associated with a high risk of cognitive impairment and dementia. Therefore, strategies are needed to identify patients who are at risk for dementia. Given that the retina is a brain-derived tissue, it may provide a noninvasive way to examine brain pathology. The aims of this study were to evaluate whether retinal sensitivity ) correlates with the specific parameters of brain imaging related to cognitive impairment and) discriminates patients with diabetes with mild cognitive impairment (MCI) from those with normal cognition and those with Alzheimer disease (AD). For this purpose, a prospective, nested case-control study was performed and included 35 patients with type 2 diabetes without cognitive impairment, 35 with MCI, and 35 with AD. Retinal sensitivity was assessed by Macular Integrity Assessment microperimetry, and a neuropsychological evaluation was performed. Brain neurodegeneration was assessed by MRI and fludeoxyglucose-18 positron emission tomography (FDG-PET). A significant correlation was found between retinal sensitivity and the MRI and FDG-PET parameters related to brain neurodegeneration. Retinal sensitivity was related to cognitive status (normocognitive> MCI > AD; < 0.0001). Our results suggest that retinal sensitivity assessed by microperimetry is related to brain neurodegeneration and could be a useful biomarker for identifying patients with type 2 diabetes who are at risk for developing AD.