scholarly journals Polygenic risk scores for Alzheimer’s disease, and academic achievement, cognitive and behavioural measures in children from the general population

2019 ◽  
Vol 48 (6) ◽  
pp. 1972-1980 ◽  
Author(s):  
Roxanna Korologou-Linden ◽  
Emma L Anderson ◽  
Hannah J Jones ◽  
George Davey Smith ◽  
Laura D Howe ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Academic Achievement ◽  
Educational Attainment ◽  
Biological Effects ◽  
Risk Scores ◽  
P Value ◽  
Childhood And Adolescence ◽  
Nucleotide Polymorphisms ◽  
Polygenic Risk

Abstract Objective Several studies report a polygenic component of risk for Alzheimer’s disease. Understanding whether this polygenic signal is associated with educational, cognitive and behavioural outcomes in children could provide an earlier window for intervention. Methods We examined whether polygenic risk scores (PRS) at varying P-value thresholds in children from the Avon Longitudinal Study of Parents and Children were associated with academic achievement, cognitive and behavioural measures in childhood and adolescence. Results We did not detect any evidence that the genome-wide significant PRS (5x10-8) were associated with these outcomes. PRS at the highest P-value threshold examined (P ≤ 5x10-1) were associated with lower academic achievement in adolescents (Key Stage 3; β: -0.03; 95% confidence interval: -0.05, -0.003) but the effect was attenuated when single nucleotide polymorphisms (SNPs) associated with educational attainment were removed. These PRS were associated with lower IQ (β: -0.04; 95% CI: -0.07, -0.02) at age 8 years with the effect remaining after removing SNPs associated with educational attainment. Conclusions SNPs mediating the biological effects of Alzheimer’s disease are unlikely to operate early in life. The evidence of association between PRS for Alzheimer’s disease at liberal thresholds and cognitive measures suggest shared genetic pathways between Alzheimer’s disease, academic achievement and cognition.

scholarly journals Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores is most accurate when using all genetic information.

2021 ◽  
Author(s):  
Ganna Leonenko ◽  
Emily Baker ◽  
Josua Stevenson-Hoare ◽  
Annerieke Sierksma ◽  
Mark Fiers ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Population Data ◽  
Risk Scores ◽  
P Value ◽  
Older Individuals ◽  
P Values ◽  
Polygenic Risk ◽  
Ε4 Allele ◽  
Polygenic Approach

Abstract There is little agreement regarding the approach and optimal p-value threshold of SNPs to calculate genetic risk scores for Alzheimer’s disease (AD). This reflects a fundamental underlying debate on the polygenic versus oligogenic disease architecture. We re-investigated the assumptions underlying the choice of specific p-value thresholds defining genetic loci used to determine polygenic risk scores (PRS). We find the optimal p-value threshold for SNP selection is 0.1, which supports the polygenic architecture of AD. We found that previous studies supporting an oligogenic model of AD did not take account of the reduction of APOE-ε4 allele frequency in older individuals, which skewed the results towards lower p-value thresholds and eclipsed the contribution of genes associated to AD with higher p-values. The polygenic approach to AD is also effective to identify individuals at high or low AD risk, when only APOE-ε3 homozygous individuals are considered. We also introduce the standardisation of PRS against a population data which ensures comparability of the PRS between studies. In conclusion, our work demonstrates that AD is fundamentally a polygenic disease and that stratifying populations for AD risk best takes the full PRS score into account.

scholarly journals Improving the Utility of Polygenic Risk Scores as a Biomarker for Alzheimer’s Disease

Cells ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 1627
Author(s):  
Dimitrios Vlachakis ◽  
Eleni Papakonstantinou ◽  
Ram Sagar ◽  
Flora Bacopoulou ◽  
Themis Exarchos ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Association Studies ◽  
Complex Diseases ◽  
Risk Scores ◽  
Tissue Cell ◽  
Open Chromatin ◽  
Genome Wide Association Studies ◽  
Nucleotide Polymorphisms ◽  
Polygenic Risk

The treatment of complex and multifactorial diseases constitutes a big challenge in day-to-day clinical practice. As many parameters influence clinical phenotypes, accurate diagnosis and prompt therapeutic management is often difficult. Significant research and investment focuses on state-of-the-art genomic and metagenomic analyses in the burgeoning field of Precision (or Personalized) Medicine with genome-wide-association-studies (GWAS) helping in this direction by linking patient genotypes at specific polymorphic sites (single-nucleotide polymorphisms, SNPs) to the specific phenotype. The generation of polygenic risk scores (PRSs) is a relatively novel statistical method that associates the collective genotypes at many of a person’s SNPs to a trait or disease. As GWAS sample sizes increase, PRSs may become a powerful tool for prevention, early diagnosis and treatment. However, the complexity and multidimensionality of genetic and environmental contributions to phenotypes continue to pose significant challenges for the clinical, broad-scale use of PRSs. To improve the value of PRS measures, we propose a novel pipeline which might better utilize GWAS results and improve the utility of PRS when applied to Alzheimer’s Disease (AD), as a paradigm of multifactorial disease with existing large GWAS datasets that have not yet achieved significant clinical impact. We propose a refined approach for the construction of AD PRS improved by (1), taking into consideration the genetic loci where the SNPs are located, (2) evaluating the post-translational impact of SNPs on coding and non-coding regions by focusing on overlap with open chromatin data and SNPs that are expression quantitative trait loci (QTLs), and (3) scoring and annotating the severity of the associated clinical phenotype into the PRS. Open chromatin and eQTL data need to be carefully selected based on tissue/cell type of origin (e.g., brain, excitatory neurons). Applying such filters to traditional PRS on GWAS studies of complex diseases like AD, can produce a set of SNPs weighted according to our algorithm and a more useful PRS. Our proposed methodology may pave the way for new applications of genomic machine and deep learning pipelines to GWAS datasets in an effort to identify novel clinically useful genetic biomarkers for complex diseases like AD.

[P3-095]: THE USE OF POLYGENIC RISK SCORES (PRS) TO CHARACTERISE THE PRECLINICAL PHASE OF ALZHEIMER's DISEASE

2017 ◽  
Vol 13 (7S_Part_20) ◽  
pp. P970-P971
Author(s):  
Michelle K. Lupton ◽  
Margie Wright ◽  
Nick Martin ◽  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Preclinical Phase

scholarly journals Associations between Alzheimer’s disease polygenic risk scores and hippocampal subfield volumes in 17,161 UK Biobank participants

2021 ◽  
Vol 98 ◽  
pp. 108-115
Author(s):  
Heidi Foo ◽  
Anbupalam Thalamuthu ◽  
Jiyang Jiang ◽  
Forrest Koch ◽  
Karen A. Mather ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Risk Scores ◽  
Uk Biobank ◽  
Polygenic Risk

P3-482: HIGHER ALZHEIMER'S DISEASE POLYGENIC RISK SCORES ARE ASSOCIATED WITH GREATER OBJECTIVELY MEASURED COGNITIVE EFFORT DESPITE NORMAL NEUROPSYCHOLOGICAL FUNCTION

2006 ◽  
Vol 14 (7S_Part_24) ◽  
pp. P1305-P1306
Author(s):  
William S. Kremen ◽  
Matthew S. Panizzon ◽  
Eric L. Granholm ◽  
Jeremy A. Elman ◽  
Daniel E. Gustavson ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Effort ◽  
Risk Scores ◽  
Neuropsychological Function ◽  
Polygenic Risk ◽  
Objectively Measured

scholarly journals Defining Alzheimer’s disease subtypes using polygenic risk scores integrated with genomic and brain transcriptomic profiles

2020 ◽  
Vol 16 (S2) ◽  
Author(s):  
Junming Hu ◽  
Jaeyoon Chung ◽  
Rebecca Panitch ◽  
Congcong Zhu ◽  
Gary W. Beecham ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Disease Subtypes

Identification of Biological Pathways to Alzheimer's Disease Using Polygenic Scores

2017 ◽  
Vol 41 (S1) ◽  
pp. S166-S167
Author(s):  
J. Harrison ◽  
E. Baker ◽  
L. Hubbard ◽  
D. Linden ◽  
J. Williams ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Protein Folding ◽  
Late Onset ◽  
Cell Lineage ◽  
Biological Pathways ◽  
Risk Scores ◽  
Nucleotide Polymorphisms ◽  
Discovery Sample ◽  
Polygenic Scores

IntroductionSingle nucleotide polymorphisms (SNPs) contribute small increases in risk for late-onset Alzheimer's disease (LOAD). LOAD SNPs cluster around genes with similar biological functions (pathways). Polygenic risk scores (PRS) aggregate the effect of SNPs genome-wide. However, this approach has not been widely used for SNPs within specific pathways.ObjectivesWe investigated whether pathway-specific PRS were significant predictors of LOAD case/control status.MethodsWe mapped SNPs to genes within 8 pathways implicated in LOAD. For our polygenic analysis, the discovery sample comprised 13,831 LOAD cases and 29,877 controls. LOAD risk alleles for SNPs in our 8 pathways were identified at a P-value threshold of 0.5. Pathway-specific PRS were calculated in a target sample of 3332 cases and 9832 controls. The genetic data were pruned with R2 > 0.2 while retaining the SNPs most significantly associated with AD. We tested whether pathway-specific PRS were associated with LOAD using logistic regression, adjusting for age, sex, country, and principal components. We report the proportion of variance in liability explained by each pathway.ResultsThe most strongly associated pathways were the immune response (NSNPs = 9304, = 5.63 × 10−19, R2 = 0.04) and hemostasis (NSNPs = 7832, P = 5.47 × 10−7, R2 = 0.015). Regulation of endocytosis, hematopoietic cell lineage, cholesterol transport, clathrin and protein folding were also significantly associated but accounted for less than 1% of the variance. With APOE excluded, all pathways remained significant except proteasome-ubiquitin activity and protein folding.ConclusionsGenetic risk for LOAD can be split into contributions from different biological pathways. These offer a means to explore disease mechanisms and to stratify patients.Disclosure of interestThe authors have not supplied their declaration of competing interest.

scholarly journals Alzheimer’s disease genetic risk and sleep phenotypes: association with more slow-waves and daytime sleepiness

2020 ◽  
Author(s):  
Vincenzo Muto ◽  
Ekaterina Koshmanova ◽  
Pouya Ghaemmaghami ◽  
Mathieu Jaspar ◽  
Christelle Meyer ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Young Adults ◽  
Genetic Variants ◽  
Daytime Sleepiness ◽  
Sleep Disturbances ◽  
Cognitive Disorders ◽  
Risk Scores ◽  
Polygenic Risk ◽  
Genome Wide

AbstractSleep disturbances and genetic variants have been identified as risk factors for Alzheimer’s disease. Whether genome-wide polygenic risk scores (PRS) for AD associate with sleep phenotypes in young adults, decades before typical AD symptom onset, is currently not known. We extensively phenotyped sleep under different sleep conditions and compute whole-genome Polygenic Risk Scores (PRS) for AD in a carefully selected homogenous sample of healthy 363 young men (22.1 y ± 2.7) devoid of sleep and cognitive disorders. AD PRS was associated with more slow wave energy, i.e. the cumulated power in the 0.5-4 Hz EEG band, a marker of sleep need, during habitual sleep and following sleep loss. Furthermore higher AD PRS was correlated with higher habitual daytime sleepiness. These results imply that sleep features may be associated with AD liability in young adults, when current AD biomarkers are typically negative, and reinforce the idea that sleep may be an efficient intervention target for AD.

scholarly journals Pleiotropy of Alzheimer’s Disease and Educational Attainment: Insights from the Summary Statistics

2021 ◽  
Vol 5 (Supplement_1) ◽  
pp. 986-986
Author(s):  
Yury Loika ◽  
Elena Loiko ◽  
Irina Culminskaya ◽  
Alexander Kulminski
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Educational Attainment ◽  
Large Scale ◽  
Association Studies ◽  
Epidemiological Studies ◽  
Genome Wide Association Studies ◽  
Summary Statistics ◽  
Nucleotide Polymorphisms ◽  
Omnibus Test

Abstract Epidemiological studies report beneficial associations of higher educational attainment (EDU) with Alzheimer’s disease (AD). Prior genome-wide association studies (GWAS) also reported variants associated with AD and EDU separately. The analysis of pleiotropic predisposition to these phenotypes may shed light on EDU-related protection against AD. We examined pleiotropic predisposition to AD and EDU using Fisher’s method and omnibus test applied to summary statistics for single nucleotide polymorphisms (SNPs) associated with AD and EDU in large-scale univariate GWAS at suggestive-effect (5×10-8

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