Objective: In a large general population study we found a close to linear rise with age in the m... more Objective: In a large general population study we found a close to linear rise with age in the mean score and prevalence of self‐reported symptoms of depression. The aim of this study was to examine if this linear relation prevailed when controlled for multiple variables and to examine factors that eventually explained the association.Method: Among individuals aged 20–89 years living in Nord‐Trøndelag County of Norway, 60 869 filled in valid ratings of the Hospital Anxiety and Depression Scale as well as many other variables. Covariates were grouped into a multivariate model with six blocks. Logistic regression was used to model the blocks and variables with caseness of depression as the dependent variable.Results: The model explains a considerable part of the age‐related pattern on depression. The pattern became less distinct in the age groups above 50 years. Variables within the blocks of somatic diagnoses and symptoms, as well as impairment, had most explanatory power.Conclusion: Because of our large sample we were able to control for more relevant variables than earlier studies. In contrast to most other studies, we found that an age‐related increase of the prevalence of depression persisted after control for multiple variables.
Background: Cerebrospinal Fluid (CSF) biomarkers are instrumental for AD risk assessment and prog... more Background: Cerebrospinal Fluid (CSF) biomarkers are instrumental for AD risk assessment and prognosis. Plasma proteins play important roles in numerous biological pathways and modulate the risk for many complex diseases. Analyte levels used as a quantitative trait in Genome-Wide Association studies (GWAS) can provide additional insights and link genetic variation to disease-predisposing factors. Furthermore, these data can be analyzed using Mendelian randomization approaches to reveal the causal relationships between analyte levels and complex traits.Methods: We have conducted a GWAS of protein levels (Amyloid-beta, tau, and additional analytes ascertained in the Rules Based Medicine Human DiscoveryMAP Panel) in CSF and plasma (1-2). Our models correct for age, gender, cohort, and the first two principal components. We have developed a new online catalogue to query the association for any common and low-frequency variants. In addition, we performed Mendelian randomization (MR) to identify analytes associated with disease outcomes available in the NHGRIEBI Catalog of published genome-wide studies and MRBase. Results: We present an online catalogue for the exploration of genome-wide associations in CSF and plasma analytes. Additionally, we integrate phenome-wide association studies to identify the causal roles CSF and plasma analytes play in diverse complex traits. Conclusions: This new resource (http://ngi.wustl.edu/) provides a unique opportunity to leverage GWAS of CSF and plasma analytes to identify causal relationships and help elucidate how genetic variants identified from GWAS contribute to AD and other diseases. 1. Deming Y, Li Z, Kapoor M, Harari O, Del-Aguila JL, Black K, Carrell D, Cai Y, Fernandez MV, Budde J, et al. Genome-wide association study identifies four novel loci associated with Alzheimer’s endophenotypes and disease modifiers. Acta Neuropathol. 2017;133(5):839–56. 2. Kauwe JS, Bailey MH, Ridge PG, et al. Genome-Wide Association Study of CSF Levels of 59 Alzheimer’s Disease Candidate Proteins: significant Associations with Proteins Involved in Amyloid Processing and Inflammation. PLoS Genet. 2014;10(10):e1004758.
Objective: In a large general population study we found a close to linear rise with age in the m... more Objective: In a large general population study we found a close to linear rise with age in the mean score and prevalence of self‐reported symptoms of depression. The aim of this study was to examine if this linear relation prevailed when controlled for multiple variables and to examine factors that eventually explained the association.Method: Among individuals aged 20–89 years living in Nord‐Trøndelag County of Norway, 60 869 filled in valid ratings of the Hospital Anxiety and Depression Scale as well as many other variables. Covariates were grouped into a multivariate model with six blocks. Logistic regression was used to model the blocks and variables with caseness of depression as the dependent variable.Results: The model explains a considerable part of the age‐related pattern on depression. The pattern became less distinct in the age groups above 50 years. Variables within the blocks of somatic diagnoses and symptoms, as well as impairment, had most explanatory power.Conclusion: Because of our large sample we were able to control for more relevant variables than earlier studies. In contrast to most other studies, we found that an age‐related increase of the prevalence of depression persisted after control for multiple variables.
Background: Cerebrospinal Fluid (CSF) biomarkers are instrumental for AD risk assessment and prog... more Background: Cerebrospinal Fluid (CSF) biomarkers are instrumental for AD risk assessment and prognosis. Plasma proteins play important roles in numerous biological pathways and modulate the risk for many complex diseases. Analyte levels used as a quantitative trait in Genome-Wide Association studies (GWAS) can provide additional insights and link genetic variation to disease-predisposing factors. Furthermore, these data can be analyzed using Mendelian randomization approaches to reveal the causal relationships between analyte levels and complex traits.Methods: We have conducted a GWAS of protein levels (Amyloid-beta, tau, and additional analytes ascertained in the Rules Based Medicine Human DiscoveryMAP Panel) in CSF and plasma (1-2). Our models correct for age, gender, cohort, and the first two principal components. We have developed a new online catalogue to query the association for any common and low-frequency variants. In addition, we performed Mendelian randomization (MR) to identify analytes associated with disease outcomes available in the NHGRIEBI Catalog of published genome-wide studies and MRBase. Results: We present an online catalogue for the exploration of genome-wide associations in CSF and plasma analytes. Additionally, we integrate phenome-wide association studies to identify the causal roles CSF and plasma analytes play in diverse complex traits. Conclusions: This new resource (http://ngi.wustl.edu/) provides a unique opportunity to leverage GWAS of CSF and plasma analytes to identify causal relationships and help elucidate how genetic variants identified from GWAS contribute to AD and other diseases. 1. Deming Y, Li Z, Kapoor M, Harari O, Del-Aguila JL, Black K, Carrell D, Cai Y, Fernandez MV, Budde J, et al. Genome-wide association study identifies four novel loci associated with Alzheimer’s endophenotypes and disease modifiers. Acta Neuropathol. 2017;133(5):839–56. 2. Kauwe JS, Bailey MH, Ridge PG, et al. Genome-Wide Association Study of CSF Levels of 59 Alzheimer’s Disease Candidate Proteins: significant Associations with Proteins Involved in Amyloid Processing and Inflammation. PLoS Genet. 2014;10(10):e1004758.
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