CSF tau is associated with impaired cortical plasticity, cognitive decline and astrocyte survival only in APOE4-positive Alzheimer's disease

In Alzheimer's disease (AD) patients, apopoliprotein (APOE) polymorphism is the main genetic factor associated with more aggressive clinical course. However, the interaction between cerebrospinal fluid (CSF) tau protein levels and APOE genotype has been scarcely investigated. A possible key mechanism invokes the dysfunction of synaptic plasticity. We investigated how CSF tau interacts with APOE genotype in AD patients. We firstly explored whether CSF tau levels and APOE genotype influence disease progression and long-term potentiation (LTP)-like cortical plasticity as measured by transcranial magnetic stimulation (TMS) in AD patients. Then, we incubated normal human astrocytes (NHAs) with CSF collected from sub-groups of AD patients to determine whether APOE genotype and CSF biomarkers influence astrocytes survival. LTP-like cortical plasticity differed between AD patients with apolipoprotein E4 (APOE4) and apolipoprotein E3 (APOE3) genotype. Higher CSF tau levels were associated with more impaired LTP-like cortical plasticity and faster disease progression in AD patients with APOE4 but not APOE3 genotype. Apoptotic activity was higher when cells were incubated with CSF from AD patients with APOE4 and high tau levels. CSF tau is detrimental on cortical plasticity, disease progression and astrocyte survival only when associated with APOE4 genotype. This is relevant for new therapeutic approaches targeting tau

Polygenic risk modeling for prediction of epithelial ovarian cancer risk

Polygenic risk scores (PRS) for epithelial ovarian cancer (EOC) have the potential to improve risk stratification. Joint estimation of Single Nucleotide Polymorphism (SNP) effects in models could improve predictive performance over standard approaches of PRS construction. Here, we implemented computationally efficient, penalized, logistic regression models (lasso, elastic net, stepwise) to individual level genotype data and a Bayesian framework with continuous shrinkage, "select and shrink for summary statistics" (S4), to summary level data for epithelial non-mucinous ovarian cancer risk prediction. We developed the models in a dataset consisting of 23,564 non-mucinous EOC cases and 40,138 controls participating in the Ovarian Cancer Association Consortium (OCAC) and validated the best models in three populations of different ancestries: prospective data from 198,101 women of European ancestries; 7,669 women of East Asian ancestries; 1,072 women of African ancestries, and in 18,915 BRCA1 and 12,337 BRCA2 pathogenic variant carriers of European ancestries. In the external validation data, the model with the strongest association for non-mucinous EOC risk derived from the OCAC model development data was the S4 model (27,240 SNPs) with odds ratios (OR) of 1.38 (95% CI: 1.28-1.48, AUC: 0.588) per unit standard deviation, in women of European ancestries; 1.14 (95% CI: 1.08-1.19, AUC: 0.538) in women of East Asian ancestries; 1.38 (95% CI: 1.21-1.58, AUC: 0.593) in women of African ancestries; hazard ratios of 1.36 (95% CI: 1.29-1.43, AUC: 0.592) in BRCA1 pathogenic variant carriers and 1.49 (95% CI: 1.35-1.64, AUC: 0.624) in BRCA2 pathogenic variant carriers. Incorporation of the S4 PRS in risk prediction models for ovarian cancer may have clinical utility in ovarian cancer prevention programs

PALB2, CHEK2 and ATM rare variants and cancer risk: data from COGS

Background: The rarity of mutations in PALB2, CHEK2 and ATM make it difficult to estimate precisely associated cancer risks. Population-based family studies have provided evidence that at least some of these mutations are associated with breast cancer risk as high as those associated with rare BRCA2 mutations. We aimed to estimate the relative risks associated with specific rare variants in PALB2, CHEK2 and ATM via a multicentre case-control study.Methods: We genotyped 10 rare mutations using the custom iCOGS array: PALB2 c.1592delT, c.2816T&gt;G and c.3113G&gt;A, CHEK2c.349A&gt;G, c.538C&gt;T, c.715G&gt;A, c.1036C&gt;T, c.1312G&gt;T, and c.1343T&gt;G and ATM c.7271T&gt;G. We assessed associations with breast cancer risk (42 671 cases and 42 164 controls), as well as prostate (22 301 cases and 22 320 controls) and ovarian (14 542 cases and 23 491 controls) cancer risk, for each variant.Results: For European women, strong evidence of association with breast cancer risk was observed for PALB2 c.1592delT OR 3.44 (95% CI 1.39 to 8.52, p=7.1×10−5), PALB2 c.3113G&gt;A OR 4.21 (95% CI 1.84 to 9.60, p=6.9×10−8) and ATM c.7271T&gt;G OR 11.0 (95% CI 1.42 to 85.7, p=0.0012). We also found evidence of association with breast cancer risk for three variants in CHEK2, c.349A&gt;G OR 2.26 (95% CI 1.29 to 3.95), c.1036C&gt;T OR 5.06 (95% CI 1.09 to 23.5) and c.538C&gt;T OR 1.33 (95% CI 1.05 to 1.67) (p≤0.017). Evidence for prostate cancer risk was observed for CHEK2 c.1343T&gt;G OR 3.03 (95% CI 1.53 to 6.03, p=0.0006) for African men and CHEK2 c.1312G&gt;T OR 2.21 (95% CI 1.06 to 4.63, p=0.030) for European men. No evidence of association with ovarian cancer was found for any of these variants.Conclusions: This report adds to accumulating evidence that at least some variants in these genes are associated with an increased risk of breast cancer that is clinically important.</p

Plasma p-tau181 accurately predicts Alzheimer's disease pathology at least 8 years prior to post-mortem and improves the clinical characterisation of cognitive decline

The neuropathological confirmation of amyloid-β (Aβ) plaques and tau neurofibrillary tangles (NFT) remains the gold standard for a definitive diagnosis of Alzheimer's disease (AD). Nowadays, the in vivo diagnosis of AD is greatly aided by both cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers. Although highly accurate, their broad implementation is restricted by high cost, limited accessibility and invasiveness. We recently developed a high-performance, ultrasensitive immunoassay for the quantification of tau phosphorylated at threonine-181 (p-tau181) in plasma, which identifies AD pathophysiology with high accuracy. However, it remains unclear whether plasma p-tau181, measured years before the death, can predict the eventual neuropathological confirmation of AD, and successfully discriminates AD from non-AD dementia pathologies. We studied a unique cohort of 115 individuals with longitudinal blood collections with clinical evaluation at 8, 4 and 2 years prior to neuropathological assessment at death. The results demonstrate that plasma p-tau181 associates better with AD neuropathology and Braak staging than a clinical diagnosis 8 years before post-mortem. Moreover, while all patients had a diagnosis of AD dementia during life, plasma p-tau181 proved to discriminate AD from non-AD pathologies with high accuracy (AUC = 97.4%, 95% CI = 94.1-100%) even 8 years before death. Additionally, the longitudinal trajectory of plasma p-tau181 was assessed in all patients. We found that the main increases in plasma p-tau181 occurred between 8 and 4 years prior to death in patients with AD neuropathology and later plateauing. In contrast, non-AD pathologies and controls exhibited minor, albeit significant, increases in p-tau181 up until death. Overall, our study demonstrates that plasma p-tau181 is highly predictive and specific of AD neuropathology years before post-mortem examination. These data add further support for the use of plasma p-tau181 to aid clinical management in primary care and recruitment for clinical trials.Open access funding provided by University of Gothenburg. This study represents independent research partly funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. Tissue samples were supplied by The London Neurodegenerative Diseases Brain Bank, which receives funding from the UK Medical Research Council and as part of the Brains for Dementia Research programme, jointly funded by Alzheimer’s Research UK and the Alzheimer’s Society. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health. The datasets used and/or analysed during the current study available from the corresponding author on reasonable request. TKK holds a postdoctoral fellowship from the BrightFocus Foundation (#A2020812F), and was further supported by the Swedish Alzheimer Foundation (Alzheimerfonden; #AF-930627), the Swedish Brain Foundation (Hjärnfonden; #FO2020-0240), the Swedish Dementia Foundation (Demensförbundet), the Agneta Prytz-Folkes and Gösta Folkes Foundation, Gamla Tjänarinnor, the Aina (Ann) Wallströms and Mary-Ann Sjöbloms Foundation, the Gun and Bertil Stohnes Foundation, and the Anna Lisa and Brother Björnsson’s Foundation. MSC received funding from the European Union’s Horizon 2020 Research and Innovation Program under the Marie Sklodowska-Curie action grant agreement no. 752310, and currently receives funding from Instituto de Salud Carlos III (PI19/00155) and from the Spanish Ministry of Science, Innovation and Universities (Juan de la Cierva Programme grant IJC2018-037478-I). AH is funded by Research Centre for Mental Health and Biomedical Research Unit for Dementia. KB holds the Torsten Söderberg Professorship in Medicine and is supported by grants from the Swedish Research Council, the Swedish Alzheimer Foundation, and the Swedish Brain Foundation. AH is funded by Research Centre for Mental Health and Biomedical Research Unit for Dementia. KB holds the Torsten Söderberg Professorship in Medicine and is supported by grants from the Swedish Research Council, the Swedish Alzheimer Foundation, and the Swedish Brain Foundation. KB holds the Torsten Söderberg Professorship in Medicine at the Royal Swedish Academy of Sciences, and is supported by the Swedish Research Council (#2017-00915), the Swedish Alzheimer Foundation (#AF-742881), Hjärnfonden, Sweden (#FO2017-0243), and a grant (#ALFGBG-715986) from the Swedish state under the agreement between the Swedish government and the County Councils, the ALF-agreement. NJA is supported by the Wallenberg Centre for Molecular and Translational Medicine, the Swedish Alzheimer Foundation (Alzheimerfonden), the Swedish Dementia Foundation (Demensförbundet), and Hjärnfonden, Sweden