Michela Pievani

Michela Pievani

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Michela Pievani

Laboratory of Alzheimer's Neuroimaging and Epidemiology (LANE), IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy

Research Focus & Metrics

Academic Career Length

21Years (2006-Present)

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

Representative Publications

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1 September 2016 in Ageing Research Reviews
Verified
Journal Article
Closed access
LPLorenzo Pini
Lorenzo Pini
MPMichela Pievani
Michela Pievani
MBMartina Bocchetta
Martina Bocchetta
DADaniele Altomare
Daniele Altomare
PBPaolo Bosco
Paolo Bosco
GFGiovanni B. Frisoni
Giovanni B. Frisoni

1 August 2012 in Neurobiology of Aging
Verified
Journal Article
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FAFederica Agosta
Federica Agosta
MPMichela Pievani
Michela Pievani
CGCristina Geroldi
Cristina Geroldi
MCMassimiliano Copetti
Massimiliano Copetti
GFGiovanni B. Frisoni
Giovanni B. Frisoni
Massimo FilippiMassimo Filippi
Massimo Filippi

1 March 2015 in The Lancet Neurology
Verified
Journal Article
Open access
JRJonathan D Rohrer
Jonathan D Rohrer
JNJennifer M Nicholas
Jennifer M Nicholas
DCDavid M Cash
David M Cash
JSJohn van Swieten
John van Swieten
EDElise Dopper
Elise Dopper
MRMartin N Rossor
Martin N Rossor
Frontotemporal dementia is a highly heritable neurodegenerative disorder. In about a third of patients, the disease is caused by autosomal dominant genetic mutations usually in one of three genes: progranulin (GRN), microtubule-associated protein tau (MAPT), or chromosome 9 open reading frame 72 (C9orf72). Findings from studies of other genetic dementias have shown neuroimaging and cognitive changes before symptoms onset, and we aimed to identify whether such changes could be shown in frontotemporal dementia. We recruited participants to this multicentre study who either were known carriers of a pathogenic mutation in GRN, MAPT, or C9orf72, or were at risk of carrying a mutation because a first-degree relative was a known symptomatic carrier. We calculated time to expected onset as the difference between age at assessment and mean age at onset within the family. Participants underwent a standardised clinical assessment and neuropsychological battery. We did MRI and generated cortical and subcortical volumes using a parcellation of the volumetric T1-weighted scan. We used linear mixed-effects models to examine whether the association of neuropsychology and imaging measures with time to expected onset of symptoms differed between mutation carriers and non-carriers. Between Jan 30, 2012, and Sept 15, 2013, we recruited participants from 11 research sites in the UK, Italy, the Netherlands, Sweden, and Canada. We analysed data from 220 participants: 118 mutation carriers (40 symptomatic and 78 asymptomatic) and 102 non-carriers. For neuropsychology measures, we noted the earliest significant differences between mutation carriers and non-carriers 5 years before expected onset, when differences were significant for all measures except for tests of immediate recall and verbal fluency. We noted the largest Z score differences between carriers and non-carriers 5 years before expected onset in tests of naming (Boston Naming Test -0·7; SE 0·3) and executive function (Trail Making Test Part B, Digit Span backwards, and Digit Symbol Task, all -0·5, SE 0·2). For imaging measures, we noted differences earliest for the insula (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume was 0·80% in mutation carriers and 0·84% in non-carriers; difference -0·04, SE 0·02) followed by the temporal lobe (at 10 years before expected symptom onset, mean volume as a percentage of total intracranial volume 8·1% in mutation carriers and 8·3% in non-carriers; difference -0·2, SE 0·1). Structural imaging and cognitive changes can be identified 5-10 years before expected onset of symptoms in asymptomatic adults at risk of genetic frontotemporal dementia. These findings could help to define biomarkers that can stage presymptomatic disease and track disease progression, which will be important for future therapeutic trials. Centres of Excellence in Neurodegeneration.

1 September 2011 in The Lancet Neurology
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Journal Article
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MPMichela Pievani
Michela Pievani
WHWillem de Haan
Willem de Haan
TWTao Wu
Tao Wu
WSWilliam W Seeley
William W Seeley
GFGiovanni B. Frisoni
Giovanni B. Frisoni

9 February 2007 in Brain
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Journal Article
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GFGiovanni B. Frisoni
Giovanni B. Frisoni
MPMichela Pievani
Michela Pievani
CTCristina Testa
Cristina Testa
FSFrancesca Sabattoli
Francesca Sabattoli
LBLorena Bresciani
Lorena Bresciani
PTPaul M. Thompson
Paul M. Thompson
Clinical observations have suggested that the neuropsychological profile of early and late onset forms of Alzheimer's disease (EOAD and LOAD) differ in that neocortical functions are more affected in the former and learning in the latter, suggesting that they might be different diseases. The aim of this study is to assess the brain structural basis of these observations, and test whether neocortical areas are more heavily affected in EOAD and medial temporal areas in LOAD. Fifteen patients with EOAD and 15 with LOAD (onset before and after age 65; Mini Mental State Examination 19.8, SD 4.0 and 20.7, SD 4.2) were assessed with a neuropsychological battery and high-resolution MRI together with 1:1 age- and sex-matched controls. Cortical atrophy was assessed with cortical pattern matching, and hippocampal atrophy with region-of-interest-based analysis. EOAD patients performed more poorly than LOAD on visuospatial, frontal-executive and learning tests. EOAD patients had the largest atrophy in the occipital [25% grey matter (GM) loss in the left and 24% in the right hemisphere] and parietal lobes (23% loss on both sides), while LOAD patients were remarkably atrophic in the hippocampus (21 and 22% loss). Hippocampal GM loss of EOAD (9 and 16% to the left and right) and occipital (12 and 14%) and parietal (13 and 12%) loss of LOAD patients were less marked. In EOAD, GM loss of 25% or more was mapped to large neocortical areas and affected all lobes, with relative sparing of primary sensory, motor, and visual cortex, and anterior cingulate and orbital cortex. In LOAD, GM loss was diffusely milder (below 15%); losses of 15–20% were confined to temporoparietal and retrosplenial cortex, and reached 25% in restricted areas of the medial temporal lobe and right superior temporal gyrus. These findings indicate that EOAD and LOAD differ in their typical topographic patterns of brain atrophy, suggesting different predisposing or aetiological factors.

1 February 2020 in The Lancet Neurology
Verified
Journal Article
Open access
KMKatrina M Moore
Katrina M Moore
JNJennifer Nicholas
Jennifer Nicholas
MGMurray Grossman
Murray Grossman
CMCorey T McMillan
Corey T McMillan
DIDavid J Irwin
David J Irwin
DGDaniel Geschwind
Daniel Geschwind
Frontotemporal dementia is a heterogenous neurodegenerative disorder, with about a third of cases being genetic. Most of this genetic component is accounted for by mutations in GRN, MAPT, and C9orf72. In this study, we aimed to complement previous phenotypic studies by doing an international study of age at symptom onset, age at death, and disease duration in individuals with mutations in GRN, MAPT, and C9orf72. In this international, retrospective cohort study, we collected data on age at symptom onset, age at death, and disease duration for patients with pathogenic mutations in the GRN and MAPT genes and pathological expansions in the C9orf72 gene through the Frontotemporal Dementia Prevention Initiative and from published papers. We used mixed effects models to explore differences in age at onset, age at death, and disease duration between genetic groups and individual mutations. We also assessed correlations between the age at onset and at death of each individual and the age at onset and at death of their parents and the mean age at onset and at death of their family members. Lastly, we used mixed effects models to investigate the extent to which variability in age at onset and at death could be accounted for by family membership and the specific mutation carried. Data were available from 3403 individuals from 1492 families: 1433 with C9orf72 expansions (755 families), 1179 with GRN mutations (483 families, 130 different mutations), and 791 with MAPT mutations (254 families, 67 different mutations). Mean age at symptom onset and at death was 49·5 years (SD 10·0; onset) and 58·5 years (11·3; death) in the MAPT group, 58·2 years (9·8; onset) and 65·3 years (10·9; death) in the C9orf72 group, and 61·3 years (8·8; onset) and 68·8 years (9·7; death) in the GRN group. Mean disease duration was 6·4 years (SD 4·9) in the C9orf72 group, 7·1 years (3·9) in the GRN group, and 9·3 years (6·4) in the MAPT group. Individual age at onset and at death was significantly correlated with both parental age at onset and at death and with mean family age at onset and at death in all three groups, with a stronger correlation observed in the MAPT group (r=0·45 between individual and parental age at onset, r=0·63 between individual and mean family age at onset, r=0·58 between individual and parental age at death, and r=0·69 between individual and mean family age at death) than in either the C9orf72 group (r=0·32 individual and parental age at onset, r=0·36 individual and mean family age at onset, r=0·38 individual and parental age at death, and r=0·40 individual and mean family age at death) or the GRN group (r=0·22 individual and parental age at onset, r=0·18 individual and mean family age at onset, r=0·22 individual and parental age at death, and r=0·32 individual and mean family age at death). Modelling showed that the variability in age at onset and at death in the MAPT group was explained partly by the specific mutation (48%, 95% CI 35-62, for age at onset; 61%, 47-73, for age at death), and even more by family membership (66%, 56-75, for age at onset; 74%, 65-82, for age at death). In the GRN group, only 2% (0-10) of the variability of age at onset and 9% (3-21) of that of age of death was explained by the specific mutation, whereas 14% (9-22) of the variability of age at onset and 20% (12-30) of that of age at death was explained by family membership. In the C9orf72 group, family membership explained 17% (11-26) of the variability of age at onset and 19% (12-29) of that of age at death. Our study showed that age at symptom onset and at death of people with genetic frontotemporal dementia is influenced by genetic group and, particularly for MAPT mutations, by the specific mutation carried and by family membership. Although estimation of age at onset will be an important factor in future pre-symptomatic therapeutic trials for all three genetic groups, our study suggests that data from other members of the family will be particularly helpful only for individuals with MAPT mutations. Further work in identifying both genetic and environmental factors that modify phenotype in all groups will be important to improve such estimates. UK Medical Research Council, National Institute for Health Research, and Alzheimer's Society.