Promoting Growth in Behavioral Neurology: A Path Forward.

Behavioral neurology & neuropsychiatry (BNNP) is a field that seeks to understand brain-behavior relationships, including fundamental brain organization principles and the many ways that brain structures and connectivity can be disrupted, leading to abnormalities of behavior, cognition, emotion, perception, and social cognition. In North America, BNNP has existed as an integrated subspecialty through the United Council for Neurologic Subspecialties since 2006. Nonetheless, the number of behavioral neurologists across academic medical centers and community settings is not keeping pace with increasing clinical and research demand. In this commentary, we provide a brief history of BNNP followed by an outline of the current challenges and opportunities for BNNP from the behavioral neurologist's perspective across clinical, research, and educational spheres. We provide a practical guide for promoting BNNP and addressing the shortage of behavioral neurologists to facilitate the continued growth and development of the subspecialty. We also urge a greater commitment to recruit trainees from diverse backgrounds so as to dismantle persistent obstacles that hinder inclusivity in BNNP-efforts that will further enhance the growth and impact of the subspecialty. With rapidly expanding diagnostic and therapeutic approaches across a range of conditions at the intersection of neurology and psychiatry, BNNP is well positioned to attract new trainees and expand its reach across clinical, research, and educational activities.

Effects of risk factors on the development and mortality of early- and late-onset dementia: an 11-year longitudinal nationwide population-based cohort study in South Korea.

BACKGROUND: Early-onset dementia (EOD, onset age < 65) and late-onset dementia (LOD, onset age ≥ 65) exhibit distinct features. Understanding the risk factors for dementia development and mortality in EOD and LOD respectively is crucial for personalized care. While risk factors are known for LOD development and mortality, their impact on EOD remains unclear. We aimed to investigate how hypertension, diabetes mellitus, hyperlipidemia, atrial fibrillation, and osteoporosis influence the development and mortality of EOD and LOD, respectively. METHODS: Using the Korean National Health Insurance Service (NHIS) database, we collected 546,709 dementia-free individuals and followed up for 11 years. In the two study groups, the Younger group (< 65 years old) and the Older group (≥ 65 years old), we applied Cox proportional hazard models to assess risk factors for development of EOD and LOD, respectively. Then, we assessed risk factors for mortality among EOD and LOD. RESULTS: Diabetes mellitus and osteoporosis increased the risk of EOD and LOD development. Hypertension increased the risk of EOD, while atrial fibrillation increased the risk of LOD. Conversely, hyperlipidemia exhibited a protective effect against LOD development. Additionally, diabetes mellitus increased mortality in EOD and LOD. Hypertension and atrial fibrillation increased mortality in LOD, while hyperlipidemia decreased mortality in EOD and LOD. CONCLUSIONS: Risk factors influencing dementia development and mortality differed in EOD and LOD. Targeted public health interventions addressing age-related risk factors may reduce dementia incidence and mortality.

Biomarker-based staging of Alzheimer disease: rationale and clinical applications.

Disease staging, whereby the spatial extent and load of brain pathology are used to estimate the severity of Alzheimer disease (AD), is pivotal to the gold-standard neuropathological diagnosis of AD. Current in vivo diagnostic frameworks for AD are based on abnormal concentrations of amyloid-ß and tau in the cerebrospinal fluid or on PET scans, and breakthroughs in molecular imaging have opened up the possibility of in vivo staging of AD. Focusing on the key principles of disease staging shared across several areas of medicine, this Review highlights the potential for in vivo staging of AD to transform our understanding of preclinical AD, refine enrolment criteria for trials of disease-modifying therapies and aid clinical decision-making in the era of anti-amyloid therapeutics. We provide a state-of-the-art review of recent biomarker-based AD staging systems and highlight their contributions to the understanding of the natural history of AD. Furthermore, we outline hypothetical frameworks to stage AD severity using more accessible fluid biomarkers. In addition, by applying amyloid PET-based staging to recently published anti-amyloid therapeutic trials, we highlight how biomarker-based disease staging frameworks could illustrate the numerous pathological changes that have already taken place in individuals with mildly symptomatic AD. Finally, we discuss challenges related to the validation and standardization of disease staging and provide a forward-looking perspective on potential clinical applications.

Demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy: an international cohort study and individual participant data meta-analysis.

BACKGROUND: Posterior cortical atrophy is a rare syndrome characterised by early, prominent, and progressive impairment in visuoperceptual and visuospatial processing. The disorder has been associated with underlying neuropathological features of Alzheimer's disease, but large-scale biomarker and neuropathological studies are scarce. We aimed to describe demographic, clinical, biomarker, and neuropathological correlates of posterior cortical atrophy in a large international cohort. METHODS: We searched PubMed between database inception and Aug 1, 2021, for all published research studies on posterior cortical atrophy and related terms. We identified research centres from these studies and requested deidentified, individual participant data (published and unpublished) that had been obtained at the first diagnostic visit from the corresponding authors of the studies or heads of the research centres. Inclusion criteria were a clinical diagnosis of posterior cortical atrophy as defined by the local centre and availability of Alzheimer's disease biomarkers (PET or CSF), or a diagnosis made at autopsy. Not all individuals with posterior cortical atrophy fulfilled consensus criteria, being diagnosed using centre-specific procedures or before development of consensus criteria. We obtained demographic, clinical, biofluid, neuroimaging, and neuropathological data. Mean values for continuous variables were combined using the inverse variance meta-analysis method; only research centres with more than one participant for a variable were included. Pooled proportions were calculated for binary variables using a restricted maximum likelihood model. Heterogeneity was quantified using I2. FINDINGS: We identified 55 research centres from 1353 papers, with 29 centres responding to our request. An additional seven centres were recruited by advertising via the Alzheimer's Association. We obtained data for 1092 individuals who were evaluated at 36 research centres in 16 countries, the other sites having not responded to our initial invitation to participate to the study. Mean age at symptom onset was 59·4 years (95% CI 58·9-59·8; I2=77%), 60% (56-64; I2=35%) were women, and 80% (72-89; I2=98%) presented with posterior cortical atrophy pure syndrome. Amyloid ß in CSF (536 participants from 28 centres) was positive in 81% (95% CI 75-87; I2=78%), whereas phosphorylated tau in CSF (503 participants from 29 centres) was positive in 65% (56-75; I2=87%). Amyloid-PET (299 participants from 24 centres) was positive in 94% (95% CI 90-97; I2=15%), whereas tau-PET (170 participants from 13 centres) was positive in 97% (93-100; I2=12%). At autopsy (145 participants from 13 centres), the most frequent neuropathological diagnosis was Alzheimer's disease (94%, 95% CI 90-97; I2=0%), with common co-pathologies of cerebral amyloid angiopathy (71%, 54-88; I2=89%), Lewy body disease (44%, 25-62; I2=77%), and cerebrovascular injury (42%, 24-60; I2=88%). INTERPRETATION: These data indicate that posterior cortical atrophy typically presents as a pure, young-onset dementia syndrome that is highly specific for underlying Alzheimer's disease pathology. Further work is needed to understand what drives cognitive vulnerability and progression rates by investigating the contribution of sex, genetics, premorbid cognitive strengths and weaknesses, and brain network integrity. FUNDING: None.

Spatial transcriptomic patterns underlying amyloid-ß and tau pathology are associated with cognitive dysfunction in Alzheimer's disease.

Amyloid-ß (Aß) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aß and tau pathologies than others, gene expression may play a role. We study the association between brain-wide gene expression profiles and regional vulnerability to Aß (gene-to-Aß associations) and tau (gene-to-tau associations) pathologies by leveraging two large independent AD cohorts. We identify AD susceptibility genes and gene modules in a gene co-expression network with expression profiles specifically related to regional vulnerability to Aß and tau pathologies in AD. In addition, we identify distinct biochemical pathways associated with the gene-to-Aß and the gene-to-tau associations. These findings may explain the discordance between regional Aß and tau pathologies. Finally, we propose an analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations.

TAF15 amyloid filaments in frontotemporal lobar degeneration.

Frontotemporal lobar degeneration (FTLD) causes frontotemporal dementia (FTD), the most common form of dementia after Alzheimer's disease, and is often also associated with motor disorders1. The pathological hallmarks of FTLD are neuronal inclusions of specific, abnormally assembled proteins2. In the majority of cases the inclusions contain amyloid filament assemblies of TAR DNA-binding protein 43 (TDP-43) or tau, with distinct filament structures characterizing different FTLD subtypes3,4. The presence of amyloid filaments and their identities and structures in the remaining approximately 10% of FTLD cases are unknown but are widely believed to be composed of the protein fused in sarcoma (FUS, also known as translocated in liposarcoma). As such, these cases are commonly referred to as FTLD-FUS. Here we used cryogenic electron microscopy (cryo-EM) to determine the structures of amyloid filaments extracted from the prefrontal and temporal cortices of four individuals with FTLD-FUS. Surprisingly, we found abundant amyloid filaments of the FUS homologue TATA-binding protein-associated factor 15 (TAF15, also known as TATA-binding protein-associated factor 2N) rather than of FUS itself. The filament fold is formed from residues 7-99 in the low-complexity domain (LCD) of TAF15 and was identical between individuals. Furthermore, we found TAF15 filaments with the same fold in the motor cortex and brainstem of two of the individuals, both showing upper and lower motor neuron pathology. The formation of TAF15 amyloid filaments with a characteristic fold in FTLD establishes TAF15 proteinopathy in neurodegenerative disease. The structure of TAF15 amyloid filaments provides a basis for the development of model systems of neurodegenerative disease, as well as for the design of diagnostic and therapeutic tools targeting TAF15 proteinopathy.

Edge time series components of functional connectivity and cognitive function in Alzheimer's disease.

Understanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer's disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer's Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer's disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.

Associations Between Social Network Characteristics and Brain Structure Among Older Adults.

INTRODUCTION: Social connectedness is associated with slower cognitive decline among older adults. Recent research suggests that distinct aspects of social networks may have differential effects on cognitive resilience, but few studies analyze brain structure. METHODS: This study includes 117 cognitively impaired and 59 unimpaired older adults. The effects of social network characteristics (bridging/bonding) on brain regions of interests were analyzed using linear regressions and voxel-wise multiple linear regressions of gray matter density. RESULTS: Increased social bridging was associated with greater bilateral amygdala volume and insular thickness, and left frontal lobe thickness, putamen, and thalamic volumes. Increased social bonding was associated with greater bilateral medial orbitofrontal and caudal anterior cingulate thickness, as well as right frontal lobe thickness, putamen, and amygdala volumes. DISCUSSION: The associations between social connectedness and brain structure vary depending on the types of social enrichment accessible through social networks, suggesting that psychosocial interventions could mitigate neurodegeneration. HIGHLIGHTS: Distinct forms of social capital are uniquely linked to gray matter density (GMD). Bridging is associated with preserved GMD in limbic system structures. Bonding is associated with preserved GMD in frontal lobe regions. Bridging is associated with increased brain reserve in sensory processing regions. Bonding is associated with increased brain reserve in regions of stress modulation.

BrainAGE Estimation: Influence of Field Strength, Voxel Size, Race, and Ethnicity.

The BrainAGE method is used to estimate biological brain age using structural neuroimaging. However, the stability of the model across different scan parameters and races/ethnicities has not been thoroughly investigated. Estimated brain age was compared within- and across- MRI field strength and across voxel sizes. Estimated brain age gap (BAG) was compared across demographically matched groups of different self-reported races and ethnicities in ADNI and IMAS cohorts. Longitudinal ComBat was used to correct for potential scanner effects. The brain age method was stable within field strength, but less stable across different field strengths. The method was stable across voxel sizes. There was a significant difference in BAG between races, but not ethnicities. Correction procedures are suggested to eliminate variation across scanner field strength while maintaining accurate brain age estimation. Further studies are warranted to determine the factors contributing to racial differences in BAG.

Edge Time Series Components of Functional Connectivity and Cognitive Function in Alzheimer's Disease.

Understanding the interrelationships of brain function as measured by resting-state magnetic resonance imaging and neuropsychological/behavioral measures in Alzheimer's disease is key for advancement of neuroimaging analysis methods in clinical research. The edge time-series framework recently developed in the field of network neuroscience, in combination with other network science methods, allows for investigations of brain-behavior relationships that are not possible with conventional functional connectivity methods. Data from the Indiana Alzheimer's Disease Research Center sample (53 cognitively normal control, 47 subjective cognitive decline, 32 mild cognitive impairment, and 20 Alzheimer's disease participants) were used to investigate relationships between functional connectivity components, each derived from a subset of time points based on co-fluctuation of regional signals, and measures of domain-specific neuropsychological functions. Multiple relationships were identified with the component approach that were not found with conventional functional connectivity. These involved attentional, limbic, frontoparietal, and default mode systems and their interactions, which were shown to couple with cognitive, executive, language, and attention neuropsychological domains. Additionally, overlapping results were obtained with two different statistical strategies (network contingency correlation analysis and network-based statistics correlation). Results demonstrate that connectivity components derived from edge time-series based on co-fluctuation reveal disease-relevant relationships not observed with conventional static functional connectivity.

Pathogenic variants in the Longitudinal Early-onset Alzheimer's Disease Study cohort.

INTRODUCTION: One goal of the Longitudinal Early-onset Alzheimer's Disease Study (LEADS) is to investigate the genetic etiology of early onset (40-64 years) cognitive impairment. Toward this goal, LEADS participants are screened for known pathogenic variants. METHODS: LEADS amyloid-positive early-onset Alzheimer's disease (EOAD) or negative early-onset non-AD (EOnonAD) cases were whole exome sequenced (N = 299). Pathogenic variant frequency in APP, PSEN1, PSEN2, GRN, MAPT, and C9ORF72 was assessed for EOAD and EOnonAD. Gene burden testing was performed in cases compared to similar-age cognitively normal controls in the Parkinson's Progression Markers Initiative (PPMI) study. RESULTS: Previously reported pathogenic variants in the six genes were identified in 1.35% of EOAD (3/223) and 6.58% of EOnonAD (5/76). No genes showed enrichment for carriers of rare functional variants in LEADS cases. DISCUSSION: Results suggest that LEADS is enriched for novel genetic causative variants, as previously reported variants are not observed in most cases. HIGHLIGHTS: Sequencing identified eight cognitively impaired pathogenic variant carriers. Pathogenic variants were identified in PSEN1, GRN, MAPT, and C9ORF72. Rare variants were not enriched in APP, PSEN1/2, GRN, and MAPT. The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) is a key resource for early-onset Alzheimer's genetic research.

The Sporadic Early-onset Alzheimer's Disease Signature Of Atrophy: Preliminary Findings From The Longitudinal Early-onset Alzheimer's Disease Study (LEADS) Cohort.

INTRODUCTION: Magnetic resonance imaging (MRI) research has advanced our understanding of neurodegeneration in sporadic early-onset Alzheimer's disease (EOAD) but studies include small samples, mostly amnestic EOAD, and have not focused on developing an MRI biomarker. METHODS: We analyzed MRI scans to define the sporadic EOAD-signature atrophy in a small sample (n = 25) of Massachusetts General Hospital (MGH) EOAD patients, investigated its reproducibility in the large longitudinal early-onset Alzheimer's disease study (LEADS) sample (n = 211), and investigated the relationship of the magnitude of atrophy with cognitive impairment. RESULTS: The EOAD-signature atrophy was replicated across the two cohorts, with prominent atrophy in the caudal lateral temporal cortex, inferior parietal lobule, and posterior cingulate and precuneus cortices, and with relative sparing of the medial temporal lobe. The magnitude of EOAD-signature atrophy was associated with the severity of cognitive impairment. DISCUSSION: The EOAD-signature atrophy is a reliable and clinically valid biomarker of AD-related neurodegeneration that could be used in clinical trials for EOAD. HIGHLIGHTS: We developed an early-onset Alzheimer's disease (EOAD)-signature of atrophy based on magnetic resonance imaging (MRI) scans. EOAD signature was robustly reproducible across two independent patient cohorts. EOAD signature included prominent atrophy in parietal and posterior temporal cortex. The EOAD-signature atrophy was associated with the severity of cognitive impairment. EOAD signature is a reliable and clinically valid biomarker of neurodegeneration.

Influence of amyloid and diagnostic syndrome on non-traditional memory scores in early-onset Alzheimer's disease.

INTRODUCTION: The Rey Auditory Verbal Learning Test (RAVLT) is a useful neuropsychological test for describing episodic memory impairment in dementia. However, there is limited research on its utility in early-onset Alzheimer's disease (EOAD). We assess the influence of amyloid and diagnostic syndrome on several memory scores in EOAD. METHODS: We transcribed RAVLT recordings from 303 subjects in the Longitudinal Early-Onset Alzheimer's Disease Study. Subjects were grouped by amyloid status and syndrome. Primacy, recency, J-curve, duration, stopping time, and speed score were calculated and entered into linear mixed effects models as dependent variables. RESULTS: Compared with amyloid negative subjects, positive subjects exhibited effects on raw score, primacy, recency, and stopping time. Inter-syndromic differences were noted with raw score, primacy, recency, J-curve, and stopping time. DISCUSSION: RAVLT measures are sensitive to the effects of amyloid and syndrome in EOAD. Future work is needed to quantify the predictive value of these scores. HIGHLIGHTS: RAVLT patterns characterize various presentations of EOAD and EOnonAD Amyloid impacts raw score, primacy, recency, and stopping time Timing-based scores add value over traditional count-based scores.

The relationship between learning slopes and Alzheimer's Disease biomarkers in cognitively unimpaired participants with and without subjective memory concerns.

OBJECTIVE: Learning slopes represent serial acquisition of information during list-learning tasks. Although several calculations for learning slopes exist, the Learning Ratio (LR) has recently demonstrated the highest sensitivity toward changes in cognition and Alzheimer's disease (AD) biomarkers. However, investigation of learning slopes in cognitively unimpaired individuals with subjective memory concerns (SMC) has been limited. The current study examines the association of learning slopes to SMC, and the role of SMC in the relationship between learning slopes and AD biomarkers in cognitively unimpaired individuals. METHOD: Data from 950 cognitively unimpaired participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 89) were used to calculate learning slope metrics. Learning slopes among those with and without SMC were compared with demographic correction, and the relationships of learning slopes with AD biomarkers of bilateral hippocampal volume and ß-amyloid pathology were determined. RESULTS: Learning slopes were consistently predictive of hippocampal atrophy and ß-amyloid deposition. Results were heightened for LR relative to the other learning slopes. Additionally, interaction analyses revealed different associations between learning slopes and hippocampal volume as a function of SMC status. CONCLUSIONS: Learning slopes appear to be sensitive to SMC and AD biomarkers, with SMC status influencing the relationship in cognitively unimpaired participants. These findings advance our knowledge of SMC, and suggest that LR - in particular - can be an important tool for the detection of AD pathology in both SMC and in AD clinical trials.

Amyloid and tau-PET in early-onset AD: Baseline data from the Longitudinal Early-onset Alzheimer's Disease Study (LEADS).

INTRODUCTION: We aimed to describe baseline amyloid-beta (Aß) and tau-positron emission tomograrphy (PET) from Longitudinal Early-onset Alzheimer's Disease Study (LEADS), a prospective multi-site observational study of sporadic early-onset Alzheimer's disease (EOAD). METHODS: We analyzed baseline [18F]Florbetaben (Aß) and [18F]Flortaucipir (tau)-PET from cognitively impaired participants with a clinical diagnosis of mild cognitive impairment (MCI) or AD dementia aged < 65 years. Florbetaben scans were used to distinguish cognitively impaired participants with EOAD (Aß+) from EOnonAD (Aß-) based on the combination of visual read by expert reader and image quantification. RESULTS: 243/321 (75.7%) of participants were assigned to the EOAD group based on amyloid-PET; 231 (95.1%) of them were tau-PET positive (A+T+). Tau-PET signal was elevated across cortical regions with a parietal-predominant pattern, and higher burden was observed in younger and female EOAD participants. DISCUSSION: LEADS data emphasizes the importance of biomarkers to enhance diagnostic accuracy in EOAD. The advanced tau-PET binding at baseline might have implications for therapeutic strategies in patients with EOAD. HIGHLIGHTS: 72% of patients with clinical EOAD were positive on both amyloid- and tau-PET. Amyloid-positive patients with EOAD had high tau-PET signal across cortical regions. In EOAD, tau-PET mediated the relationship between amyloid-PET and MMSE. Among EOAD patients, younger onset and female sex were associated with higher tau-PET.

Criterion Validation of Tau PET Staging Schemes in Relation to Cognitive Outcomes.

BACKGROUND: Utilization of NIA-AA Research Framework requires dichotomization of tau pathology. However, due to the novelty of tau-PET imaging, there is no consensus on methods to categorize scans into "positive" or "negative" (T+ or T-). In response, some tau topographical pathologic staging schemes have been developed. OBJECTIVE: The aim of the current study is to establish criterion validity to support these recently-developed staging schemes. METHODS: Tau-PET data from 465 participants from the Alzheimer's Disease Neuroimaging Initiative (aged 55 to 90) were classified as T+ or T- using decision rules for the Temporal-Occipital Classification (TOC), Simplified TOC (STOC), and Lobar Classification (LC) tau pathologic schemes of Schwarz, and Chen staging scheme. Subsequent dichotomization was analyzed in comparison to memory and learning slope performances, and diagnostic accuracy using actuarial diagnostic methods. RESULTS: Tau positivity was associated with worse cognitive performance across all staging schemes. Cognitive measures were nearly all categorized as having "fair" sensitivity at classifying tau status using TOC, STOC, and LC schemes. Results were comparable between Schwarz schemes, though ease of use and better data fit preferred the STOC and LC schemes. While some evidence was supportive for Chen's scheme, validity lagged behind others-likely due to elevated false positive rates. CONCLUSIONS: Tau-PET staging schemes appear to be valuable for Alzheimer's disease diagnosis, tracking, and screening for clinical trials. Their validation provides support as options for tau pathologic dichotomization, as necessary for use of NIA-AA Research Framework. Future research should consider other staging schemes and validation with other outcome benchmarks.

Spatial transcriptomic patterns underlying regional vulnerability to amyloid-ß and tau pathologies and their relationships to cognitive dysfunction in Alzheimer's disease.

Amyloid-ß (Aß) and tau proteins accumulate within distinct neuronal systems in Alzheimer's disease (AD). Although it is not clear why certain brain regions are more vulnerable to Aß and tau pathologies than others, gene expression may play a role. We studied the association between brain-wide gene expression profiles and regional vulnerability to Aß (gene-to-Aß associations) and tau (gene-to-tau associations) pathologies leveraging two large independent cohorts (n = 715) of participants along the AD continuum. We identified several AD susceptibility genes and gene modules in a gene co-expression network with expression profiles related to regional vulnerability to Aß and tau pathologies in AD. In particular, we found that the positive APOE -to-tau association was only seen in the AD cohort, whereas patients with AD and frontotemporal dementia shared similar positive MAPT -to-tau association. Some AD candidate genes showed sex-dependent negative gene-to-Aß and gene-to-tau associations. In addition, we identified distinct biochemical pathways associated with the gene-to-Aß and the gene-to-tau associations. Finally, we proposed a novel analytic framework, linking the identified gene-to-pathology associations to cognitive dysfunction in AD at the individual level, suggesting potential clinical implication of the gene-to-pathology associations. Taken together, our study identified distinct gene expression profiles and biochemical pathways that may explain the discordance between regional Aß and tau pathologies, and filled the gap between gene-to-pathology associations and cognitive dysfunction in individual AD patients that may ultimately help identify novel personalized pathogenetic biomarkers and therapeutic targets. One Sentence Summary: We identified replicable cognition-related associations between regional gene expression profiles and selectively regional vulnerability to amyloid-ß and tau pathologies in AD.

Multi-ancestry genome-wide meta-analysis of 56,241 individuals identifies LRRC4C, LHX5-AS1 and nominates ancestry-specific loci PTPRK , GRB14 , and KIAA0825 as novel risk loci for Alzheimer's disease: the Alzheimer's Disease Genetics Consortium.

Limited ancestral diversity has impaired our ability to detect risk variants more prevalent in non-European ancestry groups in genome-wide association studies (GWAS). We constructed and analyzed a multi-ancestry GWAS dataset in the Alzheimer's Disease (AD) Genetics Consortium (ADGC) to test for novel shared and ancestry-specific AD susceptibility loci and evaluate underlying genetic architecture in 37,382 non-Hispanic White (NHW), 6,728 African American, 8,899 Hispanic (HIS), and 3,232 East Asian individuals, performing within-ancestry fixed-effects meta-analysis followed by a cross-ancestry random-effects meta-analysis. We identified 13 loci with cross-ancestry associations including known loci at/near CR1 , BIN1 , TREM2 , CD2AP , PTK2B , CLU , SHARPIN , MS4A6A , PICALM , ABCA7 , APOE and two novel loci not previously reported at 11p12 ( LRRC4C ) and 12q24.13 ( LHX5-AS1 ). Reflecting the power of diverse ancestry in GWAS, we observed the SHARPIN locus using 7.1% the sample size of the original discovering single-ancestry GWAS (n=788,989). We additionally identified three GWS ancestry-specific loci at/near ( PTPRK ( P =2.4×10 -8 ) and GRB14 ( P =1.7×10 -8 ) in HIS), and KIAA0825 ( P =2.9×10 -8 in NHW). Pathway analysis implicated multiple amyloid regulation pathways (strongest with P adjusted =1.6×10 -4 ) and the classical complement pathway ( P adjusted =1.3×10 -3 ). Genes at/near our novel loci have known roles in neuronal development ( LRRC4C, LHX5-AS1 , and PTPRK ) and insulin receptor activity regulation ( GRB14 ). These findings provide compelling support for using traditionally-underrepresented populations for gene discovery, even with smaller sample sizes.

Donanemab in Early Symptomatic Alzheimer Disease: The TRAILBLAZER-ALZ 2 Randomized Clinical Trial.

Importance: There are limited efficacious treatments for Alzheimer disease. Objective: To assess efficacy and adverse events of donanemab, an antibody designed to clear brain amyloid plaque. Design, Setting, and Participants: Multicenter (277 medical research centers/hospitals in 8 countries), randomized, double-blind, placebo-controlled, 18-month phase 3 trial that enrolled 1736 participants with early symptomatic Alzheimer disease (mild cognitive impairment/mild dementia) with amyloid and low/medium or high tau pathology based on positron emission tomography imaging from June 2020 to November 2021 (last patient visit for primary outcome in April 2023). Interventions: Participants were randomized in a 1:1 ratio to receive donanemab (n = 860) or placebo (n = 876) intravenously every 4 weeks for 72 weeks. Participants in the donanemab group were switched to receive placebo in a blinded manner if dose completion criteria were met. Main Outcomes and Measures: The primary outcome was change in integrated Alzheimer Disease Rating Scale (iADRS) score from baseline to 76 weeks (range, 0-144; lower scores indicate greater impairment). There were 24 gated outcomes (primary, secondary, and exploratory), including the secondary outcome of change in the sum of boxes of the Clinical Dementia Rating Scale (CDR-SB) score (range, 0-18; higher scores indicate greater impairment). Statistical testing allocated α of .04 to testing low/medium tau population outcomes, with the remainder (.01) for combined population outcomes. Results: Among 1736 randomized participants (mean age, 73.0 years; 996 [57.4%] women; 1182 [68.1%] with low/medium tau pathology and 552 [31.8%] with high tau pathology), 1320 (76%) completed the trial. Of the 24 gated outcomes, 23 were statistically significant. The least-squares mean (LSM) change in iADRS score at 76 weeks was -6.02 (95% CI, -7.01 to -5.03) in the donanemab group and -9.27 (95% CI, -10.23 to -8.31) in the placebo group (difference, 3.25 [95% CI, 1.88-4.62]; P < .001) in the low/medium tau population and -10.2 (95% CI, -11.22 to -9.16) with donanemab and -13.1 (95% CI, -14.10 to -12.13) with placebo (difference, 2.92 [95% CI, 1.51-4.33]; P < .001) in the combined population. LSM change in CDR-SB score at 76 weeks was 1.20 (95% CI, 1.00-1.41) with donanemab and 1.88 (95% CI, 1.68-2.08) with placebo (difference, -0.67 [95% CI, -0.95 to -0.40]; P < .001) in the low/medium tau population and 1.72 (95% CI, 1.53-1.91) with donanemab and 2.42 (95% CI, 2.24-2.60) with placebo (difference, -0.7 [95% CI, -0.95 to -0.45]; P < .001) in the combined population. Amyloid-related imaging abnormalities of edema or effusion occurred in 205 participants (24.0%; 52 symptomatic) in the donanemab group and 18 (2.1%; 0 symptomatic during study) in the placebo group and infusion-related reactions occurred in 74 participants (8.7%) with donanemab and 4 (0.5%) with placebo. Three deaths in the donanemab group and 1 in the placebo group were considered treatment related. Conclusions and Relevance: Among participants with early symptomatic Alzheimer disease and amyloid and tau pathology, donanemab significantly slowed clinical progression at 76 weeks in those with low/medium tau and in the combined low/medium and high tau pathology population. Trial Registration: ClinicalTrials.gov Identifier: NCT04437511.

A simulative deep learning model of SNP interactions on chromosome 19 for predicting Alzheimer's disease risk and rates of disease progression.

BACKGROUND: Identifying genetic patterns that contribute to Alzheimer's disease (AD) is important not only for pre-symptomatic risk assessment but also for building personalized therapeutic strategies. METHODS: We implemented a novel simulative deep learning model to chromosome 19 genetic data from the Alzheimer's Disease Neuroimaging Initiative and the Imaging and Genetic Biomarkers of Alzheimer's Disease datasets. The model quantified the contribution of each single nucleotide polymorphism (SNP) and their epistatic impact on the likelihood of AD using the occlusion method. The top 35 AD-risk SNPs in chromosome 19 were identified, and their ability to predict the rate of AD progression was analyzed. RESULTS: Rs561311966 (APOC1) and rs2229918 (ERCC1/CD3EAP) were recognized as the most powerful factors influencing AD risk. The top 35 chromosome 19 AD-risk SNPs were significant predictors of AD progression. DISCUSSION: The model successfully estimated the contribution of AD-risk SNPs that account for AD progression at the individual level. This can help in building preventive precision medicine.