Alzheimer's disease (AD) neuropathology is associated with neuroinflammation, but there are few useful biomarkers. Mutant variants of triggering receptor expressed on myeloid cells 2 (TREM2) have recently been linked to late-onset AD and other neurodegenerative disorders. TREM2, a microglial receptor, is involved in innate immunity. A cleaved fragment, soluble TREM2 (sTREM2), is present in the cerebrospinal fluid (CSF).

It is suggested that reductions in a medial temporo-parietal episodic memory network characterize Alzheimer's disease (AD), while changes in a fronto-striatal executive network characterize healthy aging. In the present study, magnetic resonance imaging (MRI) was used to test this directly. MRI scans of 372 participants from two samples were analyzed: Sample 1 consisted of 96 very mild to moderate AD patients, 93 healthy elderly (HE), and 137 young (HY), all with available MR scans, while Sample 2 consisted of 46 MCI patients, with available MR scans and measures of CSF biomarkers Abeta42 and tau protein. Substantial morphometric reductions of the medial temporo-parietal network were found in AD, while the fronto-striatal network was less affected. Both networks were affected by healthy aging, but the fronto-striatal to a greater degree than the medial temporo-parietal. Further exploratory analyses of 49 cortical and subcortical structures indicated no overlap between predictors of AD vs. HE and predictors of HE vs. HY. CSF biomarker pathology correlated with the medial temporo-parietal but not fronto-striatal network. Likewise, the AD-prone structures from the exploratory analyses were related to CSF biomarkers, while the aging-prone structures were not. It is concluded that the pattern of macrostructural brain changes in very mild to moderate AD can be clearly delineated from that of healthy aging.

A meta-analysis of publicly available summary statistics on multiple sclerosis combined with three Nordic multiple sclerosis cohorts (21,079 cases, 371,198 controls) revealed seven sequence variants associating with multiple sclerosis, not reported previously. Using polygenic risk scores based on public summary statistics of variants outside the major histocompatibility complex region we quantified genetic overlap between common autoimmune diseases in Icelanders and identified disease clusters characterized by autoantibody presence/absence. As multiple sclerosis-polygenic risk scores captures the risk of primary biliary cirrhosis and vice versa (P = 1.6 × 10-7, 4.3 × 10-9) we used primary biliary cirrhosis as a proxy-phenotype for multiple sclerosis, the idea being that variants conferring risk of primary biliary cirrhosis have a prior probability of conferring risk of multiple sclerosis. We tested 255 variants forming the primary biliary cirrhosis-polygenic risk score and found seven multiple sclerosis-associating variants not correlated with any previously established multiple sclerosis variants. Most of the variants discovered are close to or within immune-related genes. One is a low-frequency missense variant in TYK2, another is a missense variant in MTHFR that reduces the function of the encoded enzyme affecting methionine metabolism, reported to be dysregulated in multiple sclerosis brain.

The mechanisms of amyloid-β (Aβ)-degradation and clearance in Alzheimer's disease (AD) pathogenesis have been relatively little studied. Short Aβ-fragments form by enzymatic cleavage and alternate amyloid-beta precursor protein (APP)-processing. Here we characterized a novel polyclonal Aβ-antibody raised against an Aβ mid-domain and used it to investigate microglial Aβ-uptake in situ by microscopy at the light- and ultrastructural levels. The rabbit Aβ-mid-domain antibody (ab338), raised against the mid-domain amino acids 21-34 (Aβ21-34), was characterized with biochemical and histological techniques. To identify the epitope in Aβ recognized by ab338, solid phase and solution binding data were compared with peptide folding scores as calculated with the Tango software. The ab338 antibody displayed high average affinity (KD: 6.2 × 10-10 M) and showed preference for C-terminal truncated Aβ-peptides ending at amino acid 34 and Aβ-mid domain peptides with high scores of β-turn structure. In transgenic APP-mouse brain, ab338 labelled amyloid plaques and detected Aβ-fragments in microglia at the ultra- and light microscopic levels. This reinforces a role of microglia/macrophages in Aβ-clearance in vivo. The ab338 antibody might be a valuable tool to study Aβ-clearance by microglial uptake and Aβ-mid-domain peptides generated by enzymatic degradation and alternate production.

Cerebrospinal fluid (CSF) β-site amyloid precursor protein cleaving enzyme 1 (BACE1), neurogranin and the neurogranin/BACE1 ratio are proposed markers for Alzheimer's disease. BACE1 is also a drug target. However, CSF levels may differ between early-stage amyloid plaque formation (A) and later stage downstream tau-tangle pathology (T) and neurodegeneration (N) and may be expressed as an A/T/N stage (e.g. A+/T-/N or A+/T+/N+). Whether BACE1 and neurogranin levels are persistent traits or change with disease progression is unknown. The aim of this study was to investigate whether CSF neurogranin and BACE1 concentrations differ between A/T/N stages, whether these change over time and correlate with memory decline. This may have implications for patient selection in future trials. We used CSF markers to determine A/T/N stage using amyloid beta42/40 ratio, p-tau181 and total-tau respectively in predementia Alzheimer's disease cases (n = 176) [including cases that progressed to dementia (n = 10)] and controls (n = 74) from the Norwegian Dementia Disease Initiation cohort. We selected cases at the presumed early (A+/T-/N-, n = 86) and late stages (A+/T+/N+, n = 90) of the Alzheimer's disease continuum and controlled with normal markers (A-/T-/N-, n = 74). A subset of subjects in all A/T/N groups underwent repeat CSF sampling at approximately 2-year intervals up to 6 years from baseline. Using linear mixed models, longitudinal measurements of CSF BACE1 and neurogranin levels in A+/T-/N- and A+/T+/N+ as compared to A-/T-/N- healthy controls were performed. Next, we measured changes in CSF BACE1 and neurogranin levels in cases that progressed from A-/T-/N- to A+/T-/N- (n = 12), from A+/T-/N- to A+/T or N+ (n = 12), remained stable A+/T-/N- (n = 26), remained stable A+/T+/N+ (n = 28) compared with controls remaining stable A-/T-/N- (n = 33). Lastly, associations between these markers and memory decline were assessed. Compared with A-/T-/N- healthy controls, neurogranin was unaltered in A+/T-/N- (n.s.) but higher in A+/T+/N+ (P < 0.0001). In contrast, BACE1 was lower in A+/T-/N- (P < 0.05) and higher in A+/T+/N+ (P < 0.0001). The neurogranin/BACE1 ratio was increased in both A+/T-/N- (P < 0.05) and A+/T+/N+ (P < 0.0001) groups as compared to A-/T-/N- healthy controls and was more strongly associated with memory decline (b = -0.29, P = 0.0006) than neurogranin (b = -0.20, P = 0.002) and BACE1 (b = -0.13, P = 0.046). Neurogranin and BACE1 level differences remained stable over time not only within A/T/N groups but also in patients progressing to more pathological A/T/N stages (e.g. progressing from A+/T-/N- to A + T or N+) and in cases progressing to dementia. Our results suggest that neurogranin and BACE1 levels may differentiate pathomechanistic Alzheimer's disease subgroups, putatively with different options for treatment.

Identification of proteins and genetic factors that reduce Alzheimer disease (AD) pathology is of importance when searching for novel AD treatments. Heterozygosity of the KL-VS haplotype has been associated with reduced amyloid and tau burden. Whether this association is mediated by the Klotho protein remains unclear.

Low-frequency 1q21.1 distal deletion and duplication copy number variant (CNV) carriers are predisposed to multiple neurodevelopmental disorders, including schizophrenia, autism and intellectual disability. Human carriers display a high prevalence of micro- and macrocephaly in deletion and duplication carriers, respectively. The underlying brain structural diversity remains largely unknown. We systematically called CNVs in 38 cohorts from the large-scale ENIGMA-CNV collaboration and the UK Biobank and identified 28 1q21.1 distal deletion and 22 duplication carriers and 37,088 non-carriers (48% male) derived from 15 distinct magnetic resonance imaging scanner sites. With standardized methods, we compared subcortical and cortical brain measures (all) and cognitive performance (UK Biobank only) between carrier groups also testing for mediation of brain structure on cognition. We identified positive dosage effects of copy number on intracranial volume (ICV) and total cortical surface area, with the largest effects in frontal and cingulate cortices, and negative dosage effects on caudate and hippocampal volumes. The carriers displayed distinct cognitive deficit profiles in cognitive tasks from the UK Biobank with intermediate decreases in duplication carriers and somewhat larger in deletion carriers-the latter potentially mediated by ICV or cortical surface area. These results shed light on pathobiological mechanisms of neurodevelopmental disorders, by demonstrating gene dose effect on specific brain structures and effect on cognitive function.

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele.

An important step in the analysis of magnetic resonance imaging (MRI) data for neuroimaging is the automated segmentation of white matter hyperintensities (WMHs). Fluid Attenuated Inversion Recovery (FLAIR-weighted) is an MRI contrast that is particularly useful to visualize and quantify WMHs, a hallmark of cerebral small vessel disease and Alzheimer's disease (AD). In order to achieve high spatial resolution in each of the three voxel dimensions, clinical MRI protocols are evolving to a three-dimensional (3D) FLAIR-weighted acquisition. The current study details the deployment of deep learning tools to enable automated WMH segmentation and characterization from 3D FLAIR-weighted images acquired as part of a national AD imaging initiative. Based on data from the ongoing Norwegian Disease Dementia Initiation (DDI) multicenter study, two 3D models-one off-the-shelf from the NVIDIA nnU-Net framework and the other internally developed-were trained, validated, and tested. A third cutting-edge Deep Bayesian network model (HyperMapp3r) was implemented without any de-novo tuning to serve as a comparison architecture. The 2.5D in-house developed and 3D nnU-Net models were trained and validated in-house across five national collection sites among 441 participants from the DDI study, of whom 194 were men and whose average age was (64.91 +/- 9.32) years. Both an external dataset with 29 cases from a global collaborator and a held-out subset of the internal data from the 441 participants were used to test all three models. These test sets were evaluated independently. The ground truth human-in-the-loop segmentation was compared against five established WMH performance metrics. The 3D nnU-Net had the highest performance out of the three tested networks, outperforming both the internally developed 2.5D model and the SOTA Deep Bayesian network with an average dice similarity coefficient score of 0.76 +/- 0.16. Our findings demonstrate that WMH segmentation models can achieve high performance when trained exclusively on FLAIR input volumes that are 3D volumetric acquisitions. Single image input models are desirable for ease of deployment, as reflected in the current embedded clinical research project. The 3D nnU-Net had the highest performance, which suggests a way forward for our need to automate WMH segmentation while also evaluating performance metrics during on-going data collection and model retraining.

Brain innate immune activation is associated with Alzheimer's disease (AD), but degrees of activation may vary between disease stages. Thus, brain innate immune activation must be assessed in longitudinal clinical studies that include biomarker negative healthy controls and cases with established AD pathology. Here, we employ longitudinally sampled cerebrospinal fluid (CSF) core AD, immune activation and glial biomarkers to investigate early (predementia stage) innate immune activation levels and biomarker profiles.

Dementia with Lewy Bodies (DLB) is a common neurodegenerative disorder with poor prognosis and mainly unknown pathophysiology. Heritability estimates exceed 30% but few genetic risk variants have been identified. Here we investigated common genetic variants associated with DLB in a large European multisite sample. We performed a genome wide association study in Norwegian and European cohorts of 720 DLB cases and 6490 controls and included 19 top-associated single-nucleotide polymorphisms in an additional cohort of 108 DLB cases and 75545 controls from Iceland. Overall the study included 828 DLB cases and 82035 controls. Variants in the ASH1L/GBA (Chr1q22) and APOE ε4 (Chr19) loci were associated with DLB surpassing the genome-wide significance threshold (p < 5 × 10-8). One additional genetic locus previously linked to psychosis in Alzheimer's disease, ZFPM1 (Chr16q24.2), showed suggestive association with DLB at p-value < 1 × 10-6. We report two susceptibility loci for DLB at genome-wide significance, providing insight into etiological factors. These findings highlight the complex relationship between the genetic architecture of DLB and other neurodegenerative disorders.

To meet the need for Parkinson's disease biomarkers and evidence for amount and distribution of pathological changes, MRI diffusion tensor imaging (DTI) has been explored in a number of previous studies. However, conflicting results warrant further investigations. As tissue microstructure, particularly of the grey matter, is heterogeneous, a more precise diffusion model may benefit tissue characterization. The purpose of this study was to analyze the diffusion-based imaging technique restriction spectrum imaging (RSI) and DTI, and their ability to detect microstructural changes within brain regions associated with motor function in Parkinson's disease. Diffusion weighted (DW) MR images of a total of 100 individuals, (46 Parkinson's disease patients and 54 healthy controls) were collected using b-values of 0-4000s/mm2. Output diffusion-based maps were estimated based on the RSI-model combining the full set of DW-images (Cellular Index (CI), Neurite Density (ND)) and DTI-model combining b = 0 and b = 1000 s/mm2 (fractional anisotropy (FA), Axial-, Mean- and Radial diffusivity (AD, MD, RD)). All parametric maps were analyzed in a voxel-wise group analysis, with focus on typical brain regions associated with Parkinson's disease pathology. CI, ND and DTI diffusivity metrics (AD, MD, RD) demonstrated the ability to differentiate between groups, with strongest performance within the thalamus, prone to pathology in Parkinson's disease. Our results indicate that RSI may improve the predictive power of diffusion-based MRI, and provide additional information when combined with the standard diffusivity measurements. In the absence of major atrophy, diffusion techniques may reveal microstructural pathology. Our results suggest that protocols for MRI diffusion imaging may be adapted to more sensitive detection of pathology at different sites of the central nervous system.

In the care of persons with cognitive problems, it is important to use a valid mild cognitive impairment (MCI) criterion that discriminates well between normal and pathological aging.

In the quest for prevention or treatment, there is a need to find early markers for preclinical dementia. This study observed memory clinic patients with subjective cognitive impairment (SCI) and normal cognitive function at baseline. The primary aim was to address SCI as a potential risk factor for cognitive decline. The secondary aim was to address a potential relation between (1) baseline cerebrospinal fluid biomarkers and (2) a decline in memory performance over the first 2 years of follow-up, with a possible cognitive decline after 6 years.

Neuronal and glial cell interaction is essential for synaptic homeostasis and may be affected in Alzheimer's disease (AD). We measured cerebrospinal fluid (CSF) neuronal and glia markers along the AD continuum, to reveal putative protective or harmful stage-dependent patterns of activation.

Subjective cognitive decline (SCD) is associated with an increased risk of Alzheimer's disease (AD). However, patients reporting SCD to their general practitioner are not always referred to a memory clinic.

White matter hyperintensities (WMHs) are associated with vascular risk and Alzheimer's disease. In this study, we examined relations between WMH load and distribution, amyloid pathology and vascular risk in 339 controls and cases with either subjective (SCD) or mild cognitive impairment (MCI). Regional deep (DWMH) and periventricular (PWMH) WMH loads were determined using an automated algorithm. We stratified on Aβ1-42 pathology (Aβ+/-) and analyzed group differences, as well as associations with Framingham Risk Score for cardiovascular disease (FRS-CVD) and age. Occipital PWMH (p = 0.001) and occipital DWMH (p = 0.003) loads were increased in SCD-Aβ+ compared with Aβ- controls. In MCI-Aβ+ compared with Aβ- controls, there were differences in global WMH (p = 0.003), as well as occipital DWMH (p = 0.001) and temporal DWMH (p = 0.002) loads. FRS-CVD was associated with frontal PWMHs (p = 0.003) and frontal DWMHs (p = 0.005), after adjusting for age. There were associations between global and all regional WMH loads and age. In summary, posterior WMH loads were increased in SCD-Aβ+ and MCI-Aβ+ cases, whereas frontal WMHs were associated with vascular risk. The differences in WMH topography support the use of regional WMH load as an early-stage marker of etiology.

Introduction: Amyloid beta 1-43 (Aβ43), with its additional C-terminal threonine residue, is hypothesized to play a role in early Alzheimer's disease pathology possibly different from that of amyloid beta 1-42 (Aβ42). Cerebrospinal fluid (CSF) Aβ43 has been suggested as a potential novel biomarker for predicting conversion from mild cognitive impairment (MCI) to dementia in Alzheimer's disease. However, the relationship between CSF Aβ43 and established imaging biomarkers of Alzheimer's disease has never been assessed. Materials and Methods: In this observational study, CSF Aβ43 was measured with ELISA in 89 subjects; 34 with subjective cognitive decline (SCD), 51 with MCI, and four with resolution of previous cognitive complaints. All subjects underwent structural MRI; 40 subjects on a 3T and 50 on a 1.5T scanner. Forty subjects, including 24 with SCD and 12 with MCI, underwent 18F-Flutemetamol PET. Seventy-eight subjects were assessed with 18F-fluorodeoxyglucose PET (21 SCD/7 MCI and 11 SCD/39 MCI on two different scanners). Ten subjects with SCD and 39 with MCI also underwent diffusion tensor imaging. Results: Cerebrospinal fluid Aβ43 was both alone and together with p-tau a significant predictor of the distinction between SCD and MCI. There was a marked difference in CSF Aβ43 between subjects with 18F-Flutemetamol PET scans visually interpreted as negative (37 pg/ml, n = 27) and positive (15 pg/ml, n = 9), p < 0.001. Both CSF Aβ43 and Aβ42 were negatively correlated with standardized uptake value ratios for all analyzed regions; CSF Aβ43 average rho -0.73, Aβ42 -0.74. Both CSF Aβ peptides correlated significantly with hippocampal volume, inferior parietal and frontal cortical thickness and axial diffusivity in the corticospinal tract. There was a trend toward CSF Aβ42 being better correlated with cortical glucose metabolism. None of the studied correlations between CSF Aβ43/42 and imaging biomarkers were significantly different for the two Aβ peptides when controlling for multiple testing. Conclusion: Cerebrospinal fluid Aβ43 appears to be strongly correlated with cerebral amyloid deposits in the same way as Aβ42, even in non-demented patients with only subjective cognitive complaints. Regarding imaging biomarkers, there is no evidence from the present study that CSF Aβ43 performs better than the classical CSF biomarker Aβ42 for distinguishing SCD and MCI.

While APOEɛ4 is the major genetic risk factor for Alzheimer's disease (AD), amyloid dysmetabolism is an initial or early event predicting clinical disease and is an important focus for secondary intervention trials. To improve identification of cases with increased AD risk, we evaluated recruitment procedures using pathological CSF concentrations of Aβ42 (pAβ) and APOEɛ4 as risk markers in a multi-center study in Norway. In total, 490 subjects aged 40-80 y were included after response to advertisements and media coverage or memory clinics referrals. Controls (n = 164) were classified as normal controls without first-degree relatives with dementia (NC), normal controls with first-degree relatives with dementia (NCFD), or controls scoring below norms on cognitive screening. Patients (n = 301) were classified as subjective cognitive decline or mild cognitive impairment. Subjects underwent a clinical and cognitive examination and MRI according to standardized protocols. Core biomarkers in CSF from 411 and APOE genotype from 445 subjects were obtained. Cases (both self-referrals (n = 180) and memory clinics referrals (n = 87)) had increased fractions of pAβ and APOEɛ4 frequency compared to NC. Also, NCFD had higher APOEɛ4 frequencies without increased fraction of pAβ compared to NC, and cases recruited from memory clinics had higher fractions of pAβ and APOEɛ4 frequency than self-referred. This study shows that memory clinic referrals are pAβ enriched, whereas self-referred and NCFD cases more frequently are pAβ negative but at risk (APOEɛ4 positive), suitable for primary intervention.

We used diffusion tensor imaging (DTI) to test the following hypotheses: (1) there is decreased white matter (WM) integrity in non-demented Parkinson's disease (PD), (2) WM integrity is differentially reduced in PD and early Alzheimer's disease (AD) and (3) DTI changes in non-demented PD are specifically associated with cognitive performance.