Citations

Abstract Background: Sentinel lymph node biopsy (SLNB) provides important staging and prognostic information that guides surveillance and adjuvant systemic therapy decisions for patients with cutaneous melanoma. At most centers, SLNB is indicated for patients with cutaneous melanoma with at least a 5% risk of having nodal metastases, typically melanomas ≥0.8 mm in thickness or selected thinner lesions with high-risk features such as elevated mitotic rate and/or ulceration. However, up to 85% of patients who undergo SLNB have a negative result. Currently, there is an unmet clinical need to better identify patients with a low risk of nodal metastasis who may safely forgo SLNB, but otherwise meet established criteria for undergoing SLNB. Previously, a model using primary tumor gene expression profile (GEP) data combined with clinicopathological features (CP) was developed to identify melanoma patients with a low risk of having a positive SLN. The model has been externally validated in multiple retrospective studies. The aim of the MERLIN_001 observational registry study is to prospectively validate the CP-GEP model in an independent multicenter cohort of primary cutaneous melanoma patients, who undergo lymphatic mapping and SLNB per current clinical guidelines. Methods: A total of 9 centers across the US are included in the study with planned enrollment of 2,340 patients, allowing for a loss of up to 30% due to screen failure, tissue loss, low RNA yield, no gene expression profile or failure to perform the planned SLNB. Patients with clinically node-negative cutaneous melanoma and planned SLNB using current guideline indications are eligible for the study and will be followed for five years. Both patients and investigators are blinded to the results (NCT04759781). FFPE material from the initial melanoma biopsy is collected and the GEP of the primary melanoma is assessed. Subsequently, CP-GEP probability scores are calculated and expressed as a binary classification (Low Risk or High Risk for nodal metastasis), which will be compared to SLNB pathology results. Performance metrics for CP-GEP will be evaluated and will include: SLNB Reduction Rate based on Negative Predictive Value, Positive Predictive Value, Sensitivity and Specificity, and the corresponding 95% confidence intervals. Finally, the performance of CP-GEP to stratify patients according to risk of recurrence (recurrence-free survival, distant metastasis-free survival, overall survival) will also be assessed, based on five-year outcomes data. Additional analyses will be performed using the data collected throughout the study. Enrollment of patients started in September 2021 and is ongoing. As of January 2023, 890 patients have been enrolled, representing 46% of the targeted number of patients with a successful SLNB and CP-GEP test result. Citation Format: Tina J. Hieken, Michael E. Egger, Christina V. Angeles, Erin E. Burke, Michael C. Lowe, John R. Hyngstrom, Georgia M. Beasley, Edmund K. Bartlett, Vernon K. Sondak. Merlin_001: a prospective registry study of a primary melanoma gene-signature to predict sentinel node (SN) status and determine its prognostic value for more accurate staging of SN-negative melanoma patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 2 (Clinical Trials and Late-Breaking Research); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(8_Suppl):Abstract nr CT053.

AbstractObjectivePrimary progressive apraxia of speech (PPAOS) is associated with imaging abnormalities in the lateral premotor cortex (LPC) and supplementary motor area (SMA). It is not known whether greater involvement of these regions in either hemisphere is associated with demographics, presenting, and/or longitudinal features.MethodsIn 51 prospectively recruited PPAOS patients who completed [18F]‐fluorodeoxyglucose (FDG) positron emission tomography (PET), we classified patients as left‐dominant, right‐dominant, or symmetric, based on visual assessment of the LPC and SMA on FDG‐PET. SPM and statistical analyses of regional metabolic values were performed. Diagnosis of PPAOS was made if apraxia of speech was present and aphasia absent. Thirteen patients completed ioflupane‐123I (dopamine transporter [DAT]) scans. We compared cross‐sectional and longitudinal clinicopathological, genetic, and neuroimaging characteristics across the three groups, with area under the receiver‐operating curve (AUROC) determined as a measure of effect size.ResultsIn all, 49% of the PPAOS patients were classified as left‐dominant, 31% as right‐dominant, and 20% as symmetric, which was supported by results from the SPM and regional analyses. There were no differences in baseline characteristics. Longitudinally, right‐dominant PPAOS showed faster rates of progression of ideomotor apraxia (AUROC 0.79), behavioral disturbances (AUROC 0.84), including disinhibition symptoms (AUROC 0.82) and negative behaviors (AUROC 0.82), and parkinsonism (AUROC 0.75) compared to left‐dominant PPAOS. Symmetric PPAOS showed faster rates of dysarthria progression compared to left‐dominant (AUROC 0.89) and right‐dominant PPAOS (AUROC 0.79). Five patients showed abnormal DAT uptake. Braak neurofibrillary tangle stage differed across groups (p = 0.01).ConclusionsPatients with PPAOS and a right‐dominant pattern of hypometabolism on FDG‐PET have the fastest rates of decline of behavioral and motor features.

Abstract Staging the severity of Alzheimer’s disease pathology using biomarkers is useful for therapeutic trials and clinical prognosis. Disease staging with amyloid and tau PET has face validity; however, this would be more practical with plasma biomarkers. Our objectives were, first, to examine approaches for staging amyloid and tau PET and, second, to examine prediction of amyloid and tau PET stages using plasma biomarkers. Participants (n = 1136) were enrolled in either the Mayo Clinic Study of Aging or the Alzheimer’s Disease Research Center; had a concurrent amyloid PET, tau PET and blood draw; and met clinical criteria for cognitively unimpaired (n = 864), mild cognitive impairment (n = 148) or Alzheimer’s clinical syndrome with dementia (n = 124). The latter two groups were combined into a cognitively impaired group (n = 272). We used multinomial regression models to estimate discrimination [concordance (C) statistics] among three amyloid PET stages (low, intermediate, high), four tau PET stages (Braak 0, 1–2, 3–4, 5–6) and a combined amyloid and tau PET stage (none/low versus intermediate/high severity) using plasma biomarkers as predictors separately within unimpaired and impaired individuals. Plasma analytes, p-tau181, Aβ1–42 and Aβ1–40 (analysed as the Aβ42/Aβ40 ratio), glial fibrillary acidic protein and neurofilament light chain were measured on the HD-X Simoa Quanterix platform. Plasma p-tau217 was also measured in a subset (n = 355) of cognitively unimpaired participants using the Lilly Meso Scale Discovery assay. Models with all Quanterix plasma analytes along with risk factors (age, sex and APOE) most often provided the best discrimination among amyloid PET stages (C = 0.78–0.82). Models with p-tau181 provided similar discrimination of tau PET stages to models with all four plasma analytes (C = 0.72–0.85 versus C = 0.73–0.86). Discriminating a PET proxy of intermediate/high from none/low Alzheimer’s disease neuropathological change with all four Quanterix plasma analytes was excellent but not better than p-tau181 only (C = 0.88 versus 0.87 for unimpaired and C = 0.91 versus 0.90 for impaired). Lilly p-tau217 outperformed the Quanterix p-tau181 assay for discriminating high versus intermediate amyloid (C = 0.85 versus 0.74) but did not improve over a model with all Quanterix plasma analytes and risk factors (C = 0.85 versus 0.83). Plasma analytes along with risk factors can discriminate between amyloid and tau PET stages and between a PET surrogate for intermediate/high versus none/low neuropathological change with accuracy in the acceptable to excellent range. Combinations of plasma analytes are better than single analytes for many staging predictions with the exception that Quanterix p-tau181 alone usually performed equivalently to combinations of Quanterix analytes for tau PET discrimination.

AbstractAlterations of cerebral glucose metabolism can be detected in patients with isolated rapid eye movement sleep behaviour disorder, a prodromal feature of neurodegenerative diseases with α-synuclein pathology. However, metabolic characteristics that determine clinical progression in isolated rapid eye movement sleep behaviour disorder and their association with other biomarkers need to be elucidated. We investigated the pattern of cerebral glucose metabolism on 18F-fluorodeoxyglucose PET in patients with isolated rapid eye movement sleep behaviour disorder, differentiating between those who clinically progressed and those who remained stable over time. Second, we studied the association between 18F-fluorodeoxyglucose PET and lower dopamine transporter availability in the putamen, another hallmark of synucleinopathies. Patients with isolated rapid eye movement sleep behaviour disorder from the Mayo Clinic Alzheimer’s Disease Research Center and Center for Sleep Medicine (n = 22) and age-and sex-matched clinically unimpaired controls (clinically unimpaired; n = 44) from the Mayo Clinic Study of Aging were included. All participants underwent 18F-fluorodeoxyglucose PET and dopamine transporter imaging with iodine 123-radiolabeled 2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl) nortropane on single-photon emission computerized tomography. A subset of patients with isolated rapid eye movement sleep behaviour disorder with follow-up evaluations (n = 17) was classified as isolated rapid eye movement sleep behaviour disorder progressors (n = 7) if they developed mild cognitive impairment or Parkinson’s disease; or isolated rapid eye movement sleep behaviour disorder stables (n = 10) if they remained with a diagnosis of isolated rapid eye movement sleep behaviour disorder with no cognitive impairment. Glucose metabolic abnormalities in isolated rapid eye movement sleep behaviour disorder were determined by comparing atlas-based regional 18F-fluorodeoxyglucose PET uptake between isolated rapid eye movement sleep behaviour disorder and clinically unimpaired. Associations between 18F-fluorodeoxyglucose PET and dopamine transporter availability in the putamen were analyzed with Pearson’s correlation within the nigrostriatal pathway structures and with voxel-based analysis in the cortex. Patients with isolated rapid eye movement sleep behaviour disorder had lower glucose metabolism in the substantia nigra, retrosplenial cortex, angular cortex, and thalamus, and higher metabolism in the amygdala and entorhinal cortex compared with clinically unimpaired. Patients with isolated rapid eye movement sleep behaviour disorder who clinically progressed over time were characterized by higher glucose metabolism in the amygdala and entorhinal cortex, and lower glucose metabolism in the cerebellum compared with clinically unimpaired. Lower dopamine transporter availability in the putamen was associated with higher glucose metabolism in the pallidum within the nigrostriatal pathway; and with higher 18F-fluorodeoxyglucose uptake in the amygdala, insula, and temporal pole on a voxel-based analysis, although these associations did not survive after correcting for multiple comparisons. Our findings suggest that cerebral glucose metabolism in isolated rapid eye movement sleep behaviour disorder is characterized by hypometabolism in regions frequently affected during the prodromal stage of synucleinopathies, potentially reflecting synaptic dysfunction. Hypermetabolism is also seen in isolated rapid eye movement sleep behaviour disorder, suggesting that synaptic metabolic disruptions may be leading to a lack of inhibition, compensatory mechanisms, or microglial activation, especially in regions associated with nigrostriatal degeneration.

Abstract Dysexecutive Alzheimer’s disease (dAD) manifests as a progressive dysexecutive syndrome without prominent behavioral features, and previous studies suggest clinico-radiological heterogeneity within this syndrome. We uncovered this heterogeneity using unsupervised machine learning in 52 dAD patients with multimodal imaging and cognitive data. A spectral decomposition of covariance between FDG-PET images yielded six latent factors (“eigenbrains”) accounting for 48% of variance in patterns of hypometabolism. These eigenbrains differentially related to age at onset, clinical severity, and cognitive performance. A hierarchical clustering on the eigenvalues of these eigenbrains yielded four dAD subtypes, i.e. “left-dominant,” “right-dominant,” “bi-parietal-dominant,” and “heteromodal-diffuse.” Patterns of FDG-PET hypometabolism overlapped with those of tau-PET distribution and MRI neurodegeneration for each subtype, whereas patterns of amyloid deposition were similar across subtypes. Subtypes differed in age at onset and clinical severity where the heteromodal-diffuse exhibited a worse clinical picture, and the bi-parietal had a milder clinical presentation. We propose a conceptual framework of executive components based on the clinico-radiological associations observed in dAD. We demonstrate that patients with dAD, despite sharing core clinical features, are diagnosed with variability in their clinical and neuroimaging profiles. Our findings support the use of data-driven approaches to delineate brain–behavior relationships relevant to clinical practice and disease physiology.

Abstract Objectives Sex differences permeate many aspects of dementia with Lewy bodies (DLB), including epidemiology, pathogenesis, disease progression, and symptom manifestation. However, less is known about potential sex differences in patterns of neurodegeneration in DLB. Here, we test whether grey matter networks also differ between female and male DLB patients. To assess the specificity of these sex differences to DLB, we additionally investigate sex differences in healthy controls (HCs). Methods A total of 119 (68.7 ± 8.4 years) male and 45 female (69.9 ± 9.1 years) DLB patients from three European centres and the Mayo Clinic were included in this study. Additionally, we included 119 male and 45 female age-matched HCs from the Mayo Clinic. Grey matter volumes of 58 cortical, subcortical, cerebellar, and pontine brain regions derived from structural magnetic resonance images were corrected for age, intracranial volume, and centre. Sex-specific grey matter networks for DLB patients and HCs were constructed by correlating each pair of brain regions. Network properties of the correlation matrices were compared between sexes and groups. Additional analyses were conducted on W-scored data to identify DLB-specific findings. Results Networks of male HCs and male DLB patients were characterised by a lower nodal strength compared to their respective female counterparts. In comparison to female HCs, the grey matter networks of male HCs showed a higher global efficiency, modularity, and a lower number of modules. None of the global and nodal network measures showed significant sex differences in DLB. Conclusions The disappearance of sex differences in the structural grey matter networks of DLB patients compared to HCs may indicate a sex-dependent network vulnerability to the alpha-synuclein pathology in DLB. Future studies might investigate whether the differences in structural network measures are associated with differences in cognitive scores and clinical symptoms between the sexes.

Abstract Background and objectives. Sex is an important contributing factor to neuroimaging phenotypes in brain disorders. However, little is known about the contribution of sex differences to the neurodegeneration in dementia with Lewy bodies (DLB). We investigated sex differences in probable DLB patients by using both visual rating scales of lobar atrophy and automated estimations of regional atrophy. Methods. We included 442 probable DLB patients from the European-DLB consortium and the Mayo Clinic who have magnetic resonance imaging (MRI) data available. We assessed sex differences and the sex-by-age interaction in two largely independent samples through visual rating scales of lobar atrophy (n = 333; mean age 73 ± 8 years, 62% males) and automated regional estimations of gray matter (GM) volume and mean cortical thickness (CTh) (n = 165; mean age 69 ± 9 years, 72% males). We used binary logistic regression and ANOVA for statistical analysis. Results. We found a statistically significantly higher likelihood of frontal atrophy measured by the global cortical atrophy-frontal subscale (GCA-F) in males (40% of males had an abnormal GCA-F score versus 29% of females, P-value = 0.006). Using automated estimations, we found smaller GM volumes in 6 cortical regions in males compared with females, as well as smaller GM volume in the entorhinal cortex and thinner olfactory cortices in females, compared with males. The sex-by-age interaction showed statistically significant results in 6 cortical volumes and 7 mean CTh estimations (P-value ≤ 0.05), accentuated in the right middle frontal gyrus (FDR-adjusted P-value = 0.047). These cross-sectional interactions indicated that while females have statistically significantly less atrophy than males at younger ages, differences become non-significant at older ages, with females showing the same level of atrophy than males around the age of 75. Conclusions. This study demonstrates sex differences on brain atrophy in probable DLB. While male DLB patients have a more widespread pattern of cortical atrophy at younger ages, these sex differences tend to disappear with increasing age. Longitudinal studies will help establish these cross-sectional findings and inform on sex and age considerations to the use of MRI in clinical routine, as the field moves towards precision medicine.