Reduced hippocampal volumes and memory loss in patients with early- and late-onset depression

2005 ◽  
Vol 186 (3) ◽  
pp. 197-202 ◽  
Author(s):  
Ian Hickie ◽  
Sharon Naismith ◽  
Philip B. Ward ◽  
Keelin Turner ◽  
Elizabeth Scott ◽  
...  
Keyword(s):  
Risk Factors ◽  
Older People ◽  
Genetic Risk ◽  
Early Onset ◽  
Visual Memory ◽  
Late Onset ◽  
Memory Loss ◽  
Genetic Risk Factors ◽  
Hippocampal Volume ◽  
Volume Changes

BackgroundHippocampal volume reduction has been reported inconsistently in people with major depression.AimsTo evaluate the interrelationships between hippocampal volumes, memory and key clinical, vascular and genetic risk factors.MethodTotals of 66 people with depression and 20 control participants underwent magnetic resonance imaging and clinical assessment. Measures of depression severity, psychomotor retardation, verbal and visual memory and vascular and specific genetic risk factors were collected.ResultsReduced hippocampal volumes occurred in older people with depression, those with both early-onset and late-onset disorders and those with the melancholic subtype. Reduced hippocampal volumes were associated with deficits in visual and verbal memory performance.ConclusionsAlthough reduced hippocampal volumes are most pronounced in late-onset depression, older people with early-onset disorders also display volume changes and memory loss. No clear vascular or genetic risk factors explain these findings. Hippocampal volume changes may explain how depression emerges as a risk factor to dementia.

P3-006: Late-onset Alzheimer's disease genetic risk factors in two Canadian cohorts: CSHA and ACCORD

2013 ◽  
Vol 9 ◽  
pp. P551-P552
Author(s):  
Ardeshir Omoumi ◽  
Alice Fok ◽  
Talitha Greenwood ◽  
Dessa Sadovnick ◽  
Howard Feldman ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Risk ◽  
Late Onset ◽  
Genetic Risk Factors

Impact of late-onset Alzheimer’s genetic risk factors on beta-amyloid endocytic production

2018 ◽  
Vol 75 (14) ◽  
pp. 2577-2589 ◽  
Author(s):  
Cláudia Guimas Almeida ◽  
Farzaneh Sadat Mirfakhar ◽  
Catarina Perdigão ◽  
Tatiana Burrinha
Keyword(s):  
Risk Factors ◽  
Genetic Risk ◽  
Late Onset ◽  
Beta Amyloid ◽  
Genetic Risk Factors

S2-01-04 Progress toward the identification of novel genetic risk factors for late onset Alzheimer's disease

2004 ◽  
Vol 25 ◽  
pp. S25-S26
Author(s):  
Alison M. Goate ◽  
Petra Nowotny ◽  
Tony Hinrichs ◽  
Scott Smemo ◽  
Keoni Kawe ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Risk ◽  
Late Onset ◽  
Genetic Risk Factors

scholarly journals Metabolomic and lipidomic signatures in autosomal dominant and late-onset Alzheimer disease brains

2021 ◽  
Author(s):  
Brenna C Novotny ◽  
Maria-Victoria Fernandez ◽  
Jorge Bahena ◽  
John P Budde ◽  
Kristy Bergmann ◽  
...  
Keyword(s):  
Risk Factors ◽  
Alzheimer Disease ◽  
Genetic Risk ◽  
Autosomal Dominant ◽  
Late Onset ◽  
Disease Status ◽  
Genetic Risk Factors ◽  
Web Browser ◽  
Pathogenic Variants ◽  
Genetic Groups

The identification of multiple genetic risk factors for Alzheimer Disease (AD) provides evidence to support that many pathways contribute to AD onset and progression. However, the metabolomic and lipidomic profiles in carriers of distinct genetic risk factors are not fully understood. The metabolome can provide a direct image of dysregulated pathways in the brain, including information on treatment targets. In this study, we interrogate the metabolomic and lipidomic signatures in the AD brain, including carriers of pathogenic variants in APP, PSEN1, and PSEN2 (autosomal dominant AD; ADAD), APOE ϵ4 and TREM2 risk variant carriers, and non-carrier sporadic AD (sAD). We generated metabolomic and lipidomic data from parietal cortical tissue from 366 participants with AD pathology and 26 cognitively unimpaired controls using the Metabolon global metabolomics platform. We identified 133 metabolites associated with disease status (FDR q-value<0.05). In sAD brains these include tryptophan betaine (b=-0.57) and N-acetylputrescine (b=-0.14). Metabolites associated with sAD and ADAD include ergothioneine (b=-0.21 and -0.26 respectively) and serotonin (b=-0.34 and -0.58, respectively). TREM2 and ADAD showed association with α-tocopherol (b=-0.12 and -0.12) and CDP-ethanolamine (b=-0.13 and -0.10). β-citrylglutamate levels are associated with sAD, ADAD, and TREM2 compared to controls (b=-0.15; -0.22; and -0.29, respectively). Additionally, we identified a signature of 16 metabolites that is significantly altered between genetic groups (sAD vs. control p = 1.05x10-7, ADAD vs. sAD p = 3.21x10-5) and is associated with Braak tau stage and disease duration. These data are available to the scientific community through a public web browser (http://ngi.pub/Metabolomics). Our findings were replicated in an independent cohort of 327 individuals.

scholarly journals Assessing the Cumulative Contribution of New and Established Common Genetic Risk Factors to Early-Onset Prostate Cancer

2015 ◽  
Vol 25 (5) ◽  
pp. 766-772 ◽  
Author(s):  
Ethan M. Lange ◽  
Jessica V. Ribado ◽  
Kimberly A. Zuhlke ◽  
Anna M. Johnson ◽  
Gregory R. Keele ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Risk Factors ◽  
Genetic Risk ◽  
Early Onset ◽  
Genetic Risk Factors

scholarly journals Targeting lung cancer screening to individuals at greatest risk: the role of genetic factors

2021 ◽  
pp. jmedgenet-2020-107399
Author(s):  
Mikey B Lebrett ◽  
Emma J Crosbie ◽  
Miriam J Smith ◽  
Emma R Woodward ◽  
D Gareth Evans ◽  
...  
Keyword(s):  
Risk Factors ◽  
Lung Cancer ◽  
Cancer Screening ◽  
Genetic Risk ◽  
Prediction Models ◽  
Late Onset ◽  
Lung Cancer Screening ◽  
Genetic Risk Factors ◽  
Smoking History ◽  
Risk Scores

Lung cancer (LC) is the most common global cancer. An individual’s risk of developing LC is mediated by an array of factors, including family history of the disease. Considerable research into genetic risk factors for LC has taken place in recent years, with both low-penetrance and high-penetrance variants implicated in increasing or decreasing a person’s risk of the disease. LC is the leading cause of cancer death worldwide; poor survival is driven by late onset of non-specific symptoms, resulting in late-stage diagnoses. Evidence for the efficacy of screening in detecting cancer earlier, thereby reducing lung-cancer specific mortality, is now well established. To ensure the cost-effectiveness of a screening programme and to limit the potential harms to participants, a risk threshold for screening eligibility is required. Risk prediction models (RPMs), which provide an individual’s personal risk of LC over a particular period based on a large number of risk factors, may improve the selection of high-risk individuals for LC screening when compared with generalised eligibility criteria that only consider smoking history and age. No currently used RPM integrates genetic risk factors into its calculation of risk. This review provides an overview of the evidence for LC screening, screening related harms and the use of RPMs in screening cohort selection. It gives a synopsis of the known genetic risk factors for lung cancer and discusses the evidence for including them in RPMs, focusing in particular on the use of polygenic risk scores to increase the accuracy of targeted lung cancer screening.

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