Differentiating Prodromal Dementia with Lewy Bodies from Prodromal Alzheimer's Disease: A Pragmatic Review for Clinicians.

This pragmatic review synthesises the current understanding of prodromal dementia with Lewy bodies (pDLB) and prodromal Alzheimer's disease (pAD), including clinical presentations, neuropsychological profiles, neuropsychiatric symptoms, biomarkers, and indications for disease management. The core clinical features of dementia with Lewy bodies (DLB)-parkinsonism, complex visual hallucinations, cognitive fluctuations, and REM sleep behaviour disorder are common prodromal symptoms. Supportive clinical features of pDLB include severe neuroleptic sensitivity, as well as autonomic and neuropsychiatric symptoms. The neuropsychological profile in mild cognitive impairment attributable to Lewy body pathology (MCI-LB) tends to include impairment in visuospatial skills and executive functioning, distinguishing it from MCI due to AD, which typically presents with impairment in memory. pDLB may present with cognitive impairment, psychiatric symptoms, and/or recurrent episodes of delirium, indicating that it is not necessarily synonymous with MCI-LB. Imaging, fluid and other biomarkers may play a crucial role in differentiating pDLB from pAD. The current MCI-LB criteria recognise low dopamine transporter uptake using positron emission tomography or single photon emission computed tomography (SPECT), loss of REM atonia on polysomnography, and sympathetic cardiac denervation using meta-iodobenzylguanidine SPECT as indicative biomarkers with slowing of dominant frequency on EEG among others as supportive biomarkers. This review also highlights the emergence of fluid and skin-based biomarkers. There is little research evidence for the treatment of pDLB, but pharmacological and non-pharmacological treatments for DLB may be discussed with patients. Non-pharmacological interventions such as diet, exercise, and cognitive stimulation may provide benefit, while evaluation and management of contributing factors like medications and sleep disturbances are vital. There is a need to expand research across diverse patient populations to address existing disparities in clinical trial participation. In conclusion, an early and accurate diagnosis of pDLB or pAD presents an opportunity for tailored interventions, improved healthcare outcomes, and enhanced quality of life for patients and care partners.

Practical use of DAT SPECT imaging in diagnosing dementia with Lewy bodies: a US perspective of current guidelines and future directions.

Background: Diagnosing Dementia with Lewy Bodies (DLB) remains a challenge in clinical practice. The use of 123I-ioflupane (DaTscan™) SPECT imaging, which detects reduced dopamine transporter (DAT) uptake-a key biomarker in DLB diagnosis-could improve diagnostic accuracy. However, DAT imaging is underutilized despite its potential, contributing to delays and suboptimal patient management. Methods: This review evaluates DLB diagnostic practices and challenges faced within the U.S. by synthesizing information from current literature, consensus guidelines, expert opinions, and recent updates on DaTscan FDA filings. It contrasts DAT SPECT with alternative biomarkers, provides recommendations for when DAT SPECT imaging may be indicated and discusses the potential of emerging biomarkers in enhancing diagnostic approaches. Results: The radiopharmaceutical 123I-ioflupane for SPECT imaging was initially approved in Europe (2000) and later in the US (2011) for Parkinsonism/Essential Tremor. Its application was extended in 2022 to include the diagnosis of DLB. DaTscan's diagnostic efficacy for DLB, with its sensitivity, specificity, and predictive values, confirms its clinical utility. However, US implementation faces challenges such as insurance barriers, costs, access issues, and regional availability disparities. Conclusion: 123I-ioflupane SPECT Imaging is indicated for DLB diagnosis and differential diagnosis of Alzheimer's Disease, particularly in uncertain cases. Addressing diagnostic obstacles and enhancing physician-patient education could improve and expedite DLB diagnosis. Collaborative efforts among neurologists, geriatric psychiatrists, psychologists, and memory clinic staff are key to increasing diagnostic accuracy and care in DLB management.

Assessment of Risk Factors and Clinical Importance of Enlarged Perivascular Spaces by Whole-Brain Investigation in the Multi-Ethnic Study of Atherosclerosis.

Importance: Enlarged perivascular spaces (ePVSs) have been associated with cerebral small-vessel disease (cSVD). Although their etiology may differ based on brain location, study of ePVSs has been limited to specific brain regions; therefore, their risk factors and significance remain uncertain. Objective: Toperform a whole-brain investigation of ePVSs in a large community-based cohort. Design, Setting, and Participants: This cross-sectional study analyzed data from the Atrial Fibrillation substudy of the population-based Multi-Ethnic Study of Atherosclerosis. Demographic, vascular risk, and cardiovascular disease data were collected from September 2016 to May 2018. Brain magnetic resonance imaging was performed from March 2018 to July 2019. The reported analysis was conducted between August and October 2022. A total of 1026 participants with available brain magnetic resonance imaging data and complete information on demographic characteristics and vascular risk factors were included. Main Outcomes and Measures: Enlarged perivascular spaces were quantified using a fully automated deep learning algorithm. Quantified ePVS volumes were grouped into 6 anatomic locations: basal ganglia, thalamus, brainstem, frontoparietal, insular, and temporal regions, and were normalized for the respective regional volumes. The association of normalized regional ePVS volumes with demographic characteristics, vascular risk factors, neuroimaging indices, and prevalent cardiovascular disease was explored using generalized linear models. Results: In the 1026 participants, mean (SD) age was 72 (8) years; 541 (53%) of the participants were women. Basal ganglia ePVS volume was positively associated with age (ß = 3.59 × 10-3; 95% CI, 2.80 × 10-3 to 4.39 × 10-3), systolic blood pressure (ß = 8.35 × 10-4; 95% CI, 5.19 × 10-4 to 1.15 × 10-3), use of antihypertensives (ß = 3.29 × 10-2; 95% CI, 1.92 × 10-2 to 4.67 × 10-2), and negatively associated with Black race (ß = -3.34 × 10-2; 95% CI, -5.08 × 10-2 to -1.59 × 10-2). Thalamic ePVS volume was positively associated with age (ß = 5.57 × 10-4; 95% CI, 2.19 × 10-4 to 8.95 × 10-4) and use of antihypertensives (ß = 1.19 × 10-2; 95% CI, 6.02 × 10-3 to 1.77 × 10-2). Insular region ePVS volume was positively associated with age (ß = 1.18 × 10-3; 95% CI, 7.98 × 10-4 to 1.55 × 10-3). Brainstem ePVS volume was smaller in Black than in White participants (ß = -5.34 × 10-3; 95% CI, -8.26 × 10-3 to -2.41 × 10-3). Frontoparietal ePVS volume was positively associated with systolic blood pressure (ß = 1.14 × 10-4; 95% CI, 3.38 × 10-5 to 1.95 × 10-4) and negatively associated with age (ß = -3.38 × 10-4; 95% CI, -5.40 × 10-4 to -1.36 × 10-4). Temporal region ePVS volume was negatively associated with age (ß = -1.61 × 10-2; 95% CI, -2.14 × 10-2 to -1.09 × 10-2), as well as Chinese American (ß = -2.35 × 10-1; 95% CI, -3.83 × 10-1 to -8.74 × 10-2) and Hispanic ethnicities (ß = -1.73 × 10-1; 95% CI, -2.96 × 10-1 to -4.99 × 10-2). Conclusions and Relevance: In this cross-sectional study of ePVSs in the whole brain, increased ePVS burden in the basal ganglia and thalamus was a surrogate marker for underlying cSVD, highlighting the clinical importance of ePVSs in these locations.

ADCoC: Adaptive Distribution Modeling Based Collaborative Clustering for Disentangling Disease Heterogeneity from Neuroimaging Data.

Conventional clustering techniques for neuroimaging applications usually focus on capturing differences between given subjects, while neglecting arising differences between features and the potential bias caused by degraded data quality. In practice, collected neuroimaging data are often inevitably contaminated by noise, which may lead to errors in clustering and clinical interpretation. Additionally, most methods ignore the importance of feature grouping towards optimal clustering. In this paper, we exploit the underlying heterogeneous clusters of features to serve as weak supervision for improved clustering of subjects, which is achieved by simultaneously clustering subjects and features via nonnegative matrix tri-factorization. In order to suppress noise, we further introduce adaptive regularization based on coefficient distribution modeling. Particularly, unlike conventional sparsity regularization techniques that assume zero mean of the coefficients, we form the distributions using the data of interest so that they could better fit the non-negative coefficients. In this manner, the proposed approach is expected to be more effective and robust against noise. We compared the proposed method with standard techniques and recently published methods demonstrating superior clustering performance on synthetic data with known ground truth labels. Furthermore, when applying our proposed technique to magnetic resonance imaging (MRI) data from a cohort of patients with Parkinson's disease, we identified two stable and highly reproducible patient clusters characterized by frontal and posterior cortical/medial temporal atrophy patterns, respectively, which also showed corresponding differences in cognitive characteristics.

Association of Intensive vs Standard Blood Pressure Control With Regional Changes in Cerebral Small Vessel Disease Biomarkers: Post Hoc Secondary Analysis of the SPRINT MIND Randomized Clinical Trial.

Importance: Little is known about the associations of strict blood pressure (BP) control with microstructural changes in small vessel disease markers. Objective: To investigate the regional associations of intensive vs standard BP control with small vessel disease biomarkers, such as white matter lesions (WMLs), fractional anisotropy (FA), mean diffusivity (MD), and cerebral blood flow (CBF). Design, Setting, and Participants: The Systolic Blood Pressure Intervention Trial (SPRINT) is a multicenter randomized clinical trial that compared intensive systolic BP (SBP) control (SBP target <120 mm Hg) vs standard control (SBP target <140 mm Hg) among participants aged 50 years or older with hypertension and without diabetes or a history of stroke. The study began randomization on November 8, 2010, and stopped July 1, 2016, with a follow-up duration of approximately 4 years. A total of 670 and 458 participants completed brain magnetic resonance imaging at baseline and follow-up, respectively, and comprise the cohort for this post hoc analysis. Statistical analyses for this post hoc analysis were performed between August 2020 and October 2022. Interventions: At baseline, 355 participants received intensive SBP treatment and 315 participants received standard SBP treatment. Main Outcomes and Measures: The main outcomes were regional changes in WMLs, FA, MD (in white matter regions of interest), and CBF (in gray matter regions of interest). Results: At baseline, 355 participants (mean [SD] age, 67.7 [8.0] years; 200 men [56.3%]) received intensive BP treatment and 315 participants (mean [SD] age, 67.0 [8.4] years; 199 men [63.2%]) received standard BP treatment. Intensive treatment was associated with smaller mean increases in WML volume compared with standard treatment (644.5 mm3 vs 1258.1 mm3). The smaller mean increases were observed specifically in the deep white matter regions of the left anterior corona radiata (intensive treatment, 30.3 mm3 [95% CI, 16.0-44.5 mm3]; standard treatment, 80.5 mm3 [95% CI, 53.8-107.2 mm3]), left tapetum (intensive treatment, 11.8 mm3 [95% CI, 4.4-19.2 mm3]; standard treatment, 27.2 mm3 [95% CI, 19.4-35.0 mm3]), left superior fronto-occipital fasciculus (intensive treatment, 3.2 mm3 [95% CI, 0.7-5.8 mm3]; standard treatment, 9.4 mm3 [95% CI, 5.5-13.4 mm3]), left posterior corona radiata (intensive treatment, 26.0 mm3 [95% CI, 12.9-39.1 mm3]; standard treatment, 52.3 mm3 [95% CI, 34.8-69.8 mm3]), left splenium of the corpus callosum (intensive treatment, 45.4 mm3 [95% CI, 25.1-65.7 mm3]; standard treatment, 83.0 mm3 [95% CI, 58.7-107.2 mm3]), left posterior thalamic radiation (intensive treatment, 53.0 mm3 [95% CI, 29.8-76.2 mm3]; standard treatment, 106.9 mm3 [95% CI, 73.4-140.3 mm3]), and right posterior thalamic radiation (intensive treatment, 49.5 mm3 [95% CI, 24.3-74.7 mm3]; standard treatment, 102.6 mm3 [95% CI, 71.0-134.2 mm3]). Conclusions and Relevance: This study suggests that intensive BP treatment, compared with standard treatment, was associated with a slower increase of WMLs, improved diffusion tensor imaging, and FA and CBF changes in several brain regions that represent vulnerable areas that may benefit from more strict BP control. Trial Registration: ClinicalTrials.gov Identifier: NCT01206062.

Double blind, nonrandomized crossover study of active recharge biphasic deep brain stimulation for primary dystonia.

BACKGROUND: Deep brain stimulation (DBS) of the globus pallidus interna (GPi) is an effective therapy for select patients with primary dystonia. DBS programming for dystonia is often challenging due to variable time to symptomatic improvement or stimulation induced side effects (SISE) such as capsular or optic tract activation which can prolong device optimization. OBJECTIVE: To characterize the safety and tolerability of active recharge biphasic DBS (bDBS) in primary dystonia and to compare it to conventional clinical DBS (clinDBS). METHODS: Ten subjects with primary dystonia and GPi DBS underwent a single center, double blind, nonrandomized crossover study comparing clinDBS versus bDBS. The testing occurred over two-days. bDBS and clinDBS were administered on separate days and each was activated for 6 h. Rating scales were collected by video recording and scored by four blinded movement disorders trained neurologists. RESULTS: The bDBS paradigm was safe and well-tolerated in all ten subjects. There were no persistent SISE reported. The mean change in the Unified Dystonia Rating Scale after 4 h of stimulation was greater in bDBS when compared to clinDBS (-6.5 vs 0.3, p < 0.04). CONCLUSION: In this pilot study, we demonstrated that biphasic DBS is a novel stimulation paradigm which can be administered safely. The biphasic waveform revealed a greater immediate improvement. Further studies are needed to determine whether this immediate improvement persists with chronic stimulation or if clinDBS will eventually achieve similar levels of improvement to bDBS over time.

Dementia with Lewy bodies: Impact of co-pathologies and implications for clinical trial design.

Dementia with Lewy bodies (DLB) is clinically defined by the presence of visual hallucinations, fluctuations, rapid eye movement (REM) sleep behavioral disorder, and parkinsonism. Neuropathologically, it is characterized by the presence of Lewy pathology. However, neuropathological studies have demonstrated the high prevalence of coexistent Alzheimer's disease, TAR DNA-binding protein 43 (TDP-43), and cerebrovascular pathologic cases. Due to their high prevalence and clinical impact on DLB individuals, clinical trials should account for these co-pathologies in their design and selection and the interpretation of biomarkers values and outcomes. Here we discuss the frequency of the different co-pathologies in DLB and their cross-sectional and longitudinal clinical impact. We then evaluate the utility and possible applications of disease-specific and disease-nonspecific biomarkers and how co-pathologies can impact these biomarkers. We propose a framework for integrating multi-modal biomarker fingerprints and step-wise selection and assessment of DLB individuals for clinical trials, monitoring target engagement, and interpreting outcomes in the setting of co-pathologies.

SPARE-Tau: A flortaucipir machine-learning derived early predictor of cognitive decline.

BACKGROUND: Recently, tau PET tracers have shown strong associations with clinical outcomes in individuals with cognitive impairment and cognitively unremarkable elderly individuals. flortaucipir PET scans to measure tau deposition in multiple brain areas as the disease progresses. This information needs to be summarized to evaluate disease severity and predict disease progression. We, therefore, sought to develop a machine learning-derived index, SPARE-Tau, which successfully detects pathology in the earliest disease stages and accurately predicts progression compared to a priori-based region of interest approaches (ROI). METHODS: 587 participants of the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort had flortaucipir scans, structural MRI scans, and an Aß biomarker test (CSF or florbetapir PET) performed on the same visit. We derived the SPARE-Tau index in a subset of 367 participants. We evaluated associations with clinical measures for CSF p-tau, SPARE-MRI, and flortaucipir PET indices (SPARE-Tau, meta-temporal, and average Braak ROIs). Bootstrapped multivariate adaptive regression splines linear regression analyzed the association between the biomarkers and baseline ADAS-Cog13 scores. Bootstrapped multivariate linear regression models evaluated associations with clinical diagnosis. Cox-hazards and mixed-effects models investigated clinical progression and longitudinal ADAS-Cog13 changes. The Aß positive cognitively unremarkable participants, not included in the SPARE-Tau training, served as an independent validation group. RESULTS: Compared to CSF p-tau, meta-temporal, and averaged Braak tau PET ROIs, SPARE-Tau showed the strongest association with baseline ADAS-cog13 scores and diagnosis. SPARE-Tau also presented the strongest association with clinical progression in cognitively unremarkable participants and longitudinal ADAS-Cog13 changes. Results were confirmed in the Aß+ cognitively unremarkable hold-out sample participants. CSF p-tau showed the weakest cross-sectional associations and longitudinal prediction. DISCUSSION: Flortaucipir indices showed the strongest clinical association among the studied biomarkers (flortaucipir, florbetapir, structural MRI, and CSF p-tau) and were predictive in the preclinical disease stages. Among the flortaucipir indices, the machine-learning derived SPARE-Tau index was the most sensitive clinical progression biomarker. The combination of different biomarker modalities better predicted cognitive performance.

Disentangling tau and brain atrophy cluster heterogeneity across the Alzheimer's disease continuum.

Introduction: Neuroimaging heterogeneity in dementia has been examined using single modalities. We evaluated the associations of magnetic resonance imaging (MRI) atrophy and flortaucipir positron emission tomography (PET) clusters across the Alzheimer's disease (AD) spectrum. Methods: We included 496 Alzheimer's Disease Neuroimaging Initiative participants with brain MRI, flortaucipir PET scan, and amyloid beta biomarker measures obtained. We applied a novel robust collaborative clustering (RCC) approach on the MRI and flortaucipir PET scans. We derived indices for AD-like (SPARE-AD index) and brain age (SPARE-BA) atrophy. Results: We identified four tau (I-IV) and three atrophy clusters. Tau clusters were associated with the apolipoprotein E genotype. Atrophy clusters were associated with white matter hyperintensity volumes. Only the hippocampal sparing atrophy cluster showed a specific association with brain aging imaging index. Tau clusters presented stronger clinical associations than atrophy clusters. Tau and atrophy clusters were partially associated. Conclusions: Each neuroimaging modality captured different aspects of brain aging, genetics, vascular changes, and neurodegeneration leading to individual multimodal phenotyping.

Clinical outcome measures in dementia with Lewy bodies trials: critique and recommendations.

The selection of appropriate outcome measures is fundamental to the design of any successful clinical trial. Although dementia with Lewy bodies (DLB) is one of the most common neurodegenerative conditions, assessment of therapeutic benefit in clinical trials often relies on tools developed for other conditions, such as Alzheimer's or Parkinson's disease. These may not be sufficiently valid or sensitive to treatment changes in DLB, decreasing their utility. In this review, we discuss the limitations and strengths of selected available tools used to measure DLB-associated outcomes in clinical trials and highlight the potential roles for more specific objective measures. We emphasize that the existing outcome measures require validation in the DLB population and that DLB-specific outcomes need to be developed. Finally, we highlight how the selection of outcome measures may vary between symptomatic and disease-modifying therapy trials.

A randomized clinical trial of burst vs. spaced physical therapy for Parkinsons disease.

INTRODUCTION: The optimal timing for physical therapy (PT) delivery in Parkinson's disease (PD) is unknown. Our objective was to determine whether spacing physical therapy visits over a longer period of time is beneficial for maintenance of physical function in PD. METHODS: A single center, single-blinded, randomized controlled trial of PD participants. Participants (n = 30) were randomized to either burst (two PT sessions weekly for 6 weeks) or spaced (one PT session every 2 weeks for 6 months) PT. 11 participants in each arm completed the study and were analyzed. The primary outcome measure was the Timed Up and Go (TUG) test at baseline and 6 months. The burst group had an additional outcome measure timepoint at the completion of PT at 6 weeks. RESULTS: Neither group achieved a minimal clinically significant benefit in the TUG score (3.5s) at 6 months. The spaced PT TUG scores were maintained when comparing baseline (7.8 ± 1.5s) and 6 month timepoints (7.8 ± 2.6s, p = 0.594). The burst group TUG scores comparing baseline (9.8 ± 3.8s) to 6 weeks (9.1 ± 3.0s) also was maintained (p = 0.365). The burst group worsened, however, when measuring the period from 6 weeks to 6 months (12.1 ± 7.6s, p = 0.034). CONCLUSIONS: The spaced PT group had stability of the TUG mobility measure at 6 months, while the burst group had a significant worsening once PT was discontinued after 6 weeks. It is feasible to test these approaches in a future larger comparative effectiveness study.

Neurofilament Light Chain Related to Longitudinal Decline in Frontotemporal Lobar Degeneration.

OBJECTIVE: Accurate diagnosis and prognosis of frontotemporal lobar degeneration (FTLD) during life is an urgent concern in the context of emerging disease-modifying treatment trials. Few CSF markers have been validated longitudinally in patients with known pathology, and we hypothesized that CSF neurofilament light chain (NfL) would be associated with longitudinal cognitive decline in patients with known FTLD-TAR DNA binding protein ~43kD (TDP) pathology. METHODS: This case-control study evaluated CSF NfL, total tau, phosphorylated tau, and ß-amyloid1-42 in patients with known FTLD-tau or FTLD-TDP pathology (n = 50) and healthy controls (n = 65) and an extended cohort of clinically diagnosed patients with likely FTLD-tau or FTLD-TDP (n = 148). Regression analyses related CSF analytes to longitudinal cognitive decline (follow-up ∼1 year), controlling for demographic variables and core AD CSF analytes. RESULTS: In FTLD-TDP with known pathology, CSF NfL is significantly elevated compared with controls and significantly associated with longitudinal decline on specific executive and language measures, after controlling for age, disease duration, and core AD CSF analytes. Similar findings are found in the extended cohort, also including clinically identified likely FTLD-TDP. Although CSF NfL is elevated in FTLD-tau compared with controls, the association between NfL and longitudinal cognitive decline is limited to executive measures. CONCLUSION: CSF NfL is associated with longitudinal clinical decline in relevant cognitive domains in patients with FTLD-TDP after controlling for demographic factors and core AD CSF analytes and may also be related to longitudinal decline in executive functioning in FTLD-tau.

Neuropathological consensus criteria for the evaluation of Lewy pathology in post-mortem brains: a multi-centre study.

Currently, the neuropathological diagnosis of Lewy body disease (LBD) may be stated according to several staging systems, which include the Braak Lewy body stages (Braak), the consensus criteria by McKeith and colleagues (McKeith), the modified McKeith system by Leverenz and colleagues (Leverenz), and the Unified Staging System by Beach and colleagues (Beach). All of these systems use semi-quantitative scoring (4- or 5-tier scales) of Lewy pathology (LP; i.e., Lewy bodies and Lewy neurites) in defined cortical and subcortical areas. While these systems are widely used, some suffer from low inter-rater reliability and/or an inability to unequivocally classify all cases with LP. To address these limitations, we devised a new system, the LP consensus criteria (LPC), which is based on the McKeith system, but applies a dichotomous approach for the scoring of LP (i.e., "absent" vs. "present") and includes amygdala-predominant and olfactory-only stages. α-Synuclein-stained slides from brainstem, limbic system, neocortex, and olfactory bulb from a total of 34 cases with LP provided by the Newcastle Brain Tissue Resource (NBTR) and the University of Pennsylvania brain bank (UPBB) were scanned and assessed by 16 raters, who provided diagnostic categories for each case according to Braak, McKeith, Leverenz, Beach, and LPC systems. In addition, using LP scores available from neuropathological reports of LP cases from UPBB (n = 202) and NBTR (n = 134), JT (UPBB) and JA (NBTR) assigned categories according to all staging systems to these cases. McKeith, Leverenz, and LPC systems reached good (Krippendorff's α ≈ 0.6), while both Braak and Beach systems had lower (Krippendorff's α ≈ 0.4) inter-rater reliability, respectively. Using the LPC system, all cases could be unequivocally classified by the majority of raters, which was also seen for 97.1% when the Beach system was used. However, a considerable proportion of cases could not be classified when using Leverenz (11.8%), McKeith (26.5%), or Braak (29.4%) systems. The category of neocortical LP according to the LPC system was associated with a 5.9 OR (p < 0.0001) of dementia in the 134 NBTR cases and a 3.14 OR (p = 0.0001) in the 202 UPBB cases. We established that the LPC system has good reproducibility and allows classification of all cases into distinct categories. We expect that it will be reliable and useful in routine diagnostic practice and, therefore, suggest that it should be the standard future approach for the basic post-mortem evaluation of LP.

The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans.

INTRODUCTION: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging database (11 studies; 10,216 subjects). METHODS: Three brain signatures were calculated: Brain-age, AD-like neurodegeneration, and white matter hyperintensities (WMHs). Brain Charts measured and displayed the relationships of these signatures to cognition and molecular biomarkers of AD. RESULTS: WMHs were associated with advanced brain aging, AD-like atrophy, poorer cognition, and AD neuropathology in mild cognitive impairment (MCI)/AD and cognitively normal (CN) subjects. High WMH volume was associated with brain aging and cognitive decline occurring in an ≈10-year period in CN subjects. WMHs were associated with doubling the likelihood of amyloid beta (Aß) positivity after age 65. Brain aging, AD-like atrophy, and WMHs were better predictors of cognition than chronological age in MCI/AD. DISCUSSION: A Brain Chart quantifying brain-aging trajectories was established, enabling the systematic evaluation of individuals' brain-aging patterns relative to this large consortium.

Sex and APOE ε4 genotype modify the Alzheimer's disease serum metabolome.

Late-onset Alzheimer's disease (AD) can, in part, be considered a metabolic disease. Besides age, female sex and APOE ε4 genotype represent strong risk factors for AD that also give rise to large metabolic differences. We systematically investigated group-specific metabolic alterations by conducting stratified association analyses of 139 serum metabolites in 1,517 individuals from the AD Neuroimaging Initiative with AD biomarkers. We observed substantial sex differences in effects of 15 metabolites with partially overlapping differences for APOE ε4 status groups. Several group-specific metabolic alterations were not observed in unstratified analyses using sex and APOE ε4 as covariates. Combined stratification revealed further subgroup-specific metabolic effects limited to APOE ε4+ females. The observed metabolic alterations suggest that females experience greater impairment of mitochondrial energy production than males. Dissecting metabolic heterogeneity in AD pathogenesis can therefore enable grading the biomedical relevance for specific pathways within specific subgroups, guiding the way to personalized medicine.

Inflammatory markers and imaging patterns of advanced brain aging in the general population.

Inflammaging describes the complexity between low-grade chronic inflammation with the pathogenesis of brain aging and Alzheimer´s disease (AD). We aimed to find associations of inflammatory markers: i) white blood cell count (WBC), ii) high-sensitivity C-reactive protein (hs-CRP), and iii) fibrinogen with brain structures, sensitive neuroimaging markers of advanced brain aging and AD-like atrophy, and cognitive aging scores. We analyzed magnetic resonance imaging (MRI) scans of 2204 participants from the Study of Health in Pomerania-2 (SHIP-2) and SHIP-Trend (55.6% women, mean age 52.4±13.7 years). Associations of the inflammatory markers with specific brain signatures of brain aging (SPARE-BA), AD-like brain atrophy (SPARE-AD) and white matter disease (white matter hyperintensities volume (WMHV)) were investigated. Furthermore we explored their association with general brain structures including total brain volume (TBV), gray matter volume (GMV), and white matter volume (WMV), as well as cognitive scores (Nurnberger Age Inventory (NAI); Verbal Learning and Memory Test (VLMT). We adjusted for multiple vascular risk factors (VRF; e.g. smoking and blood pressure) and corresponding medication use to take their brain aging effects into account and corrected for false-discovery rate (FDR). Results:WBC was inversely associated with SPARE-BA (FDR-adjusted p=0.003), TBV (FDR-adjusted p=0.019) and GMV (FDR-adjusted p= 0.017). GMV was also inversely associated with hs-CRP (FDR-adjusted p=0.039) and fibrinogen (FDR-adjusted p=0.039). None of the inflammatory markers was associated with WMHV. Regression analysis also revealed a trend-level interaction between intake of antiinflammatory medication and hs-CRP with brain aging (SPARE-BA; FDR-adjusted p=0.062). Inflammatatory markers are associated with neuroimaging markers, with elevated WBC leading to significant acceleration in brain aging patterns but not with AD-like imaging structural changes. Given the overlap between accelerated brain aging and AD-like atrophy, increased WBC might be associated with global dementia symptoms due to this overlap in atrophy patterns. Elevated WBC may be not causal to preclinical AD dementia, but an accessory symptom of inflammaging. At population level, our results support the relevant roles of inflammatory markers on brain aging related atrophy.

Predicting clinical decline and conversion to Alzheimer's disease or dementia using novel Elecsys Aß(1-42), pTau and tTau CSF immunoassays.

We evaluated the performance of CSF biomarkers for predicting risk of clinical decline and conversion to dementia in non-demented patients with cognitive symptoms. CSF samples from patients in two multicentre longitudinal studies (ADNI, n = 619; BioFINDER, n = 431) were analysed. Aß(1-42), tTau and pTau CSF concentrations were measured using Elecsys CSF immunoassays, and tTau/Aß(1-42) and pTau/Aß(1-42) ratios calculated. Patients were classified as biomarker (BM)-positive or BM-negative at baseline. Ability of biomarkers to predict risk of clinical decline and conversion to AD/dementia was assessed using pre-established cut-offs for Aß(1-42) and ratios; tTau and pTau cut-offs were determined. BM-positive patients showed greater clinical decline than BM-negative patients, demonstrated by greater decreases in MMSE scores (all biomarkers: -2.10 to -0.70). Risk of conversion to AD/dementia was higher in BM-positive patients (HR: 1.67 to 11.48). Performance of Tau/Aß(1-42) ratios was superior to single biomarkers, and consistent even when using cut-offs derived in a different cohort. Optimal pTau and tTau cut-offs were approximately 27 pg/mL and 300 pg/mL in both BioFINDER and ADNI. Elecsys pTau/Aß(1-42) and tTau/Aß(1-42) are robust biomarkers for predicting risk of clinical decline and conversion to dementia in non-demented patients, and may support AD diagnosis in clinical practice.

APOE Effect on Amyloid-ß PET Spatial Distribution, Deposition Rate, and Cut-Points.

There are conflicting results regarding how APOE genotype, the strongest genetic risk factor for Alzheimer's disease (AD), influences spatial and longitudinal amyloid-ß (Aß) deposition and its impact on the selection of biomarker cut-points. In our study, we sought to determine the impact of APOE genotype on cross-sectional and longitudinal florbetapir positron emission tomography (PET) amyloid measures and its impact in classification of patients and interpretation of clinical cohort results. We included 1,019 and 1,072 Alzheimer's Disease Neuroimaging Initiative participants with cerebrospinal fluid Aß1 - 42 and florbetapir PET values, respectively. 623 of these subjects had a second florbetapir PET scans two years after the baseline visit. We evaluated the effect of APOE genotype on Aß distribution pattern, pathological biomarker cut-points, cross-sectional clinical associations with Aß load, and longitudinal Aß deposition rate measured using florbetapir PET scans. 1) APOEɛ4 genotype influences brain amyloid deposition pattern; 2) APOEɛ4 genotype does not modify Aß biomarker cut-points estimated using unsupervised mixture modeling methods if white matter and brainstem references are used (but not when cerebellum is used as a reference); 3) findings of large differences in Aß biomarker value differences based on APOE genotype are due to increased probability of having AD neuropathology and are most significant in mild cognitive impairment subjects; and 4) APOE genotype and age (but not gender) were associated with increased Aß deposition rate. APOEɛ4 carrier status affects rate and location of brain Aß deposition but does not affect choice of biomarker cut-points if adequate references are selected for florbetapir PET processing.