Frontotemporal dementia in genetic forms is highly heterogeneous and begins many years to prior symptom onset, complicating disease understanding and treatment development. Unifying methods to stage ...the disease during both the presymptomatic and symptomatic phases are needed for the development of clinical trials outcomes. Here we used the contrastive trajectory inference (cTI), an unsupervised machine learning algorithm that analyzes temporal patterns in high‐dimensional large‐scale population datasets to obtain individual scores of disease stage. We used cross‐sectional MRI data (gray matter density, T1/T2 ratio as a proxy for myelin content, resting‐state functional amplitude, gray matter fractional anisotropy, and mean diffusivity) from 383 gene carriers (269 presymptomatic and 115 symptomatic) and a control group of 253 noncarriers in the Genetic Frontotemporal Dementia Initiative. We compared the cTI‐obtained disease scores to the estimated years to onset (age—mean age of onset in relatives), clinical, and neuropsychological test scores. The cTI based disease scores were correlated with all clinical and neuropsychological tests (measuring behavioral symptoms, attention, memory, language, and executive functions), with the highest contribution coming from mean diffusivity. Mean cTI scores were higher in the presymptomatic carriers than controls, indicating that the method may capture subtle pre‐dementia cerebral changes, although this change was not replicated in a subset of subjects with complete data. This study provides a proof of concept that cTI can identify data‐driven disease stages in a heterogeneous sample combining different mutations and disease stages of genetic FTD using only MRI metrics.
Unifying methods to stage genetic frontotemporal dementia during both the presymptomatic and symptomatic phases are needed for the development of clinical trials outcomes. We applied an unsupervised machine learning algorithm the contrastive trajectory inference (cTI) to multi‐modal MRI from presymptomatic and symptomatic carriers of FTD‐causing mutations to obtain individual scores of disease stage. The cTI based disease scores were correlated with all clinical and neuropsychological tests (measuring behavioral symptoms, attention, memory, language, and executive functions), with the highest contribution coming from mean diffusivity. This study provides a proof of concept that cTI can identify data‐driven disease stages in a heterogeneous sample combining different mutations and disease stages of genetic FTD using only MRI metrics.
Abstract
Background
Early‐onset dementia (EOD; <65 years) raises both diagnostic and social/health care challenges. Services for dementia are often designed for the elderly and might have ...difficulties supplying EOD needs. Clinical and epidemiological data are needed for care planning.
Method
We aim to describe the demographic and the clinical characteristics of all the new referrals to our EOD clinic during the last 4 years (2016‐2019). Clinical charts were reviewed retrospectively. Both, sporadic and genetic cases were included in the analysis. We evaluate the type of symptoms, type and frequency of ancillary tests requested and final diagnosis.
Results
We evaluated 477 new early‐onset patients mean age at consultation (MAC) 54.6 years (SD=±9.6), 56% female during this period. The aim of the first visit was genetic counseling in 17.8% MAC 48.3(±13.3), 55.3% female and evaluation of sporadic cases in 82.2% MAC 56(±8), 56.1% female Figures 1 & 2. Among sporadic cases, memory complains were the main symptom (67.1%), followed by behavioral (13%) and language disturbance (11.2%). Complete neuropsychological evaluation was performed in 61.2%, CSF biomarkers in 30.9%, PET‐FDG in 22.4%, PET‐amyloid in 12.5% and genetic testing in 10.5%. Subjective Cognitive Decline (SCD) was diagnosed in 51.8% of these sporadic cases MAC 54.2(±8), 63.5% female, Mean MMSE 27(±4), while an abnormal cognition was found in the 48.2% MAC 58(±7.5), 48.1% female, Mean MMSE 23(±6). Regarding EOD causes, 54% was due to neurodegenerative dementias MAC 60(±5.5), 47.1% females, MMSE 22(±6) and 46% to non‐neurodegenerative MAC 55.5(±8.8), 49.4% female, Mean MMSE 25(±5). EOD mean time to diagnosis was 3.1 years (±3.75) with no differences between groups (p=0,207). In neurodegenerative dementias, AD constitutes 51% MAC 61.6(±4), 51.9% female, Mean MMSE 20(±6) and Frontotemporal lobular degeneration (FTLD) 34.3% MAC 58.5(±5.3), 45,7% female, Mean MMSE 24(±5).
Conclusion
SCD is a frequent diagnosis among new referrals to EOD clinics. AD is the most frequent neurodegenerative EOD, followed by FTLD. Non‐neurodegenerative causes of EOD are frequent and heterogeneous. Long delay until diagnosis suggests that new care policies are needed to identify EOD in early stages.
Background
ABCA7 gene (ATP‐binding cassette transporter A7) loss‐of‐function mutations are related to increased risk of suffering Alzheimer’s disease (AD). On the other hand, mutations in GRN ...(Progranulin) gene are causative of frontotemporal dementia (FTD).
Methods
The proband was a patient diagnosed from semantic variant of primary progressive aphasia. Age at onset was at 50 years‐old, presenting progressive cognitive decline with an important language loss. The MRI showed a left temporal atrophy. AD CSF biomarkers were normal and no familial history of dementia was reported. Next generation sequencing was performed with Illumina NextSeq500. Single nucleotide variants were detected using GATK and copy number variants using ExomeDepth algorithm. Sanger sequencing was performed for GRN variant confirmation and MLPA technique for ABCA7 deletion validation. C9orf72 repeat expansion was studied with a repeat primed PCR and fragment analysis. Biological samples from his mother and a brother were obtained. Commercial ELISA kit was used to measure serum PGRN levels (Adipogen).
Results
Patient showed an ABCA7 partial deletion (exons 17‐47) plus 4 contiguous genes, of a total of 105 kb in size (hg19 chr19:g.1048865_1154298). Deletion was confirmed in the proband and discarded in the proband’s mother and brother by MLPA. Patient and his mother (asymptomatic at 81 yo) were also carriers of a reported GRN variant, p.(Asp33Glu; rs63750742). Progranulin serum levels were normal in the patient and his family members. C9orf72 screening was negative.
Conclusions
The patient harbored two genetic alterations in genes related to dementia risk, although it is unlikely that any of them alone could be responsible of the FTD phenotype. ABCA7 deletion should be de novo or father inherited. ABCA7 protein truncating variant at exon 14 (p.Arg578fs), which has a similar protein consequence, is relatively frequent in control population, although has showed a 1.8‐fold enrichment in AD patients. Moreover, GRN variant does not seem to be pathogenic or low penetrance because proband’s mother is unaffected and serum progranulin levels are normal. In conclusion, these variants per se are likely not sufficient to cause the disease, but rather risk variants of intermediate to high penetrance along with other factors.
Background
Early‐onset dementia (EOD; <65 years) raises both diagnostic and social/health care challenges. Services for dementia are often designed for the elderly and might have difficulties ...supplying EOD needs. Clinical and epidemiological data are needed for care planning.
Method
We aim to describe the demographic and the clinical characteristics of all the new referrals to our EOD clinic during the last 4 years (2016‐2019). Clinical charts were reviewed retrospectively. Both, sporadic and genetic cases were included in the analysis. We evaluate the type of symptoms, type and frequency of ancillary tests requested and final diagnosis.
Results
We evaluated 477 new early‐onset patients mean age at consultation (MAC) 54.6 years (SD=±9.6), 56% female during this period. The aim of the first visit was genetic counseling in 17.8% MAC 48.3(±13.3), 55.3% female and evaluation of sporadic cases in 82.2% MAC 56(±8), 56.1% female Figures 1 & 2. Among sporadic cases, memory complains were the main symptom (67.1%), followed by behavioral (13%) and language disturbance (11.2%). Complete neuropsychological evaluation was performed in 61.2%, CSF biomarkers in 30.9%, PET‐FDG in 22.4%, PET‐amyloid in 12.5% and genetic testing in 10.5%. Subjective Cognitive Decline (SCD) was diagnosed in 51.8% of these sporadic cases MAC 54.2(±8), 63.5% female, Mean MMSE 27(±4), while an abnormal cognition was found in the 48.2% MAC 58(±7.5), 48.1% female, Mean MMSE 23(±6). Regarding EOD causes, 54% was due to neurodegenerative dementias MAC 60(±5.5), 47.1% females, MMSE 22(±6) and 46% to non‐neurodegenerative MAC 55.5(±8.8), 49.4% female, Mean MMSE 25(±5). EOD mean time to diagnosis was 3.1 years (±3.75) with no differences between groups (p=0,207). In neurodegenerative dementias, AD constitutes 51% MAC 61.6(±4), 51.9% female, Mean MMSE 20(±6) and Frontotemporal lobular degeneration (FTLD) 34.3% MAC 58.5(±5.3), 45,7% female, Mean MMSE 24(±5).
Conclusion
SCD is a frequent diagnosis among new referrals to EOD clinics. AD is the most frequent neurodegenerative EOD, followed by FTLD. Non‐neurodegenerative causes of EOD are frequent and heterogeneous. Long delay until diagnosis suggests that new care policies are needed to identify EOD in early stages.
Abstract
Background
ABCA7
gene (ATP‐binding cassette transporter A7) loss‐of‐function mutations are related to increased risk of suffering Alzheimer’s disease (AD). On the other hand, mutations in
...GRN
(Progranulin) gene are causative of frontotemporal dementia (FTD).
Methods
The proband was a patient diagnosed from semantic variant of primary progressive aphasia. Age at onset was at 50 years‐old, presenting progressive cognitive decline with an important language loss. The MRI showed a left temporal atrophy. AD CSF biomarkers were normal and no familial history of dementia was reported. Next generation sequencing was performed with Illumina NextSeq500. Single nucleotide variants were detected using GATK and copy number variants using ExomeDepth algorithm. Sanger sequencing was performed for
GRN
variant confirmation and MLPA technique for
ABCA7
deletion validation.
C9orf72
repeat expansion was studied with a repeat primed PCR and fragment analysis. Biological samples from his mother and a brother were obtained. Commercial ELISA kit was used to measure serum PGRN levels (Adipogen).
Results
Patient showed an
ABCA7
partial deletion (exons 17‐47) plus 4 contiguous genes, of a total of 105 kb in size (hg19 chr19:g.1048865_1154298). Deletion was confirmed in the proband and discarded in the proband’s mother and brother by MLPA. Patient and his mother (asymptomatic at 81 yo) were also carriers of a reported
GRN
variant, p.(Asp33Glu; rs63750742). Progranulin serum levels were normal in the patient and his family members.
C9orf72
screening was negative.
Conclusions
The patient harbored two genetic alterations in genes related to dementia risk, although it is unlikely that any of them alone could be responsible of the FTD phenotype.
ABCA7
deletion should be
de novo
or father inherited.
ABCA7
protein truncating variant at exon 14 (p.Arg578fs), which has a similar protein consequence, is relatively frequent in control population, although has showed a 1.8‐fold enrichment in AD patients. Moreover,
GRN
variant does not seem to be pathogenic or low penetrance because proband’s mother is unaffected and serum progranulin levels are normal. In conclusion, these variants
per se
are likely not sufficient to cause the disease, but rather risk variants of intermediate to high penetrance along with other factors.
INTRODUCTION
Effective longitudinal biomarkers that track disease progression are needed to characterize the presymptomatic phase of genetic frontotemporal dementia (FTD). We investigate the utility ...of cerebral perfusion as one such biomarker in presymptomatic FTD mutation carriers.
METHODS
We investigated longitudinal profiles of cerebral perfusion using arterial spin labeling magnetic resonance imaging in 42 C9orf72, 70 GRN, and 31 MAPT presymptomatic carriers and 158 non‐carrier controls. Linear mixed effects models assessed perfusion up to 5 years after baseline assessment.
RESULTS
Perfusion decline was evident in all three presymptomatic groups in global gray matter. Each group also featured its own regional pattern of hypoperfusion over time, with the left thalamus common to all groups. Frontal lobe regions featured lower perfusion in those who symptomatically converted versus asymptomatic carriers past their expected age of disease onset.
DISCUSSION
Cerebral perfusion is a potential biomarker for assessing genetic FTD and its genetic subgroups prior to symptom onset.
Highlights
Gray matter perfusion declines in at‐risk genetic frontotemporal dementia (FTD).
Regional perfusion decline differs between at‐risk genetic FTD subgroups .
Hypoperfusion in the left thalamus is common across all presymptomatic groups.
Converters exhibit greater right frontal hypoperfusion than non‐converters past their expected conversion date.
Cerebral hypoperfusion is a potential early biomarker of genetic FTD.
Background
The amyloid deposition (A) in the 2018 ATN classification of Alzheimer disease can be assessed by CSF Aβ 1‐42 or amyloid PET. Although the agreement between them is high, it is not exact.
...Method
We selected patients from the Alzheimer’s disease and other cognitive disorders Unit at Hospital Clínic of Barcelona with available amyloid PET and lumbar puncture, with a maximum difference of time of one and a half year between them. We used F18 Florbetapir (n=27), F18 Florbetaben (n=7), F18 Flutemetamol (n=16) or 11C‐PIB (n=2) as tracers for amyloid PET. CSF Aβ 1‐42, total tau (tTau) and phosphorylated tau (pTau) were measured using INNOTEST® Fujirebio until June 2019 and using LUMIPULSE® Fujirebio after June 2019. We analyzed the agreement between amyloid PET and CSF biomarkers.
Result
We included 52 patients. They had been diagnosed of Alzheimer disease (n=32), frontotemporal dementia (n=11), Lewy body disease (n=2) and psychiatric disorders (n=7) (Table 1).
There was a perfect agreement between CSF biomarkers and amyloid PET when CSF biomarkers were all normal or all altered (Figure 1): All patients with CSF A+T+N+ (n=19) had a positive amyloid PET and all patients with CSF A‐T‐N‐ (n=7) had a negative amyloid PET. Agreement decreased with other CSF results. Only 11/19 patients with CSF A+T‐N‐ had a positive amyloid PET. 31/32 (97%) patients with positive amyloid PET had low Aβ 1‐42 levels (A+) but only 11/20 (55%) patients with negative amyloid PET had normal Aβ 1‐42 levels (A‐).
Conclusion
CSF biomarkers and amyloid PET showed a perfect agreement when CSF biomarkers were all normal or all altered. For other CSF ATN results, agreement with amyloid PET was much lower.
Abstract
Background
Changes in functional connectivity (FC) networks have been extensively reported in late onset Alzheimer’s Disease (AD), being the default mode network (DMN) the key system to be ...affected. However, it remains unclear if FC in early‐onset AD (EOAD) would show a similar pattern than late onset AD.
Method
We studied 48 EOAD patients (mean age=57.40±5.53 years) and 31 healthy controls (CTR, mean age=58.22±3.94 years) who underwent resting state functional magnetic resonance imaging (rs‐fMRI) in a 3T MRI scanner. We used group independent component analysis to identify the main resting state networks (RSNs). We studied group‐differences in the spatial extent of these networks, in the amplitude of their temporal oscillations and in the temporal correlation between pairs of networks, using FSLNETS. We also evaluated the discrimination capability of FC patterns by using a support vector machine (SVM) classifier.
Result
We identified 17 RSNs that were further classified into DMN, visual, motor, executive, salience and cerebellum systems. The network spatial maps' vertex‐wise analysis shows regional increases of some executive networks in EOAD (p<0.05, FWE corrected), suggesting increased aberrant local connectivity surrounding the main RSN nodes. In the temporal domain, we find decreases in amplitude in the posterior DMN and the salience network (p<0.05, corrected), and increases in the anterior DMN and the cerebellum networks. With the study of correlations between networks we describe a pattern of altered inter‐network connectivity that involves both increases and decreases of connectivity. Importantly, the entire pattern of network correlations discriminated AD from CTR subjects with an accuracy of 83.5%.
Conclusion
Our results suggest that EOAD is characterized by a complex pattern of FC alterations involving alterations in the amplitude of the main RSNs and in the way that they interconnect. Increase in connectivity in short‐range connections surrounding the main nodes might be a consequence of the decreases of larger connections between nodes. Alterations in the salience network differ from the late onset AD literature. Overall, the entire FC pattern gives a good classification rate suggesting that it might be a good biomarker for EOAD.
Background
Changes in functional connectivity (FC) networks have been extensively reported in late onset Alzheimer’s Disease (AD), being the default mode network (DMN) the key system to be affected. ...However, it remains unclear if FC in early‐onset AD (EOAD) would show a similar pattern than late onset AD.
Method
We studied 48 EOAD patients (mean age=57.40±5.53 years) and 31 healthy controls (CTR, mean age=58.22±3.94 years) who underwent resting state functional magnetic resonance imaging (rs‐fMRI) in a 3T MRI scanner. We used group independent component analysis to identify the main resting state networks (RSNs). We studied group‐differences in the spatial extent of these networks, in the amplitude of their temporal oscillations and in the temporal correlation between pairs of networks, using FSLNETS. We also evaluated the discrimination capability of FC patterns by using a support vector machine (SVM) classifier.
Result
We identified 17 RSNs that were further classified into DMN, visual, motor, executive, salience and cerebellum systems. The network spatial maps' vertex‐wise analysis shows regional increases of some executive networks in EOAD (p<0.05, FWE corrected), suggesting increased aberrant local connectivity surrounding the main RSN nodes. In the temporal domain, we find decreases in amplitude in the posterior DMN and the salience network (p<0.05, corrected), and increases in the anterior DMN and the cerebellum networks. With the study of correlations between networks we describe a pattern of altered inter‐network connectivity that involves both increases and decreases of connectivity. Importantly, the entire pattern of network correlations discriminated AD from CTR subjects with an accuracy of 83.5%.
Conclusion
Our results suggest that EOAD is characterized by a complex pattern of FC alterations involving alterations in the amplitude of the main RSNs and in the way that they interconnect. Increase in connectivity in short‐range connections surrounding the main nodes might be a consequence of the decreases of larger connections between nodes. Alterations in the salience network differ from the late onset AD literature. Overall, the entire FC pattern gives a good classification rate suggesting that it might be a good biomarker for EOAD.
IntroductionNon-infectious uveitis include a heterogeneous group of sight-threatening and incapacitating conditions. Their correct management sometimes requires the use of immunosuppressive drugs ...(ISDs), prescribed in monotherapy or in combination. Several observational studies showed that the use of ISDs in combination could be more effective than and as safe as their use in monotherapy. However, a direct comparison between these two treatment strategies has not been carried out yet.Methods and analysisThe Combination THerapy with mEthotrexate and adalImumAb for uveitis (CoTHEIA) study is a phase III, multicentre, prospective, randomised, single-blinded with masked outcome assessment, parallel three arms with 1:1:1 allocation, active-controlled, superiority study design, comparing the efficacy, safety and cost-effectiveness of methotrexate, adalimumab or their combination in non-infectious non-anterior uveitis. We aim to recruit 192 subjects. The duration of the treatment and follow-up will last up to 52 weeks, plus 70 days follow-up with no treatment. The complete and maintained resolution of the ocular inflammation will be assessed by masked evaluators (primary outcome). In addition to other secondary measurements of efficacy (quality of life, visual acuity and costs) and safety, we will identify subjects’ subgroups with different treatment responses by developing prediction models based on machine learning techniques using genetic and proteomic biomarkers.Ethics and disseminationThe protocol, annexes and informed consent forms were approved by the Reference Clinical Research Ethic Committee at the Hospital Clínico San Carlos (Madrid, Spain) and the Spanish Agency for Medicines and Health Products. We will elaborate a dissemination plan including production of materials adapted to several formats to communicate the clinical trial progress and findings to a broad group of stakeholders. The promoter will be the only access to the participant-level data, although it can be shared within the legal situation.Trial registration number2020-000130-18; NCT04798755.
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