Morris, John C.

AbstractBackgroundSolanezumab is a monoclonal antibody targeting soluble forms of β‐amyloid protein important in the pathogenesis of Alzheimer’s disease (AD). Three previous 18‐month double‐blind placebo‐controlled trials of low‐dose solanezumab in late‐onset sporadic AD found inconsistent benefits on cognitive and functional assessments. Dominantly‐inherited mutation‐associated AD subjects both before and after onset of symptoms form an ideal population to study potential benefits of solanezumab therapy.MethodMutation‐carrying asymptomatic (CDR 0, N=41) or mildly symptomatic (CDR 0.5 – 1, N=28) patients were treated for a minimum of 4 years and up to 7 years in a double‐blind 3 to 1 active versus placebo randomized clinical trial that measured disease progression by clinical, neuropsychological and biomarker evaluations. The trial was initiated with a dose of 400 mg every 4 weeks and escalated to 1600 mg when low dose trials in sporadic AD did not meet their primary endpoints. The primary cognitive outcome measure was DIAN‐MCE, composed of Delayed Recall Score of the International Shopping List Test, the Delayed Recall score of the Logical Memory IIa subtest from the Wechsler Memory Scale‐Revised, the Digit Symbol Substitution Test total score from the WAIS‐R and the MMSE total score. Secondary outcomes included a battery of other cognitive and functional measures. The study was powered to detect delay of cognitive disease progression in the DIAN‐MCE. Biomarkers include imaging modalities (volumetric MRI, FDG, amyloid and Tau PET). CSF markers included β‐amyloid, Tau and PhosphoTau species. NfL was measured in both CSF and plasma. The study used a pre‐specified Bayesian multivariate disease progression model, which included dynamic borrowing of control subjects from the DIAN Observational study.ResultThe topline efficacy, safety and biomarker results will be reported.ConclusionThis study provides the first test of targeting soluble abeta forms in DIAD. It addresses the efficacy of early initiation of higher doses of solanezumab targeting soluble forms of amyloid as a disease modifying therapy. While these results are specific to DIAD, they have the potential to inform the application of anti‐amyloid therapy in sporadic AD.

Abstract Structural grey matter covariance networks provide an individual quantification of morphological patterns in the brain. The network integrity is disrupted in sporadic Alzheimer’s disease, and network properties show associations with the level of amyloid pathology and cognitive decline. Therefore, these network properties might be disease progression markers. However, it remains unclear when and how grey matter network integrity changes with disease progression. We investigated these questions in autosomal dominant Alzheimer’s disease mutation carriers, whose conserved age at dementia onset allows individual staging based upon their estimated years to symptom onset. From the Dominantly Inherited Alzheimer Network observational cohort, we selected T1-weighted MRI scans from 269 mutation carriers and 170 non-carriers (mean age 38 ± 15 years, mean estimated years to symptom onset −9 ± 11), of whom 237 had longitudinal scans with a mean follow-up of 3.0 years. Single-subject grey matter networks were extracted, and we calculated for each individual the network properties which describe the network topology, including the size, clustering, path length and small worldness. We determined at which time point mutation carriers and non-carriers diverged for global and regional grey matter network metrics, both cross-sectionally and for rate of change over time. Based on cross-sectional data, the earliest difference was observed in normalized path length, which was decreased for mutation carriers in the precuneus area at 13 years and on a global level 12 years before estimated symptom onset. Based on longitudinal data, we found the earliest difference between groups on a global level 6 years before symptom onset, with a greater rate of decline of network size for mutation carriers. We further compared grey matter network small worldness with established biomarkers for Alzheimer disease (i.e. amyloid accumulation, cortical thickness, brain metabolism and cognitive function). We found that greater amyloid accumulation at baseline was associated with faster decline of small worldness over time, and decline in grey matter network measures over time was accompanied by decline in brain metabolism, cortical thinning and cognitive decline. In summary, network measures decline in autosomal dominant Alzheimer’s disease, which is alike sporadic Alzheimer’s disease, and the properties show decline over time prior to estimated symptom onset. These data suggest that single-subject networks properties obtained from structural MRI scans form an additional non-invasive tool for understanding the substrate of cognitive decline and measuring progression from preclinical to severe clinical stages of Alzheimer’s disease.

AbstractIntroductionAlthough some members of families with autosomal dominant Alzheimer's disease mutations learn their mutation status, most do not. How knowledge of mutation status affects clinical disease progression is unknown. This study quantifies the influence of mutation awareness on clinical symptoms, cognition, and biomarkers.MethodsMutation carriers and non‐carriers from the Dominantly Inherited Alzheimer Network (DIAN) were stratified based on knowledge of mutation status. Rates of change on standard clinical, cognitive, and neuroimaging outcomes were examined.ResultsMutation knowledge had no associations with cognitive decline, clinical progression, amyloid deposition, hippocampal volume, or depression in either carriers or non‐carriers. Carriers who learned their status mid‐study had slightly higher levels of depression and lower cognitive scores.DiscussionKnowledge of mutation status does not affect rates of change on any measured outcome. Learning of status mid‐study may confer short‐term changes in cognitive functioning, or changes in cognition may influence the determination of mutation status.

Background: Levothyroxine (LT4) is the mainstay of therapy for hypothyroidism. Yet, despite physician efforts at dose titration, some patients remain hypothyroid on LT4 doses in excess of weight-based calculations, a condition known as refractory hypothyroidism. The LT4 absorption test (LT4AT) has been proposed to have utility in these patients by enabling distinction of LT4 malabsorption from pseudomalabsorption, a condition of intentional nonadherence. Given its rare use in clinical practice, we reviewed our institution's experience with the LT4AT to assess its impact on management of refractory hypothyroidism. Methods: We reviewed the charts of 16 patients diagnosed with refractory hypothyroidism and who had completed the LT4AT between January 2015 to January 2019. The primary aim was to determine the utility of this test in distinguishing LT4 malabsorption from pseudomalabsorption. Secondary aims were to determine whether the results of this test impacted physicians' management decisions, as well as to report on clinical outcomes at follow-up. Our LT4AT is a six-hour test wherein patients receive a weight-based dose of LT4 followed by serial measurements of total thyroxine (TT4) and thyrotropin (TSH). Percentage absorption is calculated using the following formula, with normal absorption being ≥60%: Results: Percentage absorption was calculated in 13 of 16 patients due to lack of TT4 data for 3 patients. Absorption was impaired in one patient (% absorbed = 0), who had known causes of malabsorption. The remaining 12 patients had normal absorption by hour 4 of the test (% absorption 60–158) in conjunction with upward TT4 trends. Clinical follow-up ranged from 1 to 32 months (median 6.5 months), with 11 patients having follow-up data. Six of these had normal or suppressed TSH values at most recent follow-up, and four had improved but persistent TSH elevations. The one said patient with malabsorption improved with intravenous LT4. Conclusions: The LT4AT can provide valuable information for distinguishing malabsorption from pseudomalabsorption. Our findings support the combined use of calculated percentage absorptions with TT4 trends for at least a four-hour time frame when making determinations regarding absorption.