The Correlation between Inflammatory Biomarkers and Polygenic Risk Score in Alzheimer's Disease

Targeting terminal pathway reduces brain complement activation, amyloid load and synapse loss, and improves cognition in a mouse model of dementia

Complement is dysregulated in the brain in Alzheimer's Disease and in mouse models of Alzheimer's disease. Each of the complement derived effectors, opsonins, anaphylatoxins and membrane attack complex (MAC), have been implicated as drivers of disease but their relative contributions remain unclarified. Here we have focussed on the MAC, a lytic and pro-inflammatory effector, in the AppNL-G-F mouse amyloidopathy model. To test the role of MAC, we back-crossed to generate AppNL-G-F mice deficient in C7, an essential MAC component. C7 deficiency ablated MAC formation, reduced synapse loss and amyloid load and improved cognition compared to complement-sufficient AppNL-G-F mice at 8-10 months age. Adding back C7 caused increased MAC formation in brain and an acute loss of synapses in C7-deficient AppNL-G-F mice. To explore whether C7 was a viable therapeutic target, a C7-blocking monoclonal antibody was administered systemically for one month in AppNL-G-F mice aged 8-9 months. Treatment reduced brain MAC and amyloid deposition, increased synapse density and improved cognitive performance compared to isotype control-treated AppNL-G-F mice. The findings implicate MAC as a driver of pathology and highlight the potential for complement inhibition at the level of MAC as a therapy in Alzheimer's disease.

Regulation of human microglial gene expression and function via RNAase-H active antisense oligonucleotides in vivo in Alzheimer's disease

BACKGROUND

Microglia play important roles in maintaining brain homeostasis and neurodegeneration. The discovery of genetic variants in genes predominately or exclusively expressed in myeloid cells, such as Apolipoprotein E (APOE) and triggering receptor expressed on myeloid cells 2 (TREM2), as the strongest risk factors for Alzheimer's disease (AD) highlights the importance of microglial biology in the brain. The sequence, structure and function of several microglial proteins are poorly conserved across species, which has hampered the development of strategies aiming to modulate the expression of specific microglial genes. One way to target APOE and TREM2 is to modulate their expression using antisense oligonucleotides (ASOs).

METHODS

In this study, we identified, produced, and tested novel, selective and potent ASOs for human APOE and TREM2. We used a combination of in vitro iPSC-microglia models, as well as microglial xenotransplanted mice to provide proof of activity in human microglial in vivo.

RESULTS

We proved their efficacy in human iPSC microglia in vitro, as well as their pharmacological activity in vivo in a xenografted microglia model. We demonstrate ASOs targeting human microglia can modify their transcriptional profile and their response to amyloid-β plaques in vivo in a model of AD.

CONCLUSIONS

This study is the first proof-of-concept that human microglial can be modulated using ASOs in a dose-dependent manner to manipulate microglia phenotypes and response to neurodegeneration in vivo.

The complement system in neurodegenerative diseases

Complement is an important component of innate immune defence against pathogens and crucial for efficient immune complex disposal. These core protective activities are dependent in large part on properly regulated complement-mediated inflammation. Dysregulated complement activation, often driven by persistence of activating triggers, is a cause of pathological inflammation in numerous diseases, including neurological diseases. Increasingly, this has become apparent not only in well-recognized neuroinflammatory diseases like multiple sclerosis but also in neurodegenerative and neuropsychiatric diseases where inflammation was previously either ignored or dismissed as a secondary event. There is now a large and rapidly growing body of evidence implicating complement in neurological diseases that cannot be comprehensively addressed in a brief review. Here, we will focus on neurodegenerative diseases, including not only the 'classical' neurodegenerative diseases such as Alzheimer's disease and Parkinson's disease, but also two other neurological diseases where neurodegeneration is a neglected feature and complement is implicated, namely, schizophrenia, a neurodevelopmental disorder with many mechanistic features of neurodegeneration, and multiple sclerosis, a demyelinating disorder where neurodegeneration is a major cause of progressive decline. We will discuss the evidence implicating complement as a driver of pathology in these diverse diseases and address briefly the potential and pitfalls of anti-complement drug therapy for neurodegenerative diseases.

Complement factor I: Regulatory nexus, driver of immunopathology, and therapeutic

Complement factor I (FI) is the nexus for classical, lectin and alternative pathway complement regulation. FI is an 88 kDa plasma protein that circulates in an inactive configuration until it forms a trimolecular complex with its cofactor and substrate whereupon a structural reorganization allows the catalytic triad to cleave its substrates, C3b and C4b. In keeping with its role as the master complement regulatory enzyme, deficiency has been linked to immunopathology. In the setting of complete FI deficiency, a consumptive C3 deficiency results in recurrent infections with encapsulated microorganisms. Aseptic cerebral inflammation and vasculitic presentations are also less commonly observed. Heterozygous mutations in the factor I gene (CFI) have been demonstrated to be enriched in atypical haemolytic uraemic syndrome, albeit with a very low penetrance. Haploinsufficiency of CFI has also been associated with decreased retinal thickness and is a strong risk factor for the development of age-related macular degeneration. Supplementation of FI using plasma purified or recombinant protein has long been postulated, however, technical difficulties prevented progression into clinical trials. It is only using gene therapy that CFI supplementation has reached the clinic with GT005 in phase I/II clinical trials for geographic atrophy.

Pathway-specific polygenic risk scores correlate with clinical status and Alzheimer's-related biomarkers

Background: APOE is the largest genetic risk factor for sporadic Alzheimer's disease (AD), but there is a substantial polygenic component as well. Polygenic risk scores (PRS) can summarize small effects across the genome but may obscure differential risk associated with different molecular processes and pathways. Variability at the genetic level may contribute to the extensive phenotypic heterogeneity of Alzheimer's disease (AD). Here, we examine polygenic risk impacting specific pathways associated with AD and examined its relationship with clinical status and AD biomarkers of amyloid, tau, and neurodegeneration (A/T/N). Methods: A total of 1,411 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) with genotyping data were included. Sets of variants identified from a pathway analysis of AD GWAS summary statistics were combined into clusters based on their assigned pathway. We constructed pathway-specific PRSs for each participant and tested their associations with diagnostic status (AD vs cognitively normal), abnormal levels of amyloid and ptau (positive vs negative), and hippocampal volume. The APOE region was excluded from all PRSs, and analyses controlled for APOE -ε4 carrier status. Results: Thirteen pathway clusters were identified relating to categories such as immune response, amyloid precursor processing, protein localization, lipid transport and binding, tyrosine kinase, and endocytosis. Eight pathway-specific PRSs were significantly associated with AD dementia diagnosis. Amyloid-positivity was associated with endocytosis and fibril formation, response misfolded protein, and regulation protein tyrosine PRSs. Ptau positivity and hippocampal volume were both related to protein localization and mitophagy PRS, and ptau positivity was additionally associated with an immune signaling PRS. A global AD PRS showed stronger associations with diagnosis and all biomarkers compared to pathway PRSs, suggesting a strong synergistic effect of all loci contributing to the global AD PRS. Conclusions: Pathway PRS may contribute to understanding separable disease processes, but do not appear to add significant power for predictive purposes. These findings demonstrate that, although genetic risk for AD is widely distributed, AD-phenotypes may be preferentially associated with risk in specific pathways. Defining genetic risk along multiple dimensions at the individual level may help clarify the etiological heterogeneity in AD.

Serum IL-6, sAXL, and YKL-40 as systemic correlates of reduced brain structure and function in Alzheimer's disease: results from the DELCODE study

BACKGROUND

Neuroinflammation constitutes a pathological hallmark of Alzheimer's disease (AD). Still, it remains unresolved if peripheral inflammatory markers can be utilized for research purposes similar to blood-based beta-amyloid and neurodegeneration measures. We investigated experimental inflammation markers in serum and analyzed interrelations towards AD pathology features in a cohort with a focus on at-risk stages of AD.

METHODS

Data of 74 healthy controls (HC), 99 subjective cognitive decline (SCD), 75 mild cognitive impairment (MCI), 23 AD relatives, and 38 AD subjects were obtained from the DELCODE cohort. A panel of 20 serum biomarkers was determined using immunoassays. Analyses were adjusted for age, sex, APOE status, and body mass index and included correlations between serum and CSF marker levels and AD biomarker levels. Group-wise comparisons were based on screening diagnosis and routine AD biomarker-based schematics. Structural imaging data were combined into composite scores representing Braak stage regions and related to serum biomarker levels. The Preclinical Alzheimer's Cognitive Composite (PACC5) score was used to test for associations between the biomarkers and cognitive performance.

RESULTS

Each experimental marker displayed an individual profile of interrelations to AD biomarkers, imaging, or cognition features. Serum-soluble AXL (sAXL), IL-6, and YKL-40 showed the most striking associations. Soluble AXL was significantly elevated in AD subjects with pathological CSF beta-amyloid/tau profile and negatively related to structural imaging and cognitive function. Serum IL-6 was negatively correlated to structural measures of Braak regions, without associations to corresponding IL-6 CSF levels or other AD features. Serum YKL-40 correlated most consistently to CSF AD biomarker profiles and showed the strongest negative relations to structure, but none to cognitive outcomes.

CONCLUSIONS

Serum sAXL, IL-6, and YKL-40 relate to different AD features, including the degree of neuropathology and cognitive functioning. This may suggest that peripheral blood signatures correspond to specific stages of the disease. As serum markers did not reflect the corresponding CSF protein levels, our data highlight the need to interpret serum inflammatory markers depending on the respective protein's specific biology and cellular origin. These marker-specific differences will have to be considered to further define and interpret blood-based inflammatory profiles for AD research.

Pathway-Specific Polygenic Risk Scores Correlate with Clinical Status and Alzheimer's Disease-Related Biomarkers

BACKGROUND

APOE is the largest genetic risk factor for Alzheimer's disease (AD), but there is a substantial polygenic component. Polygenic risk scores (PRS) can summarize small effects across the genome but may obscure differential risk across molecular processes and pathways that contribute to heterogeneity of disease presentation.

OBJECTIVE

We examined polygenic risk impacting specific AD-associated pathways and its relationship with clinical status and biomarkers of amyloid, tau, and neurodegeneration (A/T/N).

METHODS

We analyzed data from 1,411 participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI). We applied pathway analysis and clustering to identify AD-associated "pathway clusters" and construct pathway-specific PRSs (excluding the APOE region). We tested associations with diagnostic status, abnormal levels of amyloid and ptau, and hippocampal volume.

RESULTS

Thirteen pathway clusters were identified, and eight pathway-specific PRSs were significantly associated with AD diagnosis. Amyloid-positivity was associated with endocytosis and fibril formation, response misfolded protein, and regulation protein tyrosine PRSs. Ptau positivity and hippocampal volume were both related to protein localization and mitophagy PRS, and ptau-positivity was also associated with an immune signaling PRS. A global AD PRS showed stronger associations with diagnosis and all biomarkers compared to pathway PRSs.

CONCLUSIONS

Pathway PRS may contribute to understanding separable disease processes, but do not add significant power for predictive purposes. These findings demonstrate that AD-phenotypes may be preferentially associated with risk in specific pathways, and defining genetic risk along multiple dimensions may clarify etiological heterogeneity in AD. This approach to delineate pathway-specific PRS can be used to study other complex diseases.

Dysregulation of complement system in neuropsychiatric disorders: A mini review

Complement system is one of the most important defense mechanisms of the innate immune system. In addition to their roles in immune regulation, complement proteins are also involved in neurodevelopment and adult brain plasticity. Complement dysregulation has been shown in neurodevelopmental disorders including schizophrenia and autism spectrum disorder as well as in mood disorders. A number of clinical as well as genetic studies suggest the role of complement proteins in the cortical thinning and excessive synaptic pruning frequently associated with schizophrenia. The changes in complement proteins are also associated with the pathophysiology of autism spectrum disorder, major depressive disorder and bipolar disorder, but warrant further research. In addition, rodent models suggest a strong case for complement system in anxiety-like behavior. In this article, we review the recent findings on the role of complement system in neuropsychiatric disorders. The possible uses for future complement targeted therapies are also discussed.

Influence of genetic and cardiometabolic risk factors in Alzheimer's disease

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder. Cardiometabolic and genetic risk factors play an important role in the trajectory of AD. Cardiometabolic risk factors including diabetes, mid-life obesity, mid-life hypertension and elevated cholesterol have been linked with cognitive decline in AD subjects. These potential risk factors associated with cerebral metabolic changes which fuel AD pathogenesis have been suggested to be the reason for the disappointing clinical trial results. In appreciation of the risks involved, using search engines such as PubMed, Scopus, MEDLINE and Google Scholar, a relevant literature search on cardiometabolic and genetic risk factors in AD was conducted. We discuss the role of genetic as well as established cardiovascular risk factors in the neuropathology of AD. Moreover, we show new evidence of genetic interaction between several genes potentially involved in different pathways related to both neurodegenerative process and cardiovascular damage.

Terminal complement pathway activation drives synaptic loss in Alzheimer’s disease models

Complement is involved in developmental synaptic pruning and pathological synapse loss in Alzheimer’s disease. It is posited that C1 binding initiates complement activation on synapses; C3 fragments then tag them for microglial phagocytosis. However, the precise mechanisms of complement-mediated synaptic loss remain unclear, and the role of the lytic membrane attack complex (MAC) is unexplored. We here address several knowledge gaps: (i) is complement activated through to MAC at the synapse? (ii) does MAC contribute to synaptic loss? (iii) can MAC inhibition prevent synaptic loss? Novel methods were developed and optimised to quantify C1q, C3 fragments and MAC in total and regional brain homogenates and synaptoneurosomes from WT and App^NL−G−F Alzheimer’s disease model mouse brains at 3, 6, 9 and 12 months of age. The impact on synapse loss of systemic treatment with a MAC blocking antibody and gene knockout of a MAC component was assessed in Alzheimer’s disease model mice. A significant increase in C1q, C3 fragments and MAC was observed in App^NL−G−F mice compared to controls, increasing with age and severity. Administration of anti-C7 antibody to App^NL−G−F mice modulated synapse loss, reflected by the density of dendritic spines in the vicinity of plaques. Constitutive knockout of C6 significantly reduced synapse loss in 3xTg-AD mice. We demonstrate that complement dysregulation occurs in Alzheimer’s disease mice involving the activation (C1q; C3b/iC3b) and terminal (MAC) pathways in brain areas associated with pathology. Inhibition or ablation of MAC formation reduced synapse loss in two Alzheimer’s disease mouse models, demonstrating that MAC formation is a driver of synapse loss. We suggest that MAC directly damages synapses, analogous to neuromuscular junction destruction in myasthenia gravis.

Inflammation subtypes in psychosis and their relationships with genetic risk for psychiatric and cardiometabolic disorders

Cardiometabolic disorders have known inflammatory implications, and peripheral measures of inflammation and cardiometabolic disorders are common in persons with psychotic disorders. Inflammatory signatures are also related to neurobiological and behavioral changes in psychosis. Relationships between systemic inflammation and cardiometabolic genetic risk in persons with psychosis have not been examined. Thirteen peripheral inflammatory markers and genome-wide genotyping were assessed in 122 participants (n ​= ​86 psychosis, n ​= ​36 healthy controls) of European ancestry. Cluster analyses of inflammatory markers classified higher and lower inflammation subgroups. Single-trait genetic risk scores (GRS) were constructed for each participant using previously reported GWAS summary statistics for the following traits: schizophrenia, bipolar disorder, major depressive disorder, coronary artery disease, type-2 diabetes, low-density lipoprotein, high-density lipoprotein, triglycerides, and waist-to-hip ratio. Genetic correlations across traits were quantified. Principal component (PC) analysis of the cardiometabolic GRSs generated six PC loadings used in regression models to examine associations with inflammation markers. Functional module discovery explored biological mechanisms of the inflammation association of cardiometabolic GRS genes. A subgroup of 38% persons with psychotic disorders was characterized with higher inflammation status. These higher inflammation individuals had lower BACS scores (p ​= ​0.038) compared to those with lower inflammation. The first PC of the cardiometabolic GRS matrix was related to higher inflammation status in persons with psychotic disorders (OR ​= ​2.037, p ​= ​0.001). Two of eight modules within the functional interaction network of cardiometabolic GRS genes were enriched for immune processes. Cardiometabolic genetic risk may predispose some individuals with psychosis to elevated inflammation which adversely impacts cognition associated with illness.

Blood-Based Biomarkers for Alzheimer's Disease Diagnosis and Progression: An Overview

Alzheimer’s Disease (AD) is a progressive neurodegenerative disease characterized by amyloid-β (Aβ) plaque deposition and neurofibrillary tangle accumulation in the brain. Although several studies have been conducted to unravel the complex and interconnected pathophysiology of AD, clinical trial failure rates have been high, and no disease-modifying therapies are presently available. Fluid biomarker discovery for AD is a rapidly expanding field of research aimed at anticipating disease diagnosis and following disease progression over time. Currently, Aβ_1–42, phosphorylated tau, and total tau levels in the cerebrospinal fluid are the best-studied fluid biomarkers for AD, but the need for novel, cheap, less-invasive, easily detectable, and more-accessible markers has recently led to the search for new blood-based molecules. However, despite considerable research activity, a comprehensive and up-to-date overview of the main blood-based biomarker candidates is still lacking. In this narrative review, we discuss the role of proteins, lipids, metabolites, oxidative-stress-related molecules, and cytokines as possible disease biomarkers. Furthermore, we highlight the potential of the emerging miRNAs and long non-coding RNAs (lncRNAs) as diagnostic tools, and we briefly present the role of vitamins and gut-microbiome-related molecules as novel candidates for AD detection and monitoring, thus offering new insights into the diagnosis and progression of this devastating disease.

Associations of Polygenic Risk Score for Late-Onset Alzheimer's Disease With Biomarkers

Late-onset Alzheimer's disease (LOAD) is a common irreversible neurodegenerative disease with heterogeneous genetic characteristics. Identifying the biological biomarkers with the potential to predict the conversion from normal controls to LOAD is clinically important for early interventions of LOAD and clinical treatment. The polygenic risk score for LOAD (AD-PRS) has been reported the potential possibility for reliably identifying individuals with risk of developing LOAD recently. To investigate the external phenotype changes resulting from LOAD and the underlying etiology, we summarize the comprehensive associations of AD-PRS with multiple biomarkers, including neuroimaging, cerebrospinal fluid and plasma biomarkers, cardiovascular risk factors, cognitive behavior, and mental health. This systematic review helps improve the understanding of the biomarkers with potential predictive value for LOAD and further optimizing the prediction and accurate treatment of LOAD.

Polygenic coronary artery disease association with brain atrophy in the cognitively impaired

While a number of low-frequency genetic variants of large effect size have been shown to underlie both cardiovascular disease and dementia, recent studies have highlighted the importance of common genetic variants of small effect size, which, in aggregate, are embodied by a polygenic risk score. We investigate the effect of polygenic risk for coronary artery disease on brain atrophy in Alzheimer's disease using whole-brain volume and put our findings in context with the polygenic risk for Alzheimer's disease and presumed small vessel disease as quantified by white-matter hyperintensities. We use 730 subjects from the Alzheimer's disease neuroimaging initiative database to investigate polygenic risk score effects (beyond APOE) on whole-brain volumes, total and regional white-matter hyperintensities and amyloid beta across diagnostic groups. In a subset of these subjects (N = 602), we utilized longitudinal changes in whole-brain volume over 24 months using the boundary shift integral approach. Linear regression and linear mixed-effects models were used to investigate the effect of white-matter hyperintensities at baseline as well as Alzheimer's disease-polygenic risk score and coronary artery disease-polygenic risk score on whole-brain atrophy and whole-brain atrophy acceleration, respectively. All genetic associations were examined under the oligogenic (P = 1e-5) and the more variant-inclusive polygenic (P = 0.5) scenarios. Results suggest no evidence for a link between the polygenic risk score and markers of Alzheimer's disease pathology at baseline (when stratified by diagnostic group). However, both Alzheimer's disease-polygenic risk score and coronary artery disease-polygenic risk score were associated with longitudinal decline in whole-brain volume (Alzheimer's disease-polygenic risk score t = 3.3, P _FDR = 0.007 over 24 months in healthy controls) and surprisingly, under certain conditions, whole-brain volume atrophy is statistically more correlated with cardiac polygenic risk score than Alzheimer's disease-polygenic risk score (coronary artery disease-polygenic risk score t = 2.1, P _FDR = 0.04 over 24 months in the mild cognitive impairment group). Further, in our regional analysis of white-matter hyperintensities, Alzheimer's disease-polygenic risk score beyond APOE is predictive of white-matter volume in the occipital lobe in Alzheimer's disease subjects in the polygenic regime. Finally, the rate of change of brain volume (or atrophy acceleration) may be sensitive to Alzheimer's disease-polygenic risk beyond APOE in healthy individuals (t = 2, P = 0.04). For subjects with mild cognitive impairment, beyond APOE, a more inclusive polygenic risk score including more variants, shows coronary artery disease-polygenic risk score to be more predictive of whole-brain volume atrophy, than an oligogenic approach including fewer larger effect size variants.

Polygenic Risk Scores in Alzheimer's Disease Genetics: Methodology, Applications, Inclusion, and Diversity

The success of genome-wide association studies (GWAS) completed in the last 15 years has reinforced a key fact: polygenic architecture makes a substantial contribution to variation of susceptibility to complex disease, including Alzheimer's disease. One straight-forward way to capture this architecture and predict which individuals in a population are most at risk is to calculate a polygenic risk score (PRS). This score aggregates the risk conferred across multiple genetic variants, ultimately representing an individual's predicted genetic susceptibility for a disease. PRS have received increasing attention after having been successfully used in complex traits. This has brought with it renewed attention on new methods which improve the accuracy of risk prediction. While these applications are initially informative, their utility is far from equitable: the majority of PRS models use samples heavily if not entirely of individuals of European descent. This basic approach opens concerns of health equity if applied inaccurately to other population groups, or health disparity if we fail to use them at all. In this review we will examine the methods of calculating PRS and some of their previous uses in disease prediction. We also advocate for, with supporting scientific evidence, inclusion of data from diverse populations in these existing and future studies of population risk via PRS.

Heterogeneity in Alzheimer's Disease Diagnosis and Progression Rates: Implications for Therapeutic Trials

The clinical presentation and the pathological processes underlying Alzheimer's disease (AD) can be very heterogeneous in severity, location, and composition including the amount and distribution of AB deposition and spread of neurofibrillary tangles in different brain regions resulting in atypical clinical patterns and the existence of distinct AD variants. Heterogeneity in AD may be related to demographic factors (such as age, sex, educational and socioeconomic level) and genetic factors, which influence underlying pathology, the cognitive and behavioral phenotype, rate of progression, the occurrence of neuropsychiatric features, and the presence of comorbidities (e.g., vascular disease, neuroinflammation). Heterogeneity is also manifest in the individual resilience to the development of neuropathology (brain reserve) and the ability to compensate for its cognitive and functional impact (cognitive and functional reserve). The variability in specific cognitive profiles and types of functional impairment may be associated with different progression rates, and standard measures assessing progression may not be equivalent for individual cognitive and functional profiles. Other factors, which may govern the presence, rate, and type of progression of AD, include the individuals' general medical health, the presence of specific systemic conditions, and lifestyle factors, including physical exercise, cognitive and social stimulation, amount of leisure activities, environmental stressors, such as toxins and pollution, and the effects of medications used to treat medical and behavioral conditions. These factors that affect progression are important to consider while designing a clinical trial to ensure, as far as possible, well-balanced treatment and control groups.

Blood-based biomarkers of agitation in Alzheimer's disease: Advances and future prospects

Agitation is a common neuropsychiatric symptom that becomes more prevalent as Alzheimer's disease (AD) increases in severity. The treatment of agitation is an urgent and unmet need due to the poor outcomes associated with it, its disruptive impact on patients and caregivers, and the lack of efficacious and safe treatments. Recent research on agitation in AD with blood-based biomarkers has advanced the search for its biomarkers beyond the brain and provides new insights to understand its mechanisms and improve treatments. Here, we reviewed studies of blood-based biomarkers of agitation in AD, which show that inflammatory biomarkers are increased in patients with agitation, may predict the development of agitation, and are associated with symptom severity. In addition, they may also track symptom severity and response to treatment. Other biomarkers associated with agitation include markers of oxidative stress, brain cholesterol metabolism, motor activity, and clusterin, a chaperone protein. These results are promising and need to be replicated. Preliminary evidence suggests a role for these biomarkers in interventional studies for agitation to predict and monitor treatment response, which may eventually help enrich study samples and deliver therapy likely to benefit individual patients. Advances in blood-based biomarkers of AD including those identified in "-omic" studies and high sensitivity assays provide opportunities to identify new biomarkers of agitation. Future studies of agitation and its treatment should investigate blood-based biomarkers to yield novel insights into the neurobiological mechanisms of agitation, monitoring symptoms and response to treatment, and to identify patients likely to respond to treatments.

Clusterin Is Associated with Systemic and Synovial Inflammation in Knee Osteoarthritis

OBJECTIVES

This study aimed to determine possible associations between transcriptional and translational levels of clusterin (CLU) in the systemic and local joint environments with the severity of knee osteoarthritis (OA) and to investigate CLU mRNA expression in knee OA fibroblast-like synoviocytes (FLSs) stimulated with tumor necrosis factor-α.

DESIGN

Circulating and synovial fluid CLU levels in 259 knee OA patients were quantified using an enzyme-linked immunosorbent assay. Relative CLU mRNA expression in 50 knee OA synovial tissues and 4 knee OA FLSs was determined using real-time polymerase chain reaction.

RESULTS

Plasma CLU levels of knee OA patients were significantly higher than paired synovial fluid samples. Compared with early-stage knee OA patients, those with advanced-stage OA had considerably increased plasma and synovial fluid CLU levels. There were significant positive associations of plasma and synovial fluid CLU levels with radiographic severity of knee OA. Plasma CLU levels were directly correlated with its synovial fluid levels and high-sensitivity C-reactive protein levels in the patients. Receiver-operating characteristic curve analysis unveiled the potential utility of plasma CLU as a novel biomarker for knee OA severity (AUC = 0.80), with a sensitivity of 71.4% and a specificity of 73.3%. Marked upregulation of CLU mRNA expression was observed in both the inflamed synovial tissues and FLSs of knee OA.

CONCLUSION

Increased CLU mRNA and protein levels in the systemic and local joint environments of knee OA might reflect knee OA severity, especially systemic and synovial inflammation.

Association Between Polygenic Risk Score and the Progression from Mild Cognitive Impairment to Alzheimer's Disease

BACKGROUND

Mild cognitive impairment (MCI) is a heterogeneous condition and MCI patients are at increased risk of progression to dementia due to Alzheimer's disease (AD).

OBJECTIVE

In this study, we aim to evaluate the associations between polygenic risk scores (PRSs) and 1) time to AD progression from MCI, 2) changes in longitudinal cognitive impairment, and 3) biomarkers from cerebrospinal fluid and imaging.

METHODS

We constructed PRS by using 40 independent non-APOE SNPs from well-replicated AD GWASs and tested its association with the progression time from MCI to AD by using 767 MCI patients from the ADNI study and 1373 patients from the NACC study. PRSs calculated with other methods were also computed.

RESULTS

We found that the PRS constructed with SNPs that reached genome-wide significance predicted the progression from MCI to AD (beta = 0.182, SE = 0.061, p = 0.003) after adjusting for the demographic and clinical variables. This association was replicated in the NACC dataset (beta = 0.094, SE = 0.037, p = 0.009). Further analyses revealed that PRS was associated with the increased ADAS-Cog11/ADAS-Cog13/ADASQ4 scores, tau/ptau levels, and cortical amyloid burdens (PiB-PET and AV45-PET), but decreased hippocampus and entorhinal cortex volumes (p < 0.05). Mediation analysis showed that the effect of PRS on the increased risk of AD may be mediated by Aβ42 (beta = 0.056, SE = 0.026, p = 0.036).

CONCLUSION

Our findings suggest that PRS can be useful for the prediction of time to AD and other clinical changes after the diagnosis of MCI.

Prefrontal cortex VAMP1 gene network moderates the effect of the early environment on cognitive flexibility in children

During development, genetic and environmental factors interact to modify specific phenotypes. Both in humans and in animal models, early adversities influence cognitive flexibility, an important brain function related to behavioral adaptation to variations in the environment. Abnormalities in cognitive functions are related to changes in synaptic connectivity in the prefrontal cortex (PFC), and altered levels of synaptic proteins. We investigated if individual variations in the expression of a network of genes co-expressed with the synaptic protein VAMP1 in the prefrontal cortex moderate the effect of early environmental quality on the performance of children in cognitive flexibility tasks. Genes overexpressed in early childhood and co-expressed with the VAMP1 gene in the PFC were selected for study. SNPs from these genes (post-clumping) were compiled in an expression-based polygenic score (PFC-ePRS-VAMP1). We evaluated cognitive performance of the 4 years-old children in two cohorts using similar cognitive flexibility tasks. In the first cohort (MAVAN) we utilized two CANTAB tasks: (a) the Intra-/Extra-dimensional Set Shift (IED) task, and (b) the Spatial Working Memory (SWM) task. In the second cohort, GUSTO, we used the Dimensional Change Card Sort (DCCS) task. The results show that in 4 years-old children, the PFC-ePRS-VAMP1 network moderates responsiveness to the effects of early adversities on the performance in attentional flexibility tests. The same result was observed for a spatial working memory task. Compared to attentional flexibility, reversal learning showed opposite effects of the environment, as moderated by the ePRS. A parallel ICA analysis was performed to identify relationships between whole-brain voxel based gray matter density and SNPs that comprise the PFC-ePRS-VAMP1. The early environment predicts differences in gray matter content in regions such as prefrontal and temporal cortices, significantly associated with a genetic component related to Wnt signaling pathways. Our data suggest that a network of genes co-expressed with VAMP1 in the PFC moderates the influence of early environment on cognitive function in children.

Improving the Utility of Polygenic Risk Scores as a Biomarker for Alzheimer's Disease

The treatment of complex and multifactorial diseases constitutes a big challenge in day-to-day clinical practice. As many parameters influence clinical phenotypes, accurate diagnosis and prompt therapeutic management is often difficult. Significant research and investment focuses on state-of-the-art genomic and metagenomic analyses in the burgeoning field of Precision (or Personalized) Medicine with genome-wide-association-studies (GWAS) helping in this direction by linking patient genotypes at specific polymorphic sites (single-nucleotide polymorphisms, SNPs) to the specific phenotype. The generation of polygenic risk scores (PRSs) is a relatively novel statistical method that associates the collective genotypes at many of a person’s SNPs to a trait or disease. As GWAS sample sizes increase, PRSs may become a powerful tool for prevention, early diagnosis and treatment. However, the complexity and multidimensionality of genetic and environmental contributions to phenotypes continue to pose significant challenges for the clinical, broad-scale use of PRSs. To improve the value of PRS measures, we propose a novel pipeline which might better utilize GWAS results and improve the utility of PRS when applied to Alzheimer’s Disease (AD), as a paradigm of multifactorial disease with existing large GWAS datasets that have not yet achieved significant clinical impact. We propose a refined approach for the construction of AD PRS improved by (1), taking into consideration the genetic loci where the SNPs are located, (2) evaluating the post-translational impact of SNPs on coding and non-coding regions by focusing on overlap with open chromatin data and SNPs that are expression quantitative trait loci (QTLs), and (3) scoring and annotating the severity of the associated clinical phenotype into the PRS. Open chromatin and eQTL data need to be carefully selected based on tissue/cell type of origin (e.g., brain, excitatory neurons). Applying such filters to traditional PRS on GWAS studies of complex diseases like AD, can produce a set of SNPs weighted according to our algorithm and a more useful PRS. Our proposed methodology may pave the way for new applications of genomic machine and deep learning pipelines to GWAS datasets in an effort to identify novel clinically useful genetic biomarkers for complex diseases like AD.

Novel Monoclonal Antibodies Against Mouse C1q: Characterisation and Development of a Quantitative ELISA for Mouse C1q

Recent studies have identified roles for complement in synaptic pruning, both physiological during development and pathological in Alzheimer's disease (AD). These reports suggest that C1q initiates complement activation on synapses and C3 fragments then tag them for removal by microglia. There is an urgent need to characterise these processes in rodent AD models; this requires the development of reagents and methods for detection and quantification of rodent C1q in fluids and pathological tissues. These will enable better evaluation of the role of C1q in disease and its value as disease biomarker. We describe the generation in C1q-deficient mice of novel monoclonal antibodies against mouse and rat C1q that enabled development of a sensitive, specific, and quantitative ELISA for mouse and rat C1q capable of measuring C1q in biological fluids and tissue extracts. Serum C1q levels were measured in wild-type (WT), C1q knockout (KO), C3 KO, C7 KO, Crry KO, and 3xTg and APP^NL-G-F AD model mice through ageing. C1q levels significantly decreased in WT, APP^NL-G-F, and C7 KO mice with ageing. C1q levels were reduced in APP^NL-G-F compared to WT at all ages and in 3xTg at 12 months; C3 KO and C7 KO, but not Crry KO mice, also demonstrated significantly lower C1q levels compared to matched WT. In brain homogenates, C1q levels increased with age in both WT and APP^NL-G-F mice. This robust and adaptable assay for quantification of mouse and rat C1q provides a vital tool for investigating the expression of C1q in rodent models of AD and other complement-driven pathologies.

The Impact of Complement Genes on the Risk of Late-Onset Alzheimer's Disease

Late-onset Alzheimer's disease (LOAD), the most common cause of dementia, and a huge global health challenge, is a neurodegenerative disease of uncertain aetiology. To deliver effective diagnostics and therapeutics, understanding the molecular basis of the disease is essential. Contemporary large genome-wide association studies (GWAS) have identified over seventy novel genetic susceptibility loci for LOAD. Most are implicated in microglial or inflammatory pathways, bringing inflammation to the fore as a candidate pathological pathway. Among the most significant GWAS hits are three complement genes: CLU, encoding the fluid-phase complement inhibitor clusterin; CR1 encoding complement receptor 1 (CR1); and recently, C1S encoding the complement enzyme C1s. Complement activation is a critical driver of inflammation; changes in complement genes may impact risk by altering the inflammatory status in the brain. To assess complement gene association with LOAD risk, we manually created a comprehensive complement gene list and tested these in gene-set analysis with LOAD summary statistics. We confirmed associations of CLU and CR1 genes with LOAD but showed no significant associations for the complement gene-set when excluding CLU and CR1. No significant association with other complement genes, including C1S, was seen in the IGAP dataset; however, these may emerge from larger datasets.

Clusterin and Its Role in Insulin Resistance and the Cardiometabolic Syndrome

The cardiometabolic syndrome involves a clustering of metabolic and cardiovascular factors which increase the risk of patients developing both Type 2 Diabetes Mellitus and cardio/cerebrovascular disease. Although the mechanistic underpinnings of this link remain uncertain, key factors include insulin resistance, excess visceral adiposity, atherogenic dyslipidemia, and endothelial dysfunction. Of these, a state of resistance to insulin action in overweight/obese patients appears to be central to the pathophysiologic process. Given the increasing prevalence of obesity-related Type 2 Diabetes, coupled with the fact that cardiovascular disease is the number one cause of mortality in this patient population, a more thorough understanding of the cardiometabolic syndrome and potential options to mitigate its risk is imperative. Inherent in the pathogenesis of insulin resistance is an underlying state of chronic inflammation, at least partly in response to excess adiposity. Within obese adipose tissue, an immunomodulatory shift occurs, involving a preponderance of pro-inflammatory immune cells and cytokines/adipokines, along with antigen presentation by adipocytes. Therefore, various adipokines differentially expressed by obese adipocytes may have a significant effect on cardiometabolism. Clusterin is a molecular chaperone that is widely produced by many tissues throughout the body, but is also preferentially overexpressed by obese compared lean adipocytes and relates strongly to multiple components of the cardiometabolic syndrome. Herein, we summarize the known and potential roles of circulating and adipocyte-specific clusterin in cardiometabolism and discuss potential further investigations to determine if clusterin is a viable target to attenuate both metabolic and cardiovascular disease.

The association between C-reactive protein, mood disorder, and cognitive function in UK Biobank

Background

Systemic inflammation has been linked with mood disorder and cognitive impairment. The extent of this relationship remains uncertain, with the effects of serum inflammatory biomarkers compared to genetic predisposition toward inflammation yet to be clearly established.

Methods

We investigated the magnitude of associations between C-reactive protein (CRP) measures, lifetime history of bipolar disorder or major depression, and cognitive function (reaction time and visuospatial memory) in 84,268 UK Biobank participants. CRP was measured in serum and a polygenic risk score for CRP was calculated, based on a published genome-wide association study. Multiple regression models adjusted for sociodemographic and clinical confounders.

Results

Increased serum CRP was significantly associated with mood disorder history (Kruskal–Wallis H = 196.06, p < 0.001, η² = 0.002) but increased polygenic risk for CRP was not (F = 0.668, p = 0.648, η² < 0.001). Compared to the lowest quintile, the highest serum CRP quintile was significantly associated with both negative and positive differences in cognitive performance (fully adjusted models: reaction time B = −0.030, 95% CI = −0.052, −0.008; visuospatial memory B = 0.066, 95% CI = 0.042, 0.089). More severe mood disorder categories were significantly associated with worse cognitive performance and this was not moderated by serum or genetic CRP level.

Conclusions

In this large cohort study, we found that measured inflammation was associated with mood disorder history, but genetic predisposition to inflammation was not. The association between mood disorder and worse cognitive performance was very small and did not vary by CRP level. The inconsistent relationship between CRP measures and cognitive performance warrants further study.

Polygenic Score Models for Alzheimer's Disease: From Research to Clinical Applications

The high prevalence of Alzheimer's disease (AD) among the elderly population and its lack of effective treatments make this disease a critical threat to human health. Recent epidemiological and genetics studies have revealed the polygenic nature of the disease, which is possibly explainable by a polygenic score model that considers multiple genetic risks. Here, we systemically review the rationale and methods used to construct polygenic score models for studying AD. We also discuss the associations of polygenic risk scores (PRSs) with clinical outcomes, brain imaging findings, and biochemical biomarkers from both the brain and peripheral system. Finally, we discuss the possibility of incorporating polygenic score models into research and clinical practice along with potential challenges.

A multiomics approach to heterogeneity in Alzheimer's disease: focused review and roadmap

Aetiological and clinical heterogeneity is increasingly recognized as a common characteristic of Alzheimer's disease and related dementias. This heterogeneity complicates diagnosis, treatment, and the design and testing of new drugs. An important line of research is discovery of multimodal biomarkers that will facilitate the targeting of subpopulations with homogeneous pathophysiological signatures. High-throughput 'omics' are unbiased data-driven techniques that probe the complex aetiology of Alzheimer's disease from multiple levels (e.g. network, cellular, and molecular) and thereby account for pathophysiological heterogeneity in clinical populations. This review focuses on data reduction analyses that identify complementary disease-relevant perturbations for three omics techniques: neuroimaging-based subtypes, metabolomics-derived metabolite panels, and genomics-related polygenic risk scores. Neuroimaging can track accrued neurodegeneration and other sources of network impairments, metabolomics provides a global small-molecule snapshot that is sensitive to ongoing pathological processes, and genomics characterizes relatively invariant genetic risk factors representing key pathways associated with Alzheimer's disease. Following this focused review, we present a roadmap for assembling these multiomics measurements into a diagnostic tool highly predictive of individual clinical trajectories, to further the goal of personalized medicine in Alzheimer's disease.

The good, the bad, and the opportunities of the complement system in neurodegenerative disease

The complement cascade is a critical effector mechanism of the innate immune system that contributes to the rapid clearance of pathogens and dead or dying cells, as well as contributing to the extent and limit of the inflammatory immune response. In addition, some of the early components of this cascade have been clearly shown to play a beneficial role in synapse elimination during the development of the nervous system, although excessive complement-mediated synaptic pruning in the adult or injured brain may be detrimental in multiple neurogenerative disorders. While many of these later studies have been in mouse models, observations consistent with this notion have been reported in human postmortem examination of brain tissue. Increasing awareness of distinct roles of C1q, the initial recognition component of the classical complement pathway, that are independent of the rest of the complement cascade, as well as the relationship with other signaling pathways of inflammation (in the periphery as well as the central nervous system), highlights the need for a thorough understanding of these molecular entities and pathways to facilitate successful therapeutic design, including target identification, disease stage for treatment, and delivery in specific neurologic disorders. Here, we review the evidence for both beneficial and detrimental effects of complement components and activation products in multiple neurodegenerative disorders. Evidence for requisite co-factors for the diverse consequences are reviewed, as well as the recent studies that support the possibility of successful pharmacological approaches to suppress excessive and detrimental complement-mediated chronic inflammation, while preserving beneficial effects of complement components, to slow the progression of neurodegenerative disease.

The Differential Influence of Immune, Endocytotic, and Lipid Metabolism Genes on Amyloid Deposition and Neurodegeneration in Subjects at Risk of Alzheimer's Disease

BACKGROUND

Over 20 single-nucleotide polymorphisms (SNPs) are associated with increased risk of Alzheimer's disease (AD). We categorized these loci into immunity, lipid metabolism, and endocytosis pathways, and associated the polygenic risk scores (PRS) calculated, with AD biomarkers in mild cognitive impairment (MCI) subjects.

OBJECTIVE

The aim of this study was to identify associations between pathway-specific PRS and AD biomarkers in patients with MCI and healthy controls.

METHODS

AD biomarkers ([18F]Florbetapir-PET SUVR, FDG-PET SUVR, hippocampal volume, CSF tau and amyloid-β levels) and neurocognitive tests scores were obtained in 258 healthy controls and 451 MCI subjects from the ADNI dataset at baseline and at 24-month follow up. Pathway-related (immunity, lipid metabolism, and endocytosis) and total polygenic risk scores were calculated from 20 SNPs. Multiple linear regression analysis was used to test predictive value of the polygenic risk scores over longitudinal biomarker and cognitive changes.

RESULTS

Higher immune risk score was associated with worse cognitive measures and reduced glucose metabolism. Higher lipid risk score was associated with increased amyloid deposition and cortical hypometabolism. Total, immune, and lipid scores were associated with significant changes in cognitive measures, amyloid deposition, and brain metabolism.

CONCLUSION

Polygenic risk scores highlights the influence of specific genes on amyloid-dependent and independent pathways; and these pathways could be differentially influenced by lipid and immune scores respectively.

Neuroprotective versus Neuroinflammatory Roles of Complement: From Development to Disease

Complement proteins are ancient components of innate immunity that have emerged as crucial regulators of neural networks. We discuss these roles in the context of the CNS development, acute CNS viral infections, and post-infectious and noninfectious CNS disorders, with an emphasis on microglia-mediated loss of synapses. Despite extensive examples that implicate classical complement proteins and their receptors in CNS dysfunction, recent data suggest that they exert neuroprotective roles in CNS homeostasis through continued refinement of synaptic connections. Thorough understanding of the mechanisms involved in these processes may lead to novel targets for the treatment of CNS diseases involving aberrant complement-mediated synapse loss.

Alzheimer's disease: from basic science to precision medicine approach

Alzheimer’s disease (AD) is the most common form of dementia in the elderly. Together with cerebral amyloid accumulation, several factors contribute to AD pathology including vascular alterations, systemic inflammation, genetic/epigenetic status and mitochondrial dysfunction. Much is now being devoted to neuroinflammation. However, anti-inflammatory drugs as numerous other therapies, mainly targeted on β-amyloid, have failed to show efficacious effects in AD. Timing, proper selection of patients, and the need for a multitarget approach appear to be the main weak points of current therapeutic efforts. The efficacy of a treatment could be better evaluate if efficient biomarkers are available. We propose here the application of precision medicine principles in AD to simultaneously verify the efficacy of a treatment and the reliability of specific biomarkers according to individually tailored biomarker-guided targeted therapies. People at risk of developing AD or in the very early phase of the disease should be stratified according to: (1) neuropsychological tests; (2) apolipoprotein E (ApoE) genotyping; (3) biochemical analysis of plasma and cerebrospinal fluid (CSF); (4) MRI and positron emission tomography and (5) assessment of their inflammatory profile by an integration of various genetic and biochemical parameters in plasma, CSF and an analysis of microbiota composition. The selected population should be treated with antiamyloidogenic and anti-inflammatory drugs in randomised, longitudinal, placebo-controlled studies using ad hoc profiles (eg, vascular profile, mitochondrial profile, etc…) If these criteria are adopted widely and the results shared, it may be possible to rapidly develop innovative and personalised drug treatment protocols with more realistic chances of being efficacious.

Clusterin as a Potential Biomarker of Obesity-Related Alzheimer's Disease Risk

Over 35% of the adult US population is obese. In turn, excess adiposity increases the risk of multiple complications including type 2 diabetes (T2D), insulin resistance, and cardiovascular disease; yet, obesity also independently heightens risk of Alzheimer's Disease (AD), even after adjusting for other important confounding risk factors including blood pressure, sociodemographics, cholesterol levels, smoking status, and Apolipoprotein E (ApoE) genotype. Among patients over the age of 65 with dementia, 37% have coexisting diabetes, and an estimated 7.3% of cases of AD are directly attributable to midlife obesity. Clusterin, also known as apolipoprotein J (ApoJ), is a multifunctional glycoprotein that acts as a molecular chaperone, assisting folding of secreted proteins. Clusterin has been implicated in several physiological and pathological states, including AD, metabolic disease, and cardiovascular disease. Despite long-standing interest in elucidating clusterin's relationship with amyloid beta (Aβ) aggregation/clearance and toxicity, significant knowledge gaps still exist. Altered clusterin expression and protein levels have been linked with cognitive and memory function, disrupted central nervous system lipid flux, as well as pathogenic brain structure; and its role in cardiometabolic disease suggests that it may be a link between insulin resistance, dyslipidemia, and AD. Here, we briefly highlight clusterin's relevance to AD by presenting existing evidence linking clusterin to AD and cardiometabolic disease, and discussing its potential utility as a biomarker for AD in the presence of obesity-related metabolic disease.

Hierarchical Structured Sparse Learning for Schizophrenia Identification

Fractional amplitude of low-frequency fluctuation (fALFF) has been widely used for resting-state functional magnetic resonance imaging (rs-fMRI) based schizophrenia (SZ) diagnosis. However, previous studies usually measure the fALFF within low-frequency fluctuation (from 0.01 to 0.08Hz), which cannot fully cover the complex neural activity pattern in the resting-state brain. In addition, existing studies usually ignore the fact that each specific frequency band can delineate the unique spontaneous fluctuations of neural activities in the brain. Accordingly, in this paper, we propose a novel hierarchical structured sparse learning method to sufficiently utilize the specificity and complementary structure information across four different frequency bands (from 0.01Hz to 0.25Hz) for SZ diagnosis. The proposed method can help preserve the partial group structures among multiple frequency bands and the specific characters in each frequency band. We further develop an efficient optimization algorithm to solve the proposed objective function. We validate the efficacy of our proposed method on a real SZ dataset. Also, to demonstrate the generality of the method, we apply our proposed method on a subset of Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Experimental results on both datasets demonstrate that our proposed method achieves promising performance in brain disease classification, compared with several state-of-the-art methods.

From Polygenic Scores to Precision Medicine in Alzheimer's Disease: A Systematic Review

BACKGROUND

Late-onset Alzheimer's disease (AD) is highly heritable. The effect of many common genetic variants, single nucleotide polymorphisms (SNPs), confer risk. Variants are clustered in areas of biology, notably immunity and inflammation, cholesterol metabolism, endocytosis, and ubiquitination. Polygenic scores (PRS), which weight the sum of an individual's risk alleles, have been used to draw inferences about the pathological processes underpinning AD.

OBJECTIVE

This paper aims to systematically review how AD PRS are being used to study a range of outcomes and phenotypes related to neurodegeneration.

METHODS

We searched the literature from July 2008-July 2018 following PRISMA guidelines.

RESULTS

57 studies met criteria. The AD PRS can distinguish AD cases from controls. The ability of AD PRS to predict conversion from mild cognitive impairment (MCI) to AD was less clear. There was strong evidence of association between AD PRS and cognitive impairment. AD PRS were correlated with a number of biological phenotypes associated with AD pathology, such as neuroimaging changes and amyloid and tau measures. Pathway-specific polygenic scores were also associated with AD-related biologically relevant phenotypes.

CONCLUSION

PRS can predict AD effectively and are associated with cognitive impairment. There is also evidence of association between AD PRS and other phenotypes relevant to neurodegeneration. The associations between pathway specific polygenic scores and phenotypic changes may allow us to define the biology of the disease in individuals and indicate who may benefit from specific treatments. Longitudinal cohort studies are required to test the ability of PGS to delineate pathway-specific disease activity.

The Radiogenomics of Late-onset Alzheimer Disease

Radiogenomics, defined as the integrated analysis of radiologic imaging and genetic data, is a well-established tool shown to augment neuroimaging in the clinical diagnosis, prognostication, and scientific study of late-onset Alzheimer disease (LOAD). Early work using candidate single nucleotide polymorphisms (SNPs) identified genetic variation in APOE, BIN1, CLU, and CR1 as key modifiers of brain structure and function using magnetic resonance imaging (MRI). More recently, polygenic risk scores used in conjunction with MRI and positron emission tomography have shown great promise as a risk-stratification tool for clinical trials and care-management decisions. In addition, recent work using multimodal MRI and positron emission tomography as proxies of LOAD progression has identified novel risk variants that are enhancing our understanding of LOAD pathophysiology and progression. Herein, we highlight key studies and trends in the radiogenomics of LOAD over the past two decades and their implications for clinical practice and scientific research.

Microglia - mediated immunity partly contributes to the genetic association between Alzheimer's disease and hippocampal volume

Genome-wide association studies (GWAS) suggest that Alzheimer's disease (AD) is partly explained by a burden of risk alleles (single nucleotide polymorphisms; SNPs) with relatively small effects. However, the mechanisms by which these loci cumulatively confer susceptibility remain largely unknown. Accumulating evidence suggests an association between increased AD risk allele burden (measured via a polygenic risk profile score; AD-RPS) with reduced hippocampal volume (HV) across a number of independent cohorts. These lines of research suggest that the reduced HV may be a causal mechanism of risk in the development of late-onset Alzheimer's disease (AD). However, as RPS assesses broad, cumulative genetic risk, little is known about the biological processes which may explain this observation. Here, we leverage GWAS data from i) 17,008 late onset AD cases & 37,154 controls and ii) hippocampal volume (N = 12,147; N = 9707) to explore putative pathways that may explain this association. We first demonstrate an association between whole genome AD-RPS and HV (PT < 0.5, Z = -2.07, P = 0.038), confirming previous associations. Second, we restrict our analysis to SNPs within AD genes within a microglia mediated immunity network (N_GENES = 56). A microglia AD-RPS was further associated with HV (PT < 0.01; Z = -2.152, P = 0.031). Last, using a competitive, permutation based approach, we show that the common variation within this candidate gene-set is associated with HV, controlling for SNP set-size (P = 0.024). Together, the observations suggest that the relationship between AD and HV is partially explained by genes within an AD-linked microglia mediated immunity network.

Alzheimer's disease polygenic risk score as a predictor of conversion from mild-cognitive impairment

Mild-cognitive impairment (MCI) occurs in up to one-fifth of individuals over the age of 65, with approximately a third of MCI individuals converting to dementia in later life. There is a growing necessity for early identification for those at risk of dementia as pathological processes begin decades before onset of symptoms. A cohort of 122 individuals diagnosed with MCI and followed up for a 36-month period for conversion to late-onset Alzheimer's disease (LOAD) were genotyped on the NeuroChip array along with pathologically confirmed cases of LOAD and cognitively normal controls. Polygenic risk scores (PRS) for each individual were generated using PRSice-2, derived from summary statistics produced from the International Genomics of Alzheimer's Disease Project (IGAP) genome-wide association study. Predictability models for LOAD were developed incorporating the PRS with APOE SNPs (rs7412 and rs429358), age and gender. This model was subsequently applied to the MCI cohort to determine whether it could be used to predict conversion from MCI to LOAD. The PRS model for LOAD using area under the precision-recall curve (AUPRC) calculated a predictability for LOAD of 82.5%. When applied to the MCI cohort predictability for conversion from MCI to LOAD was 61.0%. Increases in average PRS scores across diagnosis group were observed with one-way ANOVA suggesting significant differences in PRS between the groups (p < 0.0001). This analysis suggests that the PRS model for LOAD can be used to identify individuals with MCI at risk of conversion to LOAD.

Inflammatory biomarkers in Alzheimer's disease plasma

Introduction

Plasma biomarkers for Alzheimer's disease (AD) diagnosis/stratification are a “Holy Grail” of AD research and intensively sought; however, there are no well-established plasma markers.

Methods

A hypothesis-led plasma biomarker search was conducted in the context of international multicenter studies. The discovery phase measured 53 inflammatory proteins in elderly control (CTL; 259), mild cognitive impairment (MCI; 199), and AD (262) subjects from AddNeuroMed.

Results

Ten analytes showed significant intergroup differences. Logistic regression identified five (FB, FH, sCR1, MCP-1, eotaxin-1) that, age/APOε4 adjusted, optimally differentiated AD and CTL (AUC: 0.79), and three (sCR1, MCP-1, eotaxin-1) that optimally differentiated AD and MCI (AUC: 0.74). These models replicated in an independent cohort (EMIF; AUC 0.81 and 0.67). Two analytes (FB, FH) plus age predicted MCI progression to AD (AUC: 0.71).

Discussion

Plasma markers of inflammation and complement dysregulation support diagnosis and outcome prediction in AD and MCI. Further replication is needed before clinical translation.

Distinctive Effects of Aerobic and Resistance Exercise Modes on Neurocognitive and Biochemical Changes in Individuals with Mild Cognitive Impairment

Background:

Decreased levels of the neuroprotective growth factors, low-grade inflammation, and reduced neurocognitive functions during aging are associated with neurodegenerative diseases, such as Alzheimer’s disease. Physical exercise modifies these disadvantageous phenomena while a sedentary lifestyle promotes them.

Purpose:

The purposes of the present study included investigating whether both aerobic and resistance exercise produce divergent effects on the neuroprotective growth factors, inflammatory cytokines, and neurocognitive performance, and further exploring whether changes in the levels of these molecular biomarkers are associated with alterations in neurocognitive performance.

Methods:

Fifty-five older adults with amnestic MCI (aMCI) were recruited and randomly assigned to an aerobic exercise (AE) group, a resistance exercise (RE) group, or a control group. The assessment included neurocognitive measures [e.g., behavior and event-related potential (ERP)] during a task-switching paradigm, as well as circulating neuroprotective growth factors (e.g., BDNF, IGF-1, VEGF, and FGF-2) and inflammatory cytokine (e.g., TNF-α, IL-1β, IL-6, IL-8, and IL-15) levels at baseline and after either a 16-week aerobic or resistance exercise intervention program or a control period.

Results:

Aerobic and resistance exercise could effectively partially facilitate neurocognitive performance [e.g., accuracy rates (ARs), reaction times during the heterogeneous condition, global switching cost, and ERP P3 amplitude] when the participants performed the task switching paradigm although the ERP P2 components and P3 latency could not be changed. In terms of the circulating molecular biomarkers, the 16-week exercise interventions did not change some parameters (e.g., leptin, VEGF, FGF-2, IL-1β, IL-6, and IL-8). However, the peripheral serum BDNF level was significantly increased, and the levels of insulin, TNF-α, and IL-15 levels were significantly decreased in the AE group, whereas the RE group showed significantly increased IGF-1 levels and decreased IL-15 levels. The relationships between the changes in neurocognitive performance (AR and P3 amplitudes) and the changes in the levels of neurotrophins (BDNF and IGF-1)/inflammatory cytokines (TNF-α) only approached significance.

Conclusion:

These findings suggested that in older adults with aMCI, not only aerobic but also resistance exercise is effective with regard to increasing neurotrophins, reducing some inflammatory cytokines, and facilitating neurocognitive performance. However, the aerobic and resistance exercise modes likely employed divergent molecular mechanisms on neurocognitive facilitation.

Multi-task exclusive relationship learning for alzheimer's disease progression prediction with longitudinal data

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive impairment of memory and other cognitive functions. Currently, many multi-task learning approaches have been proposed to predict the disease progression at the early stage using longitudinal data, with each task corresponding to a particular time point. However, the underlying association among different time points in disease progression is still under-explored in previous studies. To this end, we propose a multi-task exclusive relationship learning model to automatically capture the intrinsic relationship among tasks at different time points for estimating clinical measures based on longitudinal imaging data. The proposed method can select the most discriminative features for different tasks and also model the intrinsic relatedness among different time points, by utilizing an exclusive lasso regularization and a relationship induced regularization. Specifically, the exclusive lasso regularization enables partial group structure feature selection among the longitudinal data, while the relationship induced regularization efficiently introduces the relationship information from data to guide knowledge transfer. We further develop an efficient optimization algorithm to solve the proposed objective function. Extensive experiments on both synthetic and real datasets demonstrate the effectiveness of our proposed method. In comparison with several state-of-the-art methods, our proposed method can achieve promising performance for cognitive status prediction and also can help discover disease-related biomarkers.

Therapeutic Inhibition of the Complement System in Diseases of the Central Nervous System

The complement system plays critical roles in development, homeostasis, and regeneration in the central nervous system (CNS) throughout life; however, complement dysregulation in the CNS can lead to damage and disease. Complement proteins, regulators, and receptors are widely expressed throughout the CNS and, in many cases, are upregulated in disease. Genetic and epidemiological studies, cerebrospinal fluid (CSF) and plasma biomarker measurements and pathological analysis of post-mortem tissues have all implicated complement in multiple CNS diseases including multiple sclerosis (MS), neuromyelitis optica (NMO), neurotrauma, stroke, amyotrophic lateral sclerosis (ALS), Alzheimer's disease (AD), Parkinson's disease (PD), and Huntington's disease (HD). Given this body of evidence implicating complement in diverse brain diseases, manipulating complement in the brain is an attractive prospect; however, the blood-brain barrier (BBB), critical to protect the brain from potentially harmful agents in the circulation, is also impermeable to current complement-targeting therapeutics, making drug design much more challenging. For example, antibody therapeutics administered systemically are essentially excluded from the brain. Recent protocols have utilized "Trojan horse" techniques to transport therapeutics across the BBB or used osmotic shock or ultrasound to temporarily disrupt the BBB. Most research to date exploring the impact of complement inhibition on CNS diseases has been in animal models, and some of these studies have generated convincing data; for example, in models of MS, NMO, and stroke. There have been a few recent clinical trials of available anti-complement drugs in CNS diseases associated with BBB impairment, for example the use of the anti-C5 monoclonal antibody (mAb) eculizumab in NMO, but for most CNS diseases there have been no human trials of anti-complement therapies. Here we will review the evidence implicating complement in diverse CNS disorders, from acute, such as traumatic brain or spine injury, to chronic, including demyelinating, neuroinflammatory, and neurodegenerative diseases. We will discuss the particular problems of drug access into the CNS and explore ways in which anti-complement therapies might be tailored for CNS disease.

Inflammageing: chronic inflammation in ageing, cardiovascular disease, and frailty

Most older individuals develop inflammageing, a condition characterized by elevated levels of blood inflammatory markers that carries high susceptibility to chronic morbidity, disability, frailty, and premature death. Potential mechanisms of inflammageing include genetic susceptibility, central obesity, increased gut permeability, changes to microbiota composition, cellular senescence, NLRP3 inflammasome activation, oxidative stress caused by dysfunctional mitochondria, immune cell dysregulation, and chronic infections. Inflammageing is a risk factor for cardiovascular diseases (CVDs), and clinical trials suggest that this association is causal. Inflammageing is also a risk factor for chronic kidney disease, diabetes mellitus, cancer, depression, dementia, and sarcopenia, but whether modulating inflammation beneficially affects the clinical course of non-CVD health problems is controversial. This uncertainty is an important issue to address because older patients with CVD are often affected by multimorbidity and frailty - which affect clinical manifestations, prognosis, and response to treatment - and are associated with inflammation by mechanisms similar to those in CVD. The hypothesis that inflammation affects CVD, multimorbidity, and frailty by inhibiting growth factors, increasing catabolism, and interfering with homeostatic signalling is supported by mechanistic studies but requires confirmation in humans. Whether early modulation of inflammageing prevents or delays the onset of cardiovascular frailty should be tested in clinical trials.

Complement in the pathogenesis of Alzheimer's disease

The emergence of complement as an important player in normal brain development and pathological remodelling has come as a major surprise to most scientists working in neuroscience and almost all those working in complement. That a system, evolved to protect the host against infection, should have these unanticipated roles has forced a rethink about what complement might be doing in the brain in health and disease, where it is coming from, and whether we can, or indeed should, manipulate complement in the brain to improve function or restore homeostasis. Complement has been implicated in diverse neurological and neuropsychiatric diseases well reviewed elsewhere, from depression through epilepsy to demyelination and dementia, in most complement drives inflammation to exacerbate the disease. Here, I will focus on just one disease, the most common cause of dementia, Alzheimer's disease. I will briefly review the current understanding of what complement does in the normal brain, noting, in particular, the many gaps in understanding, then describe how complement may influence the genesis and progression of pathology in Alzheimer's disease. Finally, I will discuss the problems and pitfalls of therapeutic inhibition of complement in the Alzheimer brain.

Effects of freezer storage time on levels of complement biomarkers

BACKGROUND

There is uncertainty regarding how stable complement analytes are during long-term storage at - 80 °C. As part of our work program we have measured 17 complement biomarkers (C1q, C1 inhibitor, C3, C3a, iC3b, C4, C5, C9, FB, FD, FH, FI, TCC, Bb, sCR1, sCR2, Clusterin) and the benchmark inflammatory marker C-reactive protein (CRP) in a large set of plasma samples (n = 720) that had been collected, processed and subsequently stored at - 80 °C over a period of 6.6-10.6 years, prior to laboratory analysis. The biomarkers were measured using solid-phase enzyme immunoassays with a combination of multiplex assays using the MesoScale Discovery Platform and single-plex enzyme-linked immunosorbent assays (ELISAs). As part of a post hoc analysis of extrinsic factors (co-variables) affecting the analyses we investigated the impact of freezer storage time on the values obtained for each complement analyte.

RESULTS

With the exception of five analytes (C4, C9, sCR2, clusterin and CRP), storage time was significantly correlated with measured plasma concentrations. For ten analytes: C3, FI, FB, FD, C5, sCR1, C3a, iC3b, Bb and TCC, storage time was positively correlated with concentration and for three analytes: FH, C1q, and C1 inhibitor, storage time was negatively correlated with concentration.

CONCLUSIONS

The results suggest that information on storage time should be regarded as an important co-variable and taken into consideration when analysing data to look for associations of complement biomarker levels and disease or other outcomes.

Polygenic risk score in postmortem diagnosed sporadic early-onset Alzheimer's disease

Sporadic early-onset Alzheimer's disease (sEOAD) exhibits the symptoms of late-onset Alzheimer's disease but lacks the familial aspect of the early-onset familial form. The genetics of Alzheimer's disease (AD) identifies APOEε4 to be the greatest risk factor; however, it is a complex disease involving both environmental risk factors and multiple genetic loci. Polygenic risk scores (PRSs) accumulate the total risk of a phenotype in an individual based on variants present in their genome. We determined whether sEOAD cases had a higher PRS compared to controls. A cohort of sEOAD cases was genotyped on the NeuroX array, and PRSs were generated using PRSice. The target data set consisted of 408 sEOAD cases and 436 controls. The base data set was collated by the International Genomics of Alzheimer's Project consortium, with association data from 17,008 late-onset Alzheimer's disease cases and 37,154 controls, which can be used for identifying sEOAD cases due to having shared phenotype. PRSs were generated using all common single nucleotide polymorphisms between the base and target data set, PRS were also generated using only single nucleotide polymorphisms within a 500 kb region surrounding the APOE gene. Sex and number of APOE ε2 or ε4 alleles were used as variables for logistic regression and combined with PRS. The results show that PRS is higher on average in sEOAD cases than controls, although there is still overlap among the whole cohort. Predictive ability of identifying cases and controls using PRSice was calculated with 72.9% accuracy, greater than the APOE locus alone (65.2%). Predictive ability was further improved with logistic regression, identifying cases and controls with 75.5% accuracy.

Serping1/C1 Inhibitor Affects Cortical Development in a Cell Autonomous and Non-cell Autonomous Manner

Current knowledge regarding regulation of radial neuronal migration is mainly focused on intracellular molecules. Our unbiased screen aimed at identification of non-cell autonomous mechanisms involved in this process detected differential expression of Serping1 or C1 inhibitor, which is known to inhibit the initiation of the complement cascade. The complement cascade is composed of three pathways; the classical, lectin, and the alternative pathway; the first two are inhibited by C1 inhibitor, and all three converge at the level of C3. Knockdown or knockout of Serping1 affected neuronal stem cell proliferation and impaired neuronal migration in mice. Knockdown of Serping1 by in utero electroporation resulted in a migration delay of the electroporated cells as well as their neighboring cells demonstrating a non-cell autonomous effect. Cellular polarity was also affected. Most importantly, expression of protein components mimicking cleaved C3 rescued the knockdown of Serping1, indicating complement pathway functionality. Furthermore, we propose that this activity is mediated mainly via the complement peptide C5a receptors. Whereas addition of a selective C3a receptor agonist was minimally effective, the addition of a dual C3aR/C5a receptor agonist significantly rescued Serping1 knockdown-mediated neuronal migration defects. Our findings suggest that modulating Serping1 levels in the developing brain may affect the complement pathway in a complex way. Collectively, our findings demonstrate an unorthodox activity for the complement pathway during brain development.

Few serum proteins mediate APOE's association with dementia

The latent variable "δ" (for "dementia") appears to be uniquely responsible for the dementing aspects of cognitive impairment. Age, depression, gender and the apolipoprotein E (APOE) e4 allele are independently associated with δ. In this analysis, we explore serum proteins as potential mediators of APOE's specific association with δ in a large, ethnically diverse longitudinal cohort, the Texas Alzheimer's Research and Care Consortium (TARCC). APOE was associated only with C-Reactive Protein (CRP), Adiponectin (APN) and Amphiregulin (AREG), although the latter two's associations did not survive Bonferroni correction for multiple comparisons. All three proteins were associated with δ and had weak potential mediation effects on APOE's association with that construct. Our findings suggest that APOE's association with cognitive performance is specific to δ and partially mediated by serum inflammatory proteins. The majority of APOE's significant unadjusted effect on δ is unexplained. It may instead arise from direct central nervous system effects, possibly on native intelligence. If so, then APOE may exert a life-long influence over δ and therefore all-cause dementia risk.