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Objective To determine whether the extent of overlap of the genetic architecture among the sporadic late-onset Alzheimer's Disease (sLOAD), familial late-onset AD (fLOAD), sporadic early-onset AD (sEOAD), and autosomal dominant early-onset AD (eADAD). Methods Polygenic risk scores (PRSs) 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. The highest association of the PRS and risk (odds ratio [OR] = 2.27; P = 1.29 × 10 −7 ) was observed in sEOAD, followed by fLOAD (OR = 1.75; P = 1.12 × 10 −7 ) and sLOAD (OR = 1.40; P = 1.21 × 10 −3 ). The PRS was associated with cerebrospinal fluid ptau 181 -Aβ 42 on eADAD ( P = 4.36 × 10 −2 ). Conclusion Our analysis confirms that the genetic factors identified for LOAD modulate risk in sLOAD and fLOAD and also sEOAD cohorts. Specifically, 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.

More than 20 genetic loci have been associated with risk for Alzheimer’s disease (AD), but reported genome-wide significant loci do not account for all the estimated heritability and provide little information about underlying biological mechanisms. Genetic studies using intermediate quantitative traits such as biomarkers, or endophenotypes, benefit from increased statistical power to identify variants that may not pass the stringent multiple test correction in case–control studies. Endophenotypes also contain additional information helpful for identifying variants and genes associated with other aspects of disease, such as rate of progression or onset, and provide context to interpret the results from genome-wide association studies (GWAS). We conducted GWAS of amyloid beta (Aβ42), tau, and phosphorylated tau (ptau181) levels in cerebrospinal fluid (CSF) from 3146 participants across nine studies to identify novel variants associated with AD. Five genome-wide significant loci (two novel) were associated with ptau181, including loci that have also been associated with AD risk or brain-related phenotypes. Two novel loci associated with Aβ42 near GLIS1 on 1p32.3 (β = −0.059, P = 2.08 × 10−8) and within SERPINB1 on 6p25 (β = −0.025, P = 1.72 × 10−8) were also associated with AD risk (GLIS1: OR = 1.105, P = 3.43 × 10−2), disease progression (GLIS1: β = 0.277, P = 1.92 × 10−2), and age at onset (SERPINB1: β = 0.043, P = 4.62 × 10−3). Bioinformatics indicate that the intronic SERPINB1 variant (rs316341) affects expression of SERPINB1 in various tissues, including the hippocampus, suggesting that SERPINB1 influences AD through an Aβ-associated mechanism. Analyses of known AD risk loci suggest CLU and FERMT2 may influence CSF Aβ42 (P = 0.001 and P = 0.009, respectively) and the INPP5D locus may affect ptau181 levels (P = 0.009); larger studies are necessary to verify these results. Together the findings from this study can be used to inform future AD studies.

Background The genetic architecture of Parkinson’s Disease (PD) is complex and not completely understood. Multiple genetic studies to date have identified multiple causal genes and risk loci. Nevertheless, most of the expected genetic heritability remains unexplained. Polygenic risk scores (PRS) may provide greater statistical power and inform about the genetic architecture of multiple phenotypes. The aim of this study was to test the association between PRS and PD risk, age at onset and cerebrospinal fluid (CSF) biomarkers (α-synuclein, Aβ1–42, t-tau and p-tau). Methods The weighted PRS was created using the genome-wide loci from Nalls et al., 2014 PD GWAs meta-analysis. The PRS was tested for association with PD status, age at onset and CSF biomarker levels in 829 cases and 432 controls of European ancestry. Results The PRS was associated with PD status (p = 5.83×10−08) and age at onset (p = 5.70×10−07). The CSF t-tau levels showed a nominal association with the PRS (p = 0.02). However, CSF α-synuclein, amyloid beta and phosphorylated tau were not found to be associated with the PRS. Conclusion Our study suggests that there is an overlap in the genetic architecture of PD risk and onset, although the different loci present different weights for those phenotypes. In our dataset we found a marginal association of the PRS with CSF t-tau but not with α-synuclein CSF levels, suggesting that the genetic architecture for the CSF biomarker levels is different from that of PD risk. Electronic supplementary material The online version of this article (10.1186/s12883-017-0978-z) contains supplementary material, which is available to authorized users.

Genome-wide association studies of 146 plasma protein levels in 818 individuals revealed 56 genome-wide significant associations (28 novel) with 47 analytes. Loci associated with plasma levels of 39 proteins tested have been previously associated with various complex traits such as heart disease, inflammatory bowel disease, Type 2 diabetes and multiple sclerosis. These data suggest that these plasma protein levels may constitute informative endophenotypes for these complex traits. We found three potential pleiotropic genes: ABO for plasma SELE and ACE levels, FUT2 for CA19-9 and CEA plasma levels and APOE for ApoE and CRP levels. We also found multiple independent signals in loci associated with plasma levels of ApoH, CA19-9, FetuinA, IL6r and LPa. Our study highlights the power of biological traits for genetic studies to identify genetic variants influencing clinically relevant traits, potential pleiotropic effects and complex disease associations in the same locus.

Background Alzheimer’s disease (AD) pathology appears several years before clinical symptoms, so identifying ways to detect individuals in the preclinical stage is imperative. The cerebrospinal fluid (CSF) Tau/Aβ42 ratio is currently the best known predictor of AD status and cognitive decline, and the ratio of CSF levels of chitinase-3-like 1 protein (CHI3L1, YKL-40) and amyloid beta (Aβ42) were reported as predictive, but individual variability and group overlap inhibits their utility for individual diagnosis making it necessary to find ways to improve sensitivity of these biomarkers. Methods We used linear regression to identify genetic loci associated with CSF YKL-40 levels in 379 individuals (80 cognitively impaired and 299 cognitively normal) from the Charles F and Joanne Knight Alzheimer’s Disease Research Center. We tested correlations between YKL-40 and CSF Tau/Aβ42 ratio, Aβ42, tau, and phosphorylated tau (ptau181). We used studentized residuals from a linear regression model of the log-transformed, standardized protein levels and the additive reference allele counts from the most significant locus to adjust YKL-40 values and tested the differences in correlations with CSF Tau/Aβ42 ratio, Aβ42, tau, and ptau181. Results We found that genetic variants on the CH13L1 locus were significantly associated with CSF YKL-40 levels, but not AD risk, age at onset, or disease progression. The most significant variant is a reported expression quantitative trait locus for CHI3L1, the gene which encodes YKL-40, and explained 12.74 % of the variance in CSF YKL-40 in our study. YKL-40 was positively correlated with ptau181 (r = 0.521) and the strength of the correlation significantly increased with the addition of genetic information (r = 0.573, p = 0.006). Conclusions CSF YKL-40 levels are likely a biomarker for AD, but we found no evidence that they are an AD endophenotype. YKL-40 levels are highly regulated by genetic variation, and by including genetic information the strength of the correlation between YKL-40 and ptau181 levels is significantly improved. Our results suggest that studies of potential biomarkers may benefit from including genetic information. Electronic supplementary material The online version of this article (doi:10.1186/s12883-016-0742-9) contains supplementary material, which is available to authorized users.