Investigating the combination of plasma amyloid-beta and geroscience biomarkers on the incidence of clinically meaningful cognitive decline in older adults

S. Lehéricy | M. Chupin | J. Dartigues | R. Bateman | J. Darcourt | M. Zanca | K. Bennys | J. Touchon | M. Allard | C. Dufouil | P. Livet | P. Payoux | S. Belleville | T. Voisin | S. Andrieu | S. Chanalet | G. Abellán van Kan | B. Vellas | N. Coley | S. Guyonnet | I. Carrié | L. Brigitte | C. Faisant | J. Delrieu | H. Villars | Emeline Combrouze | Carole Badufle | A. Zueras | C. Cantet | Christophe Morin | C. Dupuy | C. Caillaud | P. Ousset | S. Willis | B. Gilbert | F. Fontaine | Isabelle Marcet | F. Delva | Sandrine Cerda | Corinne Costes | O. Rouaud | P. Manckoundia | V. Quipourt | S. Marilier | Evelyne Franon | L. Bories | Marie-Laure Pader | Marie-France Basset | Bruno Lapoujade | V. Faure | Michael Li Yung Tong | C. Malick-Loiseau | Evelyne Cazaban-Campistron | Colette Blatge | T. Dantoine | C. Laubarie-Mouret | I. Saulnier | J. Clément | M. Picat | S. Willebois | I. Desormais | M. Bonnefoy | P. Rebaudet | Claire Gédéon | Catherine Burdet | Flavien Terracol | Stephanie Roth | S. Chaillou | S. Louchart | K. Sudres | N. Lebrun | Nadège Barro-Belaygues | A. Gabelle | Lynda Touati | C. Marelli | Cécile Pays | C. Gervais | S. Gonfrier | Y. Gasnier | S. Bordes | Danièle Begorre | Christian Carpuat | Khaled Khales | Jean-François Lefebvre | Samira Misbah El Idrissi | Pierre Skolil | J. Salles | Ali Bouhayia | F. Ricolfi | M. Martel | A. Bonafe | Françoise Hugon | F. Bonneville | C. Cognard | Sophie Peiffer | A. Hitzel | L. Molinier | H. Derumeaux | C. Vinel | P. de Souto Barreto | J. Morley | S. Caspar-Bauguil | Y. Rolland | Geetika Aggarwal | A. Parini | F. Cotton | K. Giudici | F. Le Duff | J. F. Mangin | W. Lu | Andrew D. Nguyen | Yan Li | M. Cuffi | Alexandra Foubert | Alain Pesce | Philippe Robert | Dominique Dubois | Jacques Monteil | N. Costa | A. Pesce | A. Nguyen | P. Olivier‐Abbal | L. Bernard‐Bourzeix | N. Cardinaud | A. Romano | B. Perret | Bruno Sophie Isabelle Lauréane Catherine Franҫoise Julie Vellas Guyonnet Carrié Brigitte Faisant Lal | Franҫoise Lala | Franҫoise Desclaux | Franҫois Chollet | P. Robert | Claire Vinel | Valérie Faure | Wan-Hsuan Lu | Stéphanie Willebois | Pascale Rebaudet

[1]  L. Partridge,et al.  A neuronal blood marker is associated with mortality in old age , 2021, Nature Aging.

[2]  A. Langkilde,et al.  Association of GDF15 with inflammation and physical function during aging and recovery after acute hospitalization: a longitudinal study of older patients and age-matched controls. , 2021, The journals of gerontology. Series A, Biological sciences and medical sciences.

[3]  R. Bateman,et al.  Assessment of Plasma Amyloid-β42/40 and Cognitive Decline Among Community-Dwelling Older Adults , 2020, JAMA network open.

[4]  K. Blennow,et al.  Individualized prognosis of cognitive decline and dementia in mild cognitive impairment based on plasma biomarker combinations , 2020, Nature Aging.

[5]  D. Levy,et al.  Growth Differentiation Factor 15 and NT‐proBNP as Blood‐Based Markers of Vascular Brain Injury and Dementia , 2020, Journal of the American Heart Association.

[6]  A. Sandvig,et al.  Bridging the Gap Between Fluid Biomarkers for Alzheimer’s Disease, Model Systems, and Patients , 2020, Frontiers in Aging Neuroscience.

[7]  Ludger J. E. Goeminne,et al.  Growth differentiation factor 15 protects against the aging‐mediated systemic inflammatory response in humans and mice , 2020, Aging cell.

[8]  M. Shong,et al.  The Role of Growth Differentiation Factor 15 in Energy Metabolism , 2020, Diabetes & metabolism journal.

[9]  Heleen M A Hendriksen,et al.  Plasma amyloid is associated with the rate of cognitive decline in cognitively normal elderly: the SCIENCe project , 2020, Neurobiology of Aging.

[10]  J. Berkhof,et al.  Biomarker-based prognosis for people with mild cognitive impairment (ABIDE): a modelling study , 2019, The Lancet Neurology.

[11]  James G. Bollinger,et al.  High-precision plasma β-amyloid 42/40 predicts current and future brain amyloidosis , 2019, Neurology.

[12]  M. Albert,et al.  Plasma Markers of Inflammation Linked to Clinical Progression and Decline During Preclinical AD , 2019, Front. Aging Neurosci..

[13]  M. Pisani,et al.  GDF15 Is an Inflammation-Induced Central Mediator of Tissue Tolerance , 2019, Cell.

[14]  K. Blennow,et al.  Performance of Fully Automated Plasma Assays as Screening Tests for Alzheimer Disease–Related β-Amyloid Status , 2019, JAMA neurology.

[15]  S. Baek,et al.  Growth differentiation factor 15 (GDF15): A survival protein with therapeutic potential in metabolic diseases. , 2019, Pharmacology & therapeutics.

[16]  Magda Tsolaki,et al.  Inflammatory biomarkers in Alzheimer's disease plasma , 2019, Alzheimer's & Dementia.

[17]  J. Neuhaus,et al.  Increases in a Pro-inflammatory Chemokine, MCP-1, Are Related to Decreases in Memory Over Time , 2019, Front. Aging Neurosci..

[18]  D. Bennett,et al.  Investigation of frailty as a moderator of the relationship between neuropathology and dementia in Alzheimer's disease: a cross-sectional analysis of data from the Rush Memory and Aging Project , 2019, The Lancet Neurology.

[19]  A. Hofman,et al.  Inflammatory markers and the risk of dementia and Alzheimer's disease: A meta-analysis , 2018, Alzheimer's & Dementia.

[20]  Ludwig Kappos,et al.  Neurofilaments as biomarkers in neurological disorders , 2018, Nature Reviews Neurology.

[21]  Wei‐Ju Lee,et al.  Plasma MCP-1 and Cognitive Decline in Patients with Alzheimer’s Disease and Mild Cognitive Impairment: A Two-year Follow-up Study , 2018, Scientific Reports.

[22]  Frederik Barkhof,et al.  Interpreting Biomarker Results in Individual Patients With Mild Cognitive Impairment in the Alzheimer’s Biomarkers in Daily Practice (ABIDE) Project , 2017, JAMA neurology.

[23]  Wei‐Ju Lee,et al.  The clinical significance of plasma clusterin and Aβ in the longitudinal follow-up of patients with Alzheimer’s disease , 2017, Alzheimer's Research & Therapy.

[24]  James G. Bollinger,et al.  Amyloid β concentrations and stable isotope labeling kinetics of human plasma specific to central nervous system amyloidosis , 2017, Alzheimer's & Dementia.

[25]  B. Vellas,et al.  Evaluating the clinical relevance of a cognitive composite outcome measure: An analysis of 1414 participants from the 5-year GuidAge Alzheimer's prevention trial , 2016, Alzheimer's & Dementia.

[26]  S. Shinkai,et al.  Secreted growth differentiation factor 15 as a potential biomarker for mitochondrial dysfunctions in aging and age‐related disorders , 2016, Geriatrics & gerontology international.

[27]  P. Sachdev,et al.  Macrophage inhibitory cytokine-1/growth differentiation factor 15 as a marker of cognitive ageing and dementia , 2016, Current opinion in psychiatry.

[28]  Lars Bäckman,et al.  A 2 year multidomain intervention of diet, exercise, cognitive training, and vascular risk monitoring versus control to prevent cognitive decline in at-risk elderly people (FINGER): a randomised controlled trial , 2015, The Lancet.

[29]  O. Garaschuk,et al.  Neuroinflammation in Alzheimer's disease , 2015, The Lancet Neurology.

[30]  P. Wolf,et al.  Plasma amyloid-β and risk of Alzheimer's disease in the Framingham Heart Study , 2015, Alzheimer's & Dementia.

[31]  R. Sperling,et al.  The preclinical Alzheimer cognitive composite: measuring amyloid-related decline. , 2014, JAMA neurology.

[32]  M. Weiner,et al.  MAPT STUDY: A MULTIDOMAIN APPROACH FOR PREVENTING ALZHEIMER'S DISEASE: DESIGN AND BASELINE DATA. , 2014, The journal of prevention of Alzheimer's disease.

[33]  P. Bourin,et al.  Concise Review: Growth Differentiation Factor 15 in Pathology: A Clinical Role? , 2013, Stem cells translational medicine.

[34]  P. Sachdev,et al.  Macrophage inhibitory cytokine‐1 is associated with cognitive impairment and predicts cognitive decline – the Sydney Memory and Aging Study , 2013, Aging cell.

[35]  G. Maurer,et al.  A multi-biomarker risk score improves prediction of long-term mortality in patients with advanced heart failure. , 2013, International journal of cardiology.

[36]  L. Partridge,et al.  The Hallmarks of Aging , 2013, Cell.

[37]  Huaxi Xu,et al.  Apolipoprotein E and Alzheimer disease: risk, mechanisms and therapy , 2013, Nature Reviews Neurology.

[38]  A. Wu,et al.  Multiple Biomarkers for Risk Prediction in Chronic Heart Failure , 2012, Circulation. Heart failure.

[39]  Henrik Zetterberg,et al.  Cerebrospinal fluid levels of β-amyloid 1-42, but not of tau, are fully changed already 5 to 10 years before the onset of Alzheimer dementia. , 2012, Archives of general psychiatry.

[40]  M. Cefalu.  Pointwise Confidence Intervals for the Covariate-adjusted Survivor Function in the Cox Model , 2011 .

[41]  O. Forlenza,et al.  Higher serum sTNFR1 level predicts conversion from mild cognitive impairment to Alzheimer's disease. , 2011, Journal of Alzheimer's disease : JAD.

[42]  Roger Newson,et al.  Comparing the Predictive Powers of Survival Models Using Harrell's C or Somers’ D , 2010 .

[43]  G. Conductier,et al.  The role of monocyte chemoattractant protein MCP1/CCL2 in neuroinflammatory diseases , 2010, Journal of Neuroimmunology.

[44]  G. Halliday,et al.  Monocyte Chemoattractant Protein‐1 Plays a Dominant Role in the Chronic Inflammation Observed in Alzheimer's Disease , 2009, Brain pathology.

[45]  A. Mitchell,et al.  Rate of progression of mild cognitive impairment to dementia – meta‐analysis of 41 robust inception cohort studies , 2009, Acta psychiatrica Scandinavica.

[46]  Georg Kemmler,et al.  Conversion from cognitive health to mild cognitive impairment and Alzheimer's disease: Prediction by plasma amyloid beta 42, medial temporal lobe atrophy and homocysteine , 2008, Neurobiology of Aging.

[47]  K. Wollert,et al.  Growth-differentiation factor-15 in cardiovascular disease , 2007, Basic Research in Cardiology.

[48]  F. Harrell,et al.  Prognostic/Clinical Prediction Models: Multivariable Prognostic Models: Issues in Developing Models, Evaluating Assumptions and Adequacy, and Measuring and Reducing Errors , 2005 .

[49]  David R. Anderson,et al.  Model selection and multimodel inference : a practical information-theoretic approach , 2003 .

[50]  J. Morris.  The Clinical Dementia Rating (CDR) , 1993, Neurology.

[51]  Sterling C. Johnson,et al.  Cerebrospinal Fluid and Plasma Levels of Inflammation Differentially Relate to CNS Markers of Alzheimer's Disease Pathology and Neuronal Damage. , 2018, Journal of Alzheimer's disease : JAD.

[52]  C. Jack,et al.  Framework : Towards a Biological Definition of Alzheimer ’ s Disease 1 2 draft 9-19-17 3 4 5 , 2017 .

[53]  D. Selkoe.  Alzheimer's disease. , 2011, Cold Spring Harbor perspectives in biology.