Michelle K. Lupton

Dr. Michelle K. Lupton


Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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28 February 2019 in Nature Genetics
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Journal Article
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BKBrian W. Kunkle
Brian W. Kunkle
T(The European Alzheimer’s Disease Initiative (Eadi)
The European Alzheimer’s Disease Initiative (Eadi)
BGBenjamin Grenier-Boley
Benjamin Grenier-Boley
RSRebecca Sims
Rebecca Sims
JBJoshua C. Bis
Joshua C. Bis
MPMargaret A. Pericak-Vance
Margaret A. Pericak-Vance

17 July 2017 in Nature Genetics
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Journal Article
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RSRebecca Sims
Rebecca Sims
SLSven J van der Lee
Sven J van der Lee
ANAdam C Naj
Adam C Naj
CBCéline Bellenguez
Céline Bellenguez
NBNandini Badarinarayan
Nandini Badarinarayan
GSGerard D Schellenberg
Gerard D Schellenberg

11 December 2013 in Nature
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Journal Article
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CCCarlos Cruchaga
Carlos Cruchaga
CKCeleste M. Karch
Celeste M. Karch
SJSheng Chih Jin
Sheng Chih Jin
BBBruno A. Benitez
Bruno A. Benitez
YCYefei Cai
Yefei Cai
AGAlison Goate
Alison Goate

18 April 2024 in Nature Genetics
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Journal Article
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CNCaroline Nievergelt
Caroline Nievergelt
AMAdam X. Maihofer
Adam X. Maihofer
EAElizabeth G. Atkinson
Elizabeth G. Atkinson
CCChia-Yen Chen
Chia-Yen Chen
KCKarmel W. Choi
Karmel W. Choi
KKKarestan C. Koenen
Karestan C. Koenen

7 July 2014 in Alzheimer's & Dementia
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Journal Article
Open access
AHAbdul Hye
Abdul Hye
JRJoanna Riddoch‐Contreras
Joanna Riddoch‐Contreras
ABAlison L. Baird
Alison L. Baird
NANicholas Ashton
Nicholas Ashton
CBChantal Bazenet
Chantal Bazenet
SLSimon Lovestone
Simon Lovestone
Background: The study aimed to validate previously discovered plasma biomarkers associated with AD, using a design based on imaging measures as surrogate for disease severity and assess their prognostic value in predicting conversion to dementia.Methods: Three multicenter cohorts of cognitively healthy elderly, mild cognitive impairment (MCI), and AD participants with standardized clinical assessments and structural neuroimaging measures were used. Twenty‐six candidate proteins were quantified in 1148 subjects using multiplex (xMAP) assays.Results: Sixteen proteins correlated with disease severity and cognitive decline. Strongest associations were in the MCI group with a panel of 10 proteins predicting progression to AD (accuracy 87%, sensitivity 85%, and specificity 88%).Conclusions: We have identified 10 plasma proteins strongly associated with disease severity and disease progression. Such markers may be useful for patient selection for clinical trials and assessment of patients with predisease subjective memory complaints.

10 March 2015 in Molecular Psychiatry
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Journal Article
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TCT-K Clarke
T-K Clarke
MLMichelle K. Lupton
Michelle K. Lupton
AFA M Fernandez-Pujals
A M Fernandez-Pujals
JSJ Starr
J Starr
GDG Davies
G Davies
AMA M McIntosh
A M McIntosh
Cognitive impairment is common among individuals diagnosed with autism spectrum disorder (ASD) and attention-deficit hyperactivity disorder (ADHD). It has been suggested that some aspects of intelligence are preserved or even superior in people with ASD compared with controls, but consistent evidence is lacking. Few studies have examined the genetic overlap between cognitive ability and ASD/ADHD. The aim of this study was to examine the polygenic overlap between ASD/ADHD and cognitive ability in individuals from the general population. Polygenic risk for ADHD and ASD was calculated from genome-wide association studies of ASD and ADHD conducted by the Psychiatric Genetics Consortium. Risk scores were created in three independent cohorts: Generation Scotland Scottish Family Health Study (GS:SFHS) (n=9863), the Lothian Birth Cohorts 1936 and 1921 (n=1522), and the Brisbane Adolescent Twin Sample (BATS) (n=921). We report that polygenic risk for ASD is positively correlated with general cognitive ability (beta=0.07, P=6 × 10−7, r2=0.003), logical memory and verbal intelligence in GS:SFHS. This was replicated in BATS as a positive association with full-scale intelligent quotient (IQ) (beta=0.07, P=0.03, r2=0.005). We did not find consistent evidence that polygenic risk for ADHD was associated with cognitive function; however, a negative correlation with IQ at age 11 years (beta=−0.08, Z=−3.3, P=0.001) was observed in the Lothian Birth Cohorts. These findings are in individuals from the general population, suggesting that the relationship between genetic risk for ASD and intelligence is partly independent of clinical state. These data suggest that common genetic variation relevant for ASD influences general cognitive ability.