Quantitative Phenotype Scan Statistic (QPSS) reveals rare variant associations with Alzheimer’s disease endophenotypes

Mapping Intimacies ◽

10.21203/rs.2.20987/v1 ◽

2020 ◽

Author(s):

Yuriko Katsumata ◽

David W. Fardo

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rare Variant ◽

Rare Variants ◽

Region Of Interest ◽

Csf Biomarkers ◽

Sequencing Data ◽

Scan Statistic ◽

Genetic Sequencing ◽

Quantitative Phenotype

Abstract Background: Current sequencing technologies have provided for a more comprehensive genome-wide assessment and have increased genotyping accuracy of rare variants. Scan statistic approaches have previously been adapted to genetic sequencing data. Unlike currently-employed association tests, scan-statistic-based approaches can both localize clusters of disease-related variants and, subsequently, examine the phenotype association within the resulting cluster. In this study, we present a novel Quantitative Phenotype Scan Statistic (QPSS) that extends an approach for dichotomous phenotypes to continuous outcomes in order to identify genomic regions where rare quantitative-phenotype-associated variants cluster. Results: We demonstrate the performance and practicality of QPSS with extensive simulations and an application to a whole-genome sequencing (WGS) study of cerebrospinal fluid (CSF) biomarkers from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Using QPSS, we identify regions of rare variant enrichment associated with levels of AD-related proteins, CSF Aβ 1-42 and p-tau 181P . Conclusions: QPSS is implemented under the assumption that causal variants within a window have the same direction of effect. Typical self-contained tests employ a null hypothesis of no association between the target variant set and the phenotype. Therefore, an advantage of the proposed competitive test is that it is possible to refine a known region of interest to localize disease-associated clusters. The definition of clusters can be easily adapted based on variant function or annotation.

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Quantitative phenotype scan statistic (QPSS) reveals rare variant associations with Alzheimer’s disease endophenotypes

BMC Medical Genetics ◽

10.1186/s12881-020-01046-6 ◽

2020 ◽

Vol 21 (1) ◽

Author(s):

Yuriko Katsumata ◽

David W. Fardo

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rare Variant ◽

Rare Variants ◽

Region Of Interest ◽

Csf Biomarkers ◽

Sequencing Data ◽

Scan Statistic ◽

Genetic Sequencing ◽

Quantitative Phenotype

Abstract Background Current sequencing technologies have provided for a more comprehensive genome-wide assessment and have increased genotyping accuracy of rare variants. Scan statistic approaches have previously been adapted to genetic sequencing data. Unlike currently-employed association tests, scan-statistic-based approaches can both localize clusters of disease-related variants and, subsequently, examine the phenotype association within the resulting cluster. In this study, we present a novel Quantitative Phenotype Scan Statistic (QPSS) that extends an approach for dichotomous phenotypes to continuous outcomes in order to identify genomic regions where rare quantitative-phenotype-associated variants cluster. Results We demonstrate the performance and practicality of QPSS with extensive simulations and an application to a whole-genome sequencing (WGS) study of cerebrospinal fluid (CSF) biomarkers from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Using QPSS, we identify regions of rare variant enrichment associated with levels of AD-related proteins, CSF Aβ1–42 and p-tau181P. Conclusions QPSS is implemented under the assumption that causal variants within a window have the same direction of effect. Typical self-contained tests employ a null hypothesis of no association between the target variant set and the phenotype. Therefore, an advantage of the proposed competitive test is that it is possible to refine a known region of interest to localize disease-associated clusters. The definition of clusters can be easily adapted based on variant function or annotation.

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Quantitative Phenotype Scan Statistic (QPSS) reveals rare variant associations with Alzheimer’s disease endophenotypes

10.21203/rs.2.20987/v2 ◽

2020 ◽

Author(s):

Yuriko Katsumata ◽

David W. Fardo

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Rare Variant ◽

Rare Variants ◽

Region Of Interest ◽

Csf Biomarkers ◽

Sequencing Data ◽

Scan Statistic ◽

Genetic Sequencing ◽

Quantitative Phenotype

Abstract Background: Current sequencing technologies have provided for a more comprehensive genome-wide assessment and have increased genotyping accuracy of rare variants. Scan statistic approaches have previously been adapted to genetic sequencing data. Unlike currently-employed association tests, scan-statistic-based approaches can both localize clusters of disease-related variants and, subsequently, examine the phenotype association within the resulting cluster. In this study, we present a novel Quantitative Phenotype Scan Statistic (QPSS) that extends an approach for dichotomous phenotypes to continuous outcomes in order to identify genomic regions where rare quantitative-phenotype-associated variants cluster. Results: We demonstrate the performance and practicality of QPSS with extensive simulations and an application to a whole-genome sequencing (WGS) study of cerebrospinal fluid (CSF) biomarkers from the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Using QPSS, we identify regions of rare variant enrichment associated with levels of AD-related proteins, CSF Aβ1-42 and p-tau181P.Conclusions: QPSS is implemented under the assumption that causal variants within a window have the same direction of effect. Typical self-contained tests employ a null hypothesis of no association between the target variant set and the phenotype. Therefore, an advantage of the proposed competitive test is that it is possible to refine a known region of interest to localize disease-associated clusters. The definition of clusters can be easily adapted based on variant function or annotation.

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Rare variants in the endocytic pathway are associated with Alzheimer’s disease, its related phenotypes, and functional consequences

PLoS Genetics ◽

10.1371/journal.pgen.1009772 ◽

2021 ◽

Vol 17 (9) ◽

pp. e1009772

Author(s):

Lingyu Zhan ◽

Jiajin Li ◽

Brandon Jew ◽

Jae Hoon Sul

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Clinical Research ◽

Brain Damage ◽

Rare Variant ◽

Rare Variants ◽

Endocytic Pathway ◽

European Ancestry ◽

Careful Examination ◽

Genome Wide Association Studies

Late-onset Alzheimer’s disease (LOAD) is the most common type of dementia causing irreversible brain damage to the elderly and presents a major public health challenge. Clinical research and genome-wide association studies have suggested a potential contribution of the endocytic pathway to AD, with an emphasis on common loci. However, the contribution of rare variants in this pathway to AD has not been thoroughly investigated. In this study, we focused on the effect of rare variants on AD by first applying a rare-variant gene-set burden analysis using genes in the endocytic pathway on over 3,000 individuals with European ancestry from three large whole-genome sequencing (WGS) studies. We identified significant associations of rare-variant burden within the endocytic pathway with AD, which were successfully replicated in independent datasets. We further demonstrated that this endocytic rare-variant enrichment is associated with neurofibrillary tangles (NFTs) and age-related phenotypes, increasing the risk of obtaining severer brain damage, earlier age-at-onset, and earlier age-of-death. Next, by aggregating rare variants within each gene, we sought to identify single endocytic genes associated with AD and NFTs. Careful examination using NFTs revealed one significantly associated gene, ANKRD13D. To identify functional associations, we integrated bulk RNA-Seq data from over 600 brain tissues and found two endocytic expression genes (eGenes), HLA-A and SLC26A7, that displayed significant influences on their gene expressions. Differential expressions between AD patients and controls of these three identified genes were further examined by incorporating scRNA-Seq data from 48 post-mortem brain samples and demonstrated distinct expression patterns across cell types. Taken together, our results demonstrated strong rare-variant effect in the endocytic pathway on AD risk and progression and functional effect of gene expression alteration in both bulk and single-cell resolution, which may bring more insight and serve as valuable resources for future AD genetic studies, clinical research, and therapeutic targeting.

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P3-017: ASSOCIATION ANALYSIS OF RARE VARIANTS NEAR THE APOE REGION WITH CEREBROSPINAL FLUID (CSF) BIOMARKERS OF ALZHEIMER'S DISEASE

Alzheimer s & Dementia ◽

10.1016/j.jalz.2014.05.1104 ◽

2014 ◽

Vol 10 ◽

pp. P632-P633

Author(s):

Kwangsik T. Nho ◽

Sungeun Kim ◽

Shannon Leigh Risacher ◽

Li Shen ◽

Tatiana Foroud ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cerebrospinal Fluid ◽

Association Analysis ◽

Rare Variants ◽

Csf Biomarkers

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Alzheimer's Disease and the Routine Clinical Use of CSF Biomarkers

CNS & Neurological Disorders - Drug Targets ◽

10.2174/1871527316666170124164854 ◽

2017 ◽

Vol 16 (4) ◽

Cited By ~ 1

Author(s):

Alessandro Martorana

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Csf Biomarkers ◽

Clinical Use

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Peripheral Markers of Vascular Endothelial Dysfunction Show Independent but Additive Relationships with Brain-Based Biomarkers in Association with Functional Impairment in Alzheimer’s Disease

Journal of Alzheimer s Disease ◽

10.3233/jad-200759 ◽

2021 ◽

pp. 1-13

Author(s):

Jonathan D. Drake ◽

Alison B. Chambers ◽

Brian R. Ott ◽

Lori A. Daiello ◽

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cell Adhesion ◽

Adhesion Molecule ◽

Functional Impairment ◽

Amyloid Β ◽

Intercellular Adhesion Molecule ◽

Csf Biomarkers ◽

Linear Regression Models ◽

Cognitively Normal

Background: Cerebrovascular dysfunction confers risk for functional decline in Alzheimer’s disease (AD), yet the clinical interplay of these two pathogenic processes is not well understood. Objective: We utilized Alzheimer’s Disease Neuroimaging Initiative (ADNI) data to examine associations between peripherally derived soluble cell adhesion molecules (CAMs) and clinical diagnostic indicators of AD. Methods: Using generalized linear regression models, we examined cross-sectional relationships of soluble plasma vascular cell adhesion molecule-1 (VCAM-1), intercellular adhesion molecule-1 (ICAM-1), and E-Selectin to baseline diagnosis and functional impairment (clinical dementia rating sum-of-boxes, CDR-SB) in the ADNI cohort (n = 112 AD, n = 396 mild cognitive impairment (MCI), n = 58 cognitively normal). We further analyzed associations of these biomarkers with brain-based AD biomarkers in a subset with available cerebrospinal fluid (CSF) data (n = 351). p-values derived from main effects and interaction terms from the linear regressions were used to assess the relationship between independent and dependent variables for significance (significance level was set at 0.05 a priori for all analysis). Results: Higher mean VCAM-1 (p = 0.0026) and ICAM-1 (p = 0.0189) levels were found in AD versus MCI groups; however, not in MCI versus cognitively normal groups. Only VCAM-1 was linked with CDR-SB scores (p = 0.0157), and APOE ɛ4 genotype modified this effect. We observed independent, additive associations when VCAM-1 and CSF amyloid-β (Aβ 42), total tau, phosphorylated tau (P-tau), or P-tau/Aβ 42 (all < p = 0.01) were combined in a CDR-SB model; ICAM-1 showed a similar pattern, but to a lesser extent. Conclusion: Our findings indicate independent associations of plasma-based vascular biomarkers and CSF biomarkers with AD-related clinical impairment.

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Long runs of homozygosity are associated with Alzheimer’s disease

Translational Psychiatry ◽

10.1038/s41398-020-01145-1 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Sonia Moreno-Grau ◽

◽

Maria Victoria Fernández ◽

Itziar de Rojas ◽

Pablo Garcia-González ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

European Ancestry ◽

Runs Of Homozygosity ◽

Sequencing Data ◽

Outbred Population ◽

Whole Exome ◽

Whole Exome Sequencing Data ◽

Outbred Populations ◽

Recessive Effects

AbstractLong runs of homozygosity (ROH) are contiguous stretches of homozygous genotypes, which are a footprint of inbreeding and recessive inheritance. The presence of recessive loci is suggested for Alzheimer’s disease (AD); however, their search has been poorly assessed to date. To investigate homozygosity in AD, here we performed a fine-scale ROH analysis using 10 independent cohorts of European ancestry (11,919 AD cases and 9181 controls.) We detected an increase of homozygosity in AD cases compared to controls [βAVROH (CI 95%) = 0.070 (0.037–0.104); P = 3.91 × 10−5; βFROH (CI95%) = 0.043 (0.009–0.076); P = 0.013]. ROHs increasing the risk of AD (OR > 1) were significantly overrepresented compared to ROHs increasing protection (p < 2.20 × 10−16). A significant ROH association with AD risk was detected upstream the HS3ST1 locus (chr4:11,189,482‒11,305,456), (β (CI 95%) = 1.09 (0.48 ‒ 1.48), p value = 9.03 × 10−4), previously related to AD. Next, to search for recessive candidate variants in ROHs, we constructed a homozygosity map of inbred AD cases extracted from an outbred population and explored ROH regions in whole-exome sequencing data (N = 1449). We detected a candidate marker, rs117458494, mapped in the SPON1 locus, which has been previously associated with amyloid metabolism. Here, we provide a research framework to look for recessive variants in AD using outbred populations. Our results showed that AD cases have enriched homozygosity, suggesting that recessive effects may explain a proportion of AD heritability.

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Longitudinal brain atrophy and CSF biomarkers in early-onset Alzheimer’s disease

NeuroImage Clinical ◽

10.1016/j.nicl.2021.102804 ◽

2021 ◽

pp. 102804

Author(s):

José Contador ◽

Agnès Pérez-Millán ◽

Adrià Tort-Merino ◽

Mircea Balasa ◽

Neus Falgàs ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Brain Atrophy ◽

Early Onset ◽

Csf Biomarkers ◽

Early Onset Alzheimer’S Disease

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Cerebrospinal Fluid Biomarkers of Alzheimer’s Disease: Current Evidence and Future Perspectives

Brain Sciences ◽

10.3390/brainsci11020215 ◽

2021 ◽

Vol 11 (2) ◽

pp. 215

Author(s):

Donovan A. McGrowder ◽

Fabian Miller ◽

Kurt Vaz ◽

Chukwuemeka Nwokocha ◽

Cameil Wilson-Clarke ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cerebrospinal Fluid ◽

Late Onset ◽

Amyloid Β ◽

Current Evidence ◽

Csf Biomarkers ◽

Diagnostic Efficacy ◽

Neurofilament Light ◽

New Biomarkers

Alzheimer’s disease is a progressive, clinically heterogeneous, and particularly complex neurodegenerative disease characterized by a decline in cognition. Over the last two decades, there has been significant growth in the investigation of cerebrospinal fluid (CSF) biomarkers for Alzheimer’s disease. This review presents current evidence from many clinical neurochemical studies, with findings that attest to the efficacy of existing core CSF biomarkers such as total tau, phosphorylated tau, and amyloid-β (Aβ42), which diagnose Alzheimer’s disease in the early and dementia stages of the disorder. The heterogeneity of the pathophysiology of the late-onset disease warrants the growth of the Alzheimer’s disease CSF biomarker toolbox; more biomarkers showing other aspects of the disease mechanism are needed. This review focuses on new biomarkers that track Alzheimer’s disease pathology, such as those that assess neuronal injury (VILIP-1 and neurofilament light), neuroinflammation (sTREM2, YKL-40, osteopontin, GFAP, progranulin, and MCP-1), synaptic dysfunction (SNAP-25 and GAP-43), vascular dysregulation (hFABP), as well as CSF α-synuclein levels and TDP-43 pathology. Some of these biomarkers are promising candidates as they are specific and predict future rates of cognitive decline. Findings from the combinations of subclasses of new Alzheimer’s disease biomarkers that improve their diagnostic efficacy in detecting associated pathological changes are also presented.

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