scholarly journals ANU-ADRI and not Genetic Risk score predicts MCI in a cohort of older adults followed for 12 years

2016 ◽  
Author(s):  
Shea J. Andrews ◽  
Ranmalee Eramudugolla ◽  
Jorge I. Velez ◽  
Nicolas Cherbuin ◽  
Simon Easteal ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Demographic Factors ◽  
Population Level ◽  
Risk Scores ◽  
Cognitive States ◽  
State Models

AbstractINTRODUCTIONWe evaluated a risk score comprising lifestyle, medical and demographic factors (ANU-ADRI), and a genetic risk score (GRS) as predictors of Mild Cognitive Impairment (MCI).METHODSANU-ADRI risk scores were computed for the baseline assessment of 2,078 participants from the PATH project. Participants were assessed for clinically diagnosed MCI/Dementia and psychometric test-based MCI (MCI-TB) at 12 years of follow-up. Multi-state models estimated the odds of transitioning from cognitively normal (CN) to MCI/Dementia and MCI-TB over 12 years according to baseline ANU-ADRI and GRS.RESULTSHigher ANU-ADRI score predicted transitioning from CN to either MCI/Dementia and MCI-TB (Hazard ratio [HR] = 1.06, 95% CI:1.04-1.09; HR = 1.06, 95% CI: 1.03-1.09), and a reduced likelihood of cognitive recovery from MCITB to CN (HR = 0.69, 95% CI: 0.49-0.98). GRS was not associated with transition to MCI/Dementia, or MCI-TB.DISCUSSIONThe ANU-ADRI may be used for population-level risk assessment and screening.Research in ContextSystematic ReviewThe authors reviewed the literature using online databases e.g. (PubMed). We consulted mild cognitive impairment (MCI) and Alzheimer’s disease (AD) research detailing the use of risk factors for predicting progression from MCI and AD; and the appropriate statistical models for modelling transitions between cognitive states. These publications are appropriately cited.InterpretationIn the general population, the ANU-ADRI comprising lifestyle, medical and demographic factors is predictive of progression from normal cognition to MCI/Dementia whereas a Genetic Risk Score comprising the main Alzheimer’s risk genes is not predictive.Future DirectionsFurther evaluation of the ANU-ADRI as a predictor of specific MCI and dementia subtypes is required. The ANU-ADRI may be used to identify individuals indicated for risk reduction intervention and to assist clinical management and cognitive health promotion. Genetic risk scores contribute to understanding dementia etiology but apart from APOE are unlikely to be useful in screening or prevention trials.

scholarly journals P300 Amplitude in Relation to Age, Neuropsychological Performance, and Genetic Risk for Alzheimer’s Disease

2020 ◽  
Vol 4 (Supplement_1) ◽  
pp. 490-490
Author(s):  
Julia Sheffler ◽  
Greg Hajcak ◽  
Cynthia Vied ◽  
Melissa Meynadasy ◽  
Russell Mach
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Executive Functioning ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Event Related Potential ◽  
P300 Amplitude ◽  
Visual Tasks ◽  
Neuropsychological Outcomes

Abstract The P300 event-related potential (ERP) is associated with aging and risk for Alzhiemer’s disease (AD) and mild cognitive impairment (MCI). Our study sought to replicate previous findings regarding P300 amplitude, age, and neuropsychological outcomes. We also sought to fill gaps in the literature by assessing associations in a primarily healthy sample of older adults (aged 60-75) and through use of comprehensive assessment procedures for ERPs, neuropsychological outcomes, and a genetic risk score (i.e., BDNF, APOE, and PSEN1 mutations). Approximately 25% of our total sample (N=72) met criteria for possible or probable mild cognitive impairment. We assessed whether the P300 elicited by auditory (oddball) and visual (go/nogo) paradigms were associated with performance across neuropsychological tests commonly used in clinical settings, which include cognitive domains of semantic, episodic, and visual memory, executive functioning, language (confrontation naming), abstract reasoning (visual and verbal), and attention. Further, we examined associations between P300 and multiple genetic risks for AD. Our findings demonstrated differences in outcomes between audio and visual tasks of P300, with visual tasks tending to show stronger relationships with neuropsychological and genetic factors. Neuropsychological measures of memory and executive functioning were most closely related to visual P300 amplitude. P300 amplitude was also significantly associated with a genetic risk score for AD, despite the sample generally performing in the normal range on most neuropsychological tasks. Overall, our study has implications for use of the P300 for early detection of risk for AD and for improving our understanding of the P300 as a cognitive biomarker.

scholarly journals Genetic risk score predicting accelerated progression from mild cognitive impairment to Alzheimer’s disease

2012 ◽  
Vol 120 (5) ◽  
pp. 807-812 ◽  
Author(s):  
E. Rodríguez-Rodríguez ◽  
P. Sánchez-Juan ◽  
J. L. Vázquez-Higuera ◽  
I. Mateo ◽  
A. Pozueta ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score

scholarly journals Identifying individuals with high risk of Alzheimer’s disease using polygenic risk scores

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Ganna Leonenko ◽  
Emily Baker ◽  
Joshua Stevenson-Hoare ◽  
Annerieke Sierksma ◽  
Mark Fiers ◽  
...  
Keyword(s):  
High Risk ◽  
Risk Score ◽  
Genetic Risk ◽  
Prediction Accuracy ◽  
Genetic Risk Score ◽  
Low Risk ◽  
Risk Scores ◽  
Sample Mean ◽  
Polygenic Risk ◽  
Reliable Identification

AbstractPolygenic Risk Scores (PRS) for AD offer unique possibilities for reliable identification of individuals at high and low risk of AD. However, there is little agreement in the field as to what approach should be used for genetic risk score calculations, how to model the effect of APOE, what the optimal p-value threshold (pT) for SNP selection is and how to compare scores between studies and methods. We show that the best prediction accuracy is achieved with a model with two predictors (APOE and PRS excluding APOE region) with pT<0.1 for SNP selection. Prediction accuracy in a sample across different PRS approaches is similar, but individuals’ scores and their associated ranking differ. We show that standardising PRS against the population mean, as opposed to the sample mean, makes the individuals’ scores comparable between studies. Our work highlights the best strategies for polygenic profiling when assessing individuals for AD risk.

scholarly journals Progression from islet autoimmunity to clinical type 1 diabetes is influenced by genetic factors: results from the prospective TEDDY study

2018 ◽  
Vol 56 (9) ◽  
pp. 602-605 ◽  
Author(s):  
Andreas Beyerlein ◽  
Ezio Bonifacio ◽  
Kendra Vehik ◽  
Markus Hippich ◽  
Christiane Winkler ◽  
...  
Keyword(s):  
Type 1 Diabetes ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Factors ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Islet Autoimmunity ◽  
Islet Autoantibody ◽  
Clinical Type

BackgroundProgression time from islet autoimmunity to clinical type 1 diabetes is highly variable and the extent that genetic factors contribute is unknown.MethodsIn 341 islet autoantibody-positive children with the human leucocyte antigen (HLA) DR3/DR4-DQ8 or the HLA DR4-DQ8/DR4-DQ8 genotype from the prospective TEDDY (The Environmental Determinants of Diabetes in the Young) study, we investigated whether a genetic risk score that had previously been shown to predict islet autoimmunity is also associated with disease progression.ResultsIslet autoantibody-positive children with a genetic risk score in the lowest quartile had a slower progression from single to multiple autoantibodies (p=0.018), from single autoantibodies to diabetes (p=0.004), and by trend from multiple islet autoantibodies to diabetes (p=0.06). In a Cox proportional hazards analysis, faster progression was associated with an increased genetic risk score independently of HLA genotype (HR for progression from multiple autoantibodies to type 1 diabetes, 1.27, 95% CI 1.02 to 1.58 per unit increase), an earlier age of islet autoantibody development (HR, 0.68, 95% CI 0.58 to 0.81 per year increase in age) and female sex (HR, 1.94, 95% CI 1.28 to 2.93).ConclusionsGenetic risk scores may be used to identify islet autoantibody-positive children with high-risk HLA genotypes who have a slow rate of progression to subsequent stages of autoimmunity and type 1 diabetes.

scholarly journals Alzheimer’s Genetic Risk Score linked to Incident Mild Behavioral Impairment

2017 ◽  
Author(s):  
Shea J. Andrews ◽  
Zahinoor Ismail ◽  
Kaarin J. Anstey ◽  
Moyra Mortby
Keyword(s):  
Cognitive Impairment ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Neuropsychiatric Symptoms ◽  
Later Life ◽  
Behavioral Impairment ◽  
Affective Dysregulation ◽  
Weighted Genetic Risk Score ◽  
Shared Risk

AbstractMild Behavioral Impairment (MBI) describes the emergence of later-life Neuropsychiatric Symptoms (NPS) as an at-risk state for cognitive decline and dementia and as a potential manifestation of prodromal dementia. How NPS mechanistically link to the development of Mild Cognitive Impairment (MCI) and Alzheimer’s disease (AD) is not fully understood. Potential mechanisms include either shared risk factors that are related to both NPS and cognitive impairment, or AD pathology promoting NPS. This is the first study to examine whether AD genetic loci, individually and as a genetic risk score, are a shared risk factor with MBI. 1377 older adults (aged 72-79; 738 males; 763 normal cognition) from the PATH Through Life project. MBI was assessed in accordance with Criterion 1 of the ISTAART-AA diagnostic criteria using the Neuropsychiatric Inventory. 25 LOAD risk loci were genotyped and a weighted genetic risk score (GRS) was constructed. Binomial logistic regression adjusting for age, gender, and education examined the association between LOAD GRS and MBI domains. An increase in the LOAD GRS and APOE*ε4 were associated with higher likelihood of Affective Dysregulation;MS4A4A-rs4938933*C andMS4A6A-rs610932*G were associated with a reduced likelihood of Affective Dysregulation;ZCWPW1-rs1476679*C was associated with a reduced likelihood of Social Inappropriateness and Abnormal Perception;BIN1-rs744373*G andEPHA1-rs11767557*C were associated with higher likelihood of Abnormal Perception;NME8-rs2718058*G was associated with a reduced likelihood Decreased Motivation. These findings suggest a common genetic etiology between MBI and traditionally recognized memory problems observed in AD and improve our understanding of the pathophysiological features underlying MBI.

scholarly journals Sexual Differences in Genetic Predisposition of Coronary Artery Disease

2020 ◽  
Author(s):  
Yunfeng Huang ◽  
Qin Hui ◽  
Marta Gwinn ◽  
Yi-Juan Hu ◽  
Arshed A. Quyyumi ◽  
...  
Keyword(s):  
Coronary Artery Disease ◽  
Coronary Artery ◽  
Risk Score ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Men And Women ◽  
High Genetic Risk ◽  
Genome Wide ◽  
Artery Disease

Background - The genomic structure that contributes to the risk of coronary artery disease (CAD) can be evaluated as a risk score of multiple variants. However, sex differences have not been fully examined in applications of genetic risk score of CAD. Methods - Using data from the UK Biobank, we constructed a CAD genetic risk score based on all known loci, three mediating trait-based (blood pressure, lipids, body mass index) sub-scores, and a genome-wide polygenic risk score based on 1.1 million variants. The differences in genetic associations with prevalent and incident CAD between men and women were investigated among 317,509 unrelated individuals of European ancestry. We also assessed interactions with sex for 161 individual loci included in the comprehensive genetic risk score. Results - For both prevalent and incident CAD, the associations of comprehensive and genome-wide genetic risk scores were stronger among men than women. Using a score of 161 loci, we observed a 2.4 times higher risk for incident CAD comparing men with high genetic risk to men with low genetic risk, but an 80 percent greater risk comparing women with high genetic risk to women with low genetic risk. (interaction p=0.002). Of the three sub-scores, the blood pressure-associated sub-score exhibited sex differences (interaction p=0.0004 per SD increase in sub-score). Analysis of individual variants identified a novel gene-sex interaction at locus 21q22.11 . Conclusions - Sexual differences in genetic predisposition should be considered in future studies of coronary artery disease, and genetic risk scores should not be assumed to perform equally well in men and women.

scholarly journals Individual and joint performance of DNA methylation profiles, genetic risk score and environmental risk scores for predicting breast cancer risk

2019 ◽  
Vol 14 (1) ◽  
pp. 42-53
Author(s):  
Zhong Guan ◽  
Janhavi R. Raut ◽  
Korbinian Weigl ◽  
Ben Schöttker ◽  
Bernd Holleczek ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Dna Methylation ◽  
Breast Cancer Risk ◽  
Cancer Risk ◽  
Risk Score ◽  
Environmental Risk ◽  
Genetic Risk ◽  
Genetic Risk Score ◽  
Risk Scores ◽  
Joint Performance

scholarly journals Pharmacogenomics Factors Influencing the Effect of Risperidone on Prolactin Levels in Thai Pediatric Patients With Autism Spectrum Disorder

2021 ◽  
Vol 12 ◽  
Author(s):  
Yaowaluck Hongkaew ◽  
Andrea Gaedigk ◽  
Bob Wilffert ◽  
Roger Gaedigk ◽  
Wiranpat Kittitharaphan ◽  
...  
Keyword(s):  
Autism Spectrum Disorder ◽  
Risk Score ◽  
Genetic Risk ◽  
Dopamine D2 Receptor ◽  
Genetic Risk Score ◽  
D2 Receptor ◽  
Kinase Domain ◽  
Autism Spectrum ◽  
Spectrum Disorder ◽  
Risk Scores

We investigated the association between genetic variations in pharmacodynamic genes and risperidone-induced increased prolactin levels in children and adolescents with autism spectrum disorder (ASD). In a retrospective study, variants of pharmacodynamic genes were analyzed in 124 ASD patients treated with a risperidone regimen for at least 3 months. To simplify genotype interpretation, we created an algorithm to calculate the dopamine D2 receptor (DRD2) gene genetic risk score. There was no relationship between prolactin levels and single SNPs. However, the H1/H3 diplotype (A2/A2-Cin/Cin-A/G) of DRD2/ankyrin repeat and kinase domain containing 1 (ANKK1) Taq1A, DRD2 -141C indel, and DRD2 -141A&gt;G, which had a genetic risk score of 5.5, was associated with the highest median prolactin levels (23 ng/ml). As the dose-corrected plasma levels of risperidone, 9-OH-risperidone, and the active moiety increased, prolactin levels in patients carrying the H1/H3 diplotype were significantly higher than those of the other diplotypes. DRD2 diplotypes showed significantly high prolactin levels as plasma risperidone levels increased. Lower levels of prolactin were detected in patients who responded to risperidone. This is the first system for describing DRD2 haplotypes using genetic risk scores based on their protein expression. Clinicians should consider using pharmacogenetic-based decision-making in clinical practice to prevent prolactin increase.

scholarly journals Integrating expert knowledge for dementia risk prediction in individuals with mild cognitive impairment (MCI): a study protocol

BMJ Open ◽  
2021 ◽  
Vol 11 (11) ◽  
pp. e051185
Author(s):  
Meng Wang ◽  
Eric E Smith ◽  
Nils Daniel Forkert ◽  
Thierry Chekouo ◽  
Zahinoor Ismail ◽  
...  
Keyword(s):  
Cognitive Impairment ◽  
Mild Cognitive Impairment ◽  
Risk Stratification ◽  
Risk Score ◽  
Expert Knowledge ◽  
Patient Data ◽  
Expert Elicitation ◽  
Risk Scores ◽  
Data Set ◽  
Dementia Risk

IntroductionTo date, there is no broadly accepted dementia risk score for use in individuals with mild cognitive impairment (MCI), partly because there are few large datasets available for model development. When evidence is limited, the knowledge and experience of experts becomes more crucial for risk stratification and providing MCI patients with prognosis. Structured expert elicitation (SEE) includes formal methods to quantify experts’ beliefs and help experts to express their beliefs in a quantitative form, reducing biases in the process. This study proposes to (1) assess experts’ beliefs about important predictors for 3-year dementia risk in persons with MCI through SEE methodology and (2) to integrate expert knowledge and patient data to derive dementia risk scores in persons with MCI using a Bayesian approach.Methods and analysisThis study will use a combination of SEE methodology, prospectively collected clinical data, and statistical modelling to derive a dementia risk score in persons with MCI . Clinical expert knowledge will be quantified using SEE methodology that involves the selection and training of the experts, administration of questionnaire for eliciting expert knowledge, discussion meetings and results aggregation. Patient data from the Prospective Registry for Persons with Memory Symptoms of the Cognitive Neurosciences Clinic at the University of Calgary; the Alzheimer’s Disease Neuroimaging Initiative; and the National Alzheimer’s Coordinating Center’s Uniform Data Set will be used for model training and validation. Bayesian Cox models will be used to incorporate patient data and elicited data to predict 3-year dementia risk.DiscussionThis study will develop a robust dementia risk score that incorporates clinician expert knowledge with patient data for accurate risk stratification, prognosis and management of dementia.

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