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Sökning: WFRF:(Lovestone Simon)

  • Resultat 11-20 av 38
  • Föregående 1[2]34Nästa
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11.
  • Kaufmann, Tobias, et al. (författare)
  • Common brain disorders are associated with heritable patterns of apparent aging of the brain
  • 2019
  • Ingår i: Nature Neuroscience. - Nature Publishing Group. - 1097-6256 .- 1546-1726. ; 22:10, s. 1617-
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Common risk factors for psychiatric and other brain disorders are likely to converge on biological pathways influencing the development and maintenance of brain structure and function across life. Using structural MRI data from 45,615 individuals aged 3-96 years, we demonstrate distinct patterns of apparent brain aging in several brain disorders and reveal genetic pleiotropy between apparent brain aging in healthy individuals and common brain disorders.</p>
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12.
  • Kim, Min, et al. (författare)
  • Primary fatty amides in plasma associated with brain amyloid burden, hippocampal volume, and memory in the European Medical Information Framework for Alzheimer's Disease biomarker discovery cohort.
  • 2019
  • Ingår i: Alzheimer's & dementia : the journal of the Alzheimer's Association. - 1552-5279. ; 15:6, s. 817-827
  • Tidskriftsartikel (refereegranskat)abstract
    • Introduction: A critical and as-yet unmet need in Alzheimer's disease (AD) is the discovery of peripheral small molecule biomarkers. Given that brain pathology precedes clinical symptom onset, we set out to test whether metabolites in blood associated with pathology as indexed by cerebrospinal fluid (CSF) AD biomarkers. Methods: This study analyzed 593 plasma samples selected from the European Medical Information Framework for Alzheimer's Disease Multimodal Biomarker Discovery study, of individuals who were cognitively healthy (n = 242), had mild cognitive impairment (n = 236), or had AD-type dementia (n = 115). Logistic regressions were carried out between plasma metabolites (n = 883) and CSF markers, magnetic resonance imaging, cognition, and clinical diagnosis. Results: Eight metabolites were associated with amyloid β and one with t-tau in CSF, these were primary fatty acid amides (PFAMs), lipokines, and amino acids. From these, PFAMs, glutamate, and aspartate also associated with hippocampal volume and memory. Discussion: PFAMs have been found increased and associated with amyloid β burden in CSF and clinical measures. © 2019
13.
  • Lambert, Jean-Charles, et al. (författare)
  • Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease
  • 2013
  • Ingår i: Nature Genetics. - 1061-4036 .- 1546-1718. ; 45:12, s. 1452-U206
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Eleven susceptibility loci for late-onset Alzheimer's disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer's disease cases and 37,154 controls. In stage 2, 11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer's disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P &lt; 5 x 10(-8)) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer's disease.</p>
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14.
  • Lambert, Jean-Charles, et al. (författare)
  • Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease
  • 2013
  • Ingår i: Nature Genetics. - Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 45:12, s. 1452-U206
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>Eleven susceptibility loci for late-onset Alzheimer's disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer's disease cases and 37,154 controls. In stage 2, 11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer's disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P &lt; 5 x 10(-8)) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer's disease.</p>
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15.
  • Morgan, Angharad R, et al. (författare)
  • Inflammatory biomarkers in Alzheimer's disease plasma
  • 2019
  • Ingår i: Alzheimer's & dementia : the journal of the Alzheimer's Association. - 1552-5279. ; 15:6, s. 776-787
  • Tidskriftsartikel (refereegranskat)abstract
    • Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a "Holy Grail" of AD research and intensively sought; however, there are no well-established plasma markers.A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed.Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71).Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation.
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16.
  • Shi, Liu, et al. (författare)
  • Discovery and validation of plasma proteomic biomarkers relating to brain amyloid burden by SOMAscan assay.
  • 2019
  • Ingår i: Alzheimer's & dementia : the journal of the Alzheimer's Association. - 1552-5279. ; 15:11, s. 1478-1488
  • Tidskriftsartikel (refereegranskat)abstract
    • Plasma proteins have been widely studied as candidate biomarkers to predict brain amyloid deposition to increase recruitment efficiency in secondary prevention clinical trials for Alzheimer's disease. Most such biomarker studies are targeted to specific proteins or are biased toward high abundant proteins.4001 plasma proteins were measured in two groups of participants (discovery group = 516, replication group = 365) selected from the European Medical Information Framework for Alzheimer's disease Multimodal Biomarker Discovery study, all of whom had measures of amyloid.A panel of proteins (n = 44), along with age and apolipoprotein E (APOE) ε4, predicted brain amyloid deposition with good performance in both the discovery group (area under the curve = 0.78) and the replication group (area under the curve = 0.68). Furthermore, a causal relationship between amyloid and tau was confirmed by Mendelian randomization.The results suggest that high-dimensional plasma protein testing could be a useful and reproducible approach for measuring brain amyloid deposition.
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17.
  • Smith, Bradley N., et al. (författare)
  • The C9ORF72 expansion mutation is a common cause of ALS+/-FTD in Europe and has a single founder
  • 2013
  • Ingår i: European Journal of Human Genetics. - London : Nature Publishing Group. - 1018-4813 .- 1476-5438. ; 21:1, s. 102-108
  • Tidskriftsartikel (refereegranskat)abstract
    • <p>A massive hexanucleotide repeat expansion mutation (HREM) in C9ORF72 has recently been linked to amyotrophic lateral sclerosis (ALS) and frontotemporal dementia (FTD). Here we describe the frequency, origin and stability of this mutation in ALS+/-FTD from five European cohorts (total n = 1347). Single-nucleotide polymorphisms defining the risk haplotype in linked kindreds were genotyped in cases (n = 434) and controls (n = 856). Haplotypes were analysed using PLINK and aged using DMLE+. In a London clinic cohort, the HREM was the most common mutation in familial ALS+/-FTD: C9ORF72 29/112 (26%), SOD1 27/112 (24%), TARDBP 1/112 (1%) and FUS 4/112 (4%) and detected in 13/216 (6%) of unselected sporadic ALS cases but was rare in controls (3/856, 0.3%). HREM prevalence was high for familial ALS+/-FTD throughout Europe: Belgium 19/22 (86%), Sweden 30/41 (73%), the Netherlands 10/27 (37%) and Italy 4/20 (20%). The HREM did not affect the age at onset or survival of ALS patients. Haplotype analysis identified a common founder in all 137 HREM carriers that arose around 6300 years ago. The haplotype from which the HREM arose is intrinsically unstable with an increased number of repeats (average 8, compared with 2 for controls, P&lt;10(-8)). We conclude that the HREM has a single founder and is the most common mutation in familial and sporadic ALS in Europe.</p>
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18.
  • Stamate, Daniel, et al. (författare)
  • A metabolite-based machine learning approach to diagnose Alzheimer-type dementia in blood: Results from the European Medical Information Framework for Alzheimer disease biomarker discovery cohort.
  • 2019
  • Ingår i: Alzheimer's & dementia (New York, N. Y.). - 2352-8737. ; 5:1, s. 933-938
  • Tidskriftsartikel (refereegranskat)abstract
    • Machine learning (ML) may harbor the potential to capture the metabolic complexity in Alzheimer Disease (AD). Here we set out to test the performance of metabolites in blood to categorize AD when compared to CSF biomarkers.This study analyzed samples from 242 cognitively normal (CN) people and 115 with AD-type dementia utilizing plasma metabolites (n = 883). Deep Learning (DL), Extreme Gradient Boosting (XGBoost) and Random Forest (RF) were used to differentiate AD from CN. These models were internally validated using Nested Cross Validation (NCV).On the test data, DL produced the AUC of 0.85 (0.80-0.89), XGBoost produced 0.88 (0.86-0.89) and RF produced 0.85 (0.83-0.87). By comparison, CSF measures of amyloid, p-tau and t-tau (together with age and gender) produced with XGBoost the AUC values of 0.78, 0.83 and 0.87, respectively.This study showed that plasma metabolites have the potential to match the AUC of well-established AD CSF biomarkers in a relatively small cohort. Further studies in independent cohorts are needed to validate whether this specific panel of blood metabolites can separate AD from controls, and how specific it is for AD as compared with other neurodegenerative disorders.
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19.
  • van Maurik, Ingrid S., et al. (författare)
  • Biomarker-based prognosis for people with mild cognitive impairment (ABIDE) : a modelling study
  • 2019
  • Ingår i: The Lancet Neurology. - Lancet Ltd. - 1474-4422. ; 18:11, s. 1034-1044
  • Tidskriftsartikel (refereegranskat)abstract
    • Background: Biomarker-based risk predictions of dementia in people with mild cognitive impairment are highly relevant for care planning and to select patients for treatment when disease-modifying drugs become available. We aimed to establish robust prediction models of disease progression in people at risk of dementia. Methods: In this modelling study, we included people with mild cognitive impairment (MCI) from single-centre and multicentre cohorts in Europe and North America: the European Medical Information Framework for Alzheimer's Disease (EMIF-AD; n=883), Alzheimer's Disease Neuroimaging Initiative (ADNI; n=829), Amsterdam Dementia Cohort (ADC; n=666), and the Swedish BioFINDER study (n=233). Inclusion criteria were a baseline diagnosis of MCI, at least 6 months of follow-up, and availability of a baseline Mini-Mental State Examination (MMSE) and MRI or CSF biomarker assessment. The primary endpoint was clinical progression to any type of dementia. We evaluated performance of previously developed risk prediction models—a demographics model, a hippocampal volume model, and a CSF biomarkers model—by evaluating them across cohorts, incorporating different biomarker measurement methods, and determining prognostic performance with Harrell's C statistic. We then updated the models by re-estimating parameters with and without centre-specific effects and evaluated model calibration by comparing observed and expected survival. Finally, we constructed a model combining markers for amyloid deposition, tauopathy, and neurodegeneration (ATN), in accordance with the National Institute on Aging and Alzheimer's Association research framework. Findings: We included all 2611 individuals with MCI in the four cohorts, 1007 (39%) of whom progressed to dementia. The validated demographics model (Harrell's C 0·62, 95% CI 0·59–0·65), validated hippocampal volume model (0·67, 0·62–0·72), and updated CSF biomarkers model (0·72, 0·68–0·74) had adequate prognostic performance across cohorts and were well calibrated. The newly constructed ATN model had the highest performance (0·74, 0·71–0·76). Interpretation: We generated risk models that are robust across cohorts, which adds to their potential clinical applicability. The models could aid clinicians in the interpretation of CSF biomarker and hippocampal volume results in individuals with MCI, and help research and clinical settings to prepare for a future of precision medicine in Alzheimer's disease. Future research should focus on the clinical utility of the models, particularly if their use affects participants' understanding, emotional wellbeing, and behaviour. Funding: ZonMW-Memorabel.
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20.
  • Vos, Stephanie J B, et al. (författare)
  • Prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage.
  • 2015
  • Ingår i: Brain. - Oxford University Press. - 1460-2156. ; 138:Feb 17, s. 1327-1338
  • Tidskriftsartikel (refereegranskat)abstract
    • Three sets of research criteria are available for diagnosis of Alzheimer's disease in subjects with mild cognitive impairment: the International Working Group-1, International Working Group-2, and National Institute of Aging-Alzheimer Association criteria. We compared the prevalence and prognosis of Alzheimer's disease at the mild cognitive impairment stage according to these criteria. Subjects with mild cognitive impairment (n = 1607), 766 of whom had both amyloid and neuronal injury markers, were recruited from 13 cohorts. We used cognitive test performance and available biomarkers to classify subjects as prodromal Alzheimer's disease according to International Working Group-1 and International Working Group-2 criteria and in the high Alzheimer's disease likelihood group, conflicting biomarker groups (isolated amyloid pathology or suspected non-Alzheimer pathophysiology), and low Alzheimer's disease likelihood group according to the National Institute of Ageing-Alzheimer Association criteria. Outcome measures were the proportion of subjects with Alzheimer's disease at the mild cognitive impairment stage and progression to Alzheimer's disease-type dementia. We performed survival analyses using Cox proportional hazards models. According to the International Working Group-1 criteria, 850 (53%) subjects had prodromal Alzheimer's disease. Their 3-year progression rate to Alzheimer's disease-type dementia was 50% compared to 21% for subjects without prodromal Alzheimer's disease. According to the International Working Group-2 criteria, 308 (40%) subjects had prodromal Alzheimer's disease. Their 3-year progression rate to Alzheimer's disease-type dementia was 61% compared to 22% for subjects without prodromal Alzheimer's disease. According to the National Institute of Ageing-Alzheimer Association criteria, 353 (46%) subjects were in the high Alzheimer's disease likelihood group, 49 (6%) in the isolated amyloid pathology group, 220 (29%) in the suspected non-Alzheimer pathophysiology group, and 144 (19%) in the low Alzheimer's disease likelihood group. The 3-year progression rate to Alzheimer's disease-type dementia was 59% in the high Alzheimer's disease likelihood group, 22% in the isolated amyloid pathology group, 24% in the suspected non-Alzheimer pathophysiology group, and 5% in the low Alzheimer's disease likelihood group. Our findings support the use of the proposed research criteria to identify Alzheimer's disease at the mild cognitive impairment stage. In clinical settings, the use of both amyloid and neuronal injury markers as proposed by the National Institute of Ageing-Alzheimer Association criteria offers the most accurate prognosis. For clinical trials, selection of subjects in the National Institute of Ageing-Alzheimer Association high Alzheimer's disease likelihood group or the International Working Group-2 prodromal Alzheimer's disease group could be considered.
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