Complement biomarkers as predictors of disease progression in Alzheimer's disease

There is a critical unmet need for reliable markers of disease and disease course in mild cognitive impairment (MCI) and early Alzheimer’s disease (AD). The growing appreciation of the importance of inflammation in early AD has focused attention on inflammatory biomarkers in cerebrospinal fluid or plasma; however, non-specific inflammation markers have disappointed to date. We have adopted a targeted approach, centered on an inflammatory pathway already implicated in the disease. Complement, a core system in innate immune defense and potent driver of inflammation, has been implicated in pathogenesis of AD based on a confluence of genetic, histochemical, and model data. Numerous studies have suggested that measurement of individual complement proteins or activation products in cerebrospinal fluid or plasma is useful in diagnosis, prediction, or stratification, but few have been replicated. Here we apply a novel multiplex assay to measure five complement proteins and four activation products in plasma from donors with MCI, AD, and controls. Only one complement analyte, clusterin, differed significantly between control and AD plasma (controls, 295 mg/l; AD, 388 mg/l: p < 10- 5). A model combining clusterin with relevant co-variables was highly predictive of disease. Three analytes (clusterin, factor I, terminal complement complex) were significantly different between MCI individuals who had converted to dementia one year later compared to non-converters; a model combining these three analytes with informative co-variables was highly predictive of conversion. The data confirm the relevance of complement biomarkers in MCI and AD and build the case for using multi-parameter models for disease prediction and stratification

Dickkopf-1 Overexpression in vitro Nominates Candidate Blood Biomarkers Relating to Alzheimer's Disease Pathology

Previous studies suggest that Dickkopf-1 (DKK1), an inhibitor of Wnt signaling, plays a role in amyloid-induced toxicity and hence Alzheimer's disease (AD). However, the effect of DKK1 expression on protein expression, and whether such proteins are altered in disease, is unknown. We aim to test whether DKK1 induced protein signature obtained in vitro were associated with markers of AD pathology as used in the amyloid/tau/neurodegeneration (ATN) framework as well as with clinical outcomes. We first overexpressed DKK1 in HEK293A cells and quantified 1,128 proteins in cell lysates using aptamer capture arrays (SomaScan) to obtain a protein signature induced by DKK1. We then used the same assay to measure the DKK1-signature proteins in human plasma in two large cohorts, EMIF (n = 785) and ANM (n = 677). We identified a 100-protein signature induced by DKK1 in vitro. Subsets of proteins, along with age and apolipoprotein E ɛ 4 genotype distinguished amyloid pathology (A + T-N-, A+T+N-, A+T-N+, and A+T+N+) from no AD pathology (A-T-N-) with an area under the curve of 0.72, 0.81, 0.88, and 0.85, respectively. Furthermore, we found that some signature proteins (e.g., Complement C3 and albumin) were associated with cognitive score and AD diagnosis in both cohorts. Our results add further evidence for a role of DKK regulation of Wnt signaling in AD and suggest that DKK1 induced signature proteins obtained in vitro could reflect theATNframework as well as predict disease severity and progression in vivo

Plasma Protein Biomarkers for the Prediction of CSF Amyloid and Tau and [18F]-Flutemetamol PET Scan Result

Background: Blood biomarkers may aid in recruitment to clinical trials of Alzheimer's disease (AD) modifying therapeutics by triaging potential trials participants for amyloid positron emission tomography (PET) or cerebrospinal fluid (CSF) A\u3b2 and tau tests. Objective: To discover a plasma proteomic signature associated with CSF and PET measures of AD pathology. Methods: Liquid chromatography-tandem mass spectrometry (LC-MS/MS) based proteomics were performed in plasma from participants with subjective cognitive decline (SCD), mild cognitive impairment (MCI), and AD, recruited to the Amsterdam Dementia Cohort, stratified by CSF Tau/A\u3b242 (n = 50). Technical replication and independent validation were performed by immunoassay in plasma from SCD, MCI, and AD participants recruited to the Amsterdam Dementia Cohort with CSF measures (n = 100), MCI participants enrolled in the GE067-005 study with [18F]-Flutemetamol PET amyloid measures (n = 173), and AD, MCI and cognitively healthy participants from the EMIF 500 study with CSF A\u3b242 measurements (n = 494). Results: 25 discovery proteins were nominally associated with CSF Tau/A\u3b242 (P < 0.05) with associations of ficolin-2 (FCN2), apolipoprotein C-IV and fibrinogen \u3b2 chain confirmed by immunoassay (P < 0.05). In the GE067-005 cohort, FCN2 was nominally associated with PET amyloid (P < 0.05) replicating the association with CSF Tau/A\u3b242. There were nominally significant associations of complement component 3 with PET amyloid, and apolipoprotein(a), apolipoprotein A-I, ceruloplasmin, and PPY with MCI conversion to AD (all P < 0.05). In the EMIF 500 cohort FCN2 was trending toward a significant relationship with CSF A\u3b242 (P 48 0.05), while both A1AT and clusterin were nominally significantly associated with CSF A\u3b242 (both P < 0.05). Conclusion: Associations of plasma proteins with multiple measures of AD pathology and progression are demonstrated. To our knowledge this is the first study to report an association of FCN2 with AD pathology. Further testing of the proteins in larger independent cohorts will be important

COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multinational observational study

Background: The ISARIC prospective multinational observational study is the largest cohort of hospitalized patients with COVID-19. We present relationships of age, sex, and nationality to presenting symptoms. Methods: International, prospective observational study of 60 109 hospitalized symptomatic patients with laboratory-confirmed COVID-19 recruited from 43 countries between 30 January and 3 August 2020. Logistic regression was performed to evaluate relationships of age and sex to published COVID-19 case definitions and the most commonly reported symptoms. Results: ‘Typical’ symptoms of fever (69%), cough (68%) and shortness of breath (66%) were the most commonly reported. 92% of patients experienced at least one of these. Prevalence of typical symptoms was greatest in 30- to 60-year-olds (respectively 80, 79, 69%; at least one 95%). They were reported less frequently in children (≤ 18 years: 69, 48, 23; 85%), older adults (≥ 70 years: 61, 62, 65; 90%), and women (66, 66, 64; 90%; vs. men 71, 70, 67; 93%, each P &lt; 0.001). The most common atypical presentations under 60 years of age were nausea and vomiting and abdominal pain, and over 60 years was confusion. Regression models showed significant differences in symptoms with sex, age and country. Interpretation: This international collaboration has allowed us to report reliable symptom data from the largest cohort of patients admitted to hospital with COVID-19. Adults over 60 and children admitted to hospital with COVID-19 are less likely to present with typical symptoms. Nausea and vomiting are common atypical presentations under 30 years. Confusion is a frequent atypical presentation of COVID-19 in adults over 60 years. Women are less likely to experience typical symptoms than men

Biomarkers for Parkinsonâs disease and Alzheimerâs disease

Alzheimerâs Disease (AD) and Parkinsonâs Disease (PD) represent the two most prevalent neurodegenerative diseases in the world, affecting 30 million and 5 million people, respectively. As populations age, the global burden of AD and PD will increase, resulting in significant societal and economic implications. By 2050, it is estimated that 1 in 85 people will have AD. Biomarkers, surrogate indicators of physiological or pathophysiological states, can be used to guide the diagnosis of diseases, evaluate risk or prognosis, and track therapeutic interventions. In neurodegenerative diseases such as PD and AD, biomarkers can play a crucial role by facilitating earlier diagnosis and the screening of individuals into clinical trials. Given its function to track various disease states, biomarkers will be fundamentally important as we develop and assess disease-modifying therapies and preventative strategies. (3) The advent of high-throughput sequencing technologies and advancements in omicsâ genomics, proteomics, and transcriptomicsâhas enabled the exploration of biomarkers for disease with unprecedented scale. Investigators can now move beyond candidate biomarker discovery approaches based upon a priori hypotheses. This presents an opportunity to utilize biomarkers to develop more sensitive and specific diagnostics and identify molecular targets that may have been overlooked through candidate approaches. Researchers can also use biomarkers to better define subgroups within PD or AD. These endophenotypes can help characterize the different etiologies that contribute to the development of the diseases, reveal distinct subpopulations within disease categories, and thereby uncover potential therapeutic targets. The work presented here leverages these new advancements in high variable capture approaches, specifically proteomics, to identify novel biomarkers and signatures of disease states for PD and AD. My thesis also demonstrates how multivariate analytical tools can be used to interrogate and validate distinguishing signatures found between disease and control states. In the first chapter, I will review the pathophysiology and clinical management of AD and PD. I will also review the AD and PD biomarkers and the various proteomic and computational approaches that enable biomarker discovery at scale. In the second chapter, I introduce a novel biomarker discovery approach that combines the advantages of hypothesis-driven and high variable capture approaches. The third chapter explores biomarkers for PD, using data from plasma and brain. In the fourth chapter, I identify proteins correlated across CSF and plasma and demonstrate how this data may be used in biomarker identification. In summary, I have identified novel biomarker signatures for the diagnosis and prognosis of PD and AD using high variable data capture methods and multivariate computational approaches. </p

Biomarkers for Parkinson’s disease and Alzheimer’s disease

Alzheimer’s Disease (AD) and Parkinson’s Disease (PD) represent the two most prevalent neurodegenerative diseases in the world, affecting 30 million and 5 million people, respectively. As populations age, the global burden of AD and PD will increase, resulting in significant societal and economic implications. By 2050, it is estimated that 1 in 85 people will have AD. Biomarkers, surrogate indicators of physiological or pathophysiological states, can be used to guide the diagnosis of diseases, evaluate risk or prognosis, and track therapeutic interventions. In neurodegenerative diseases such as PD and AD, biomarkers can play a crucial role by facilitating earlier diagnosis and the screening of individuals into clinical trials. Given its function to track various disease states, biomarkers will be fundamentally important as we develop and assess disease-modifying therapies and preventative strategies. (3) The advent of high-throughput sequencing technologies and advancements in omics— genomics, proteomics, and transcriptomics—has enabled the exploration of biomarkers for disease with unprecedented scale. Investigators can now move beyond candidate biomarker discovery approaches based upon a priori hypotheses. This presents an opportunity to utilize biomarkers to develop more sensitive and specific diagnostics and identify molecular targets that may have been overlooked through candidate approaches. Researchers can also use biomarkers to better define subgroups within PD or AD. These endophenotypes can help characterize the different etiologies that contribute to the development of the diseases, reveal distinct subpopulations within disease categories, and thereby uncover potential therapeutic targets. The work presented here leverages these new advancements in high variable capture approaches, specifically proteomics, to identify novel biomarkers and signatures of disease states for PD and AD. My thesis also demonstrates how multivariate analytical tools can be used to interrogate and validate distinguishing signatures found between disease and control states. In the first chapter, I will review the pathophysiology and clinical management of AD and PD. I will also review the AD and PD biomarkers and the various proteomic and computational approaches that enable biomarker discovery at scale. In the second chapter, I introduce a novel biomarker discovery approach that combines the advantages of hypothesis-driven and high variable capture approaches. The third chapter explores biomarkers for PD, using data from plasma and brain. In the fourth chapter, I identify proteins correlated across CSF and plasma and demonstrate how this data may be used in biomarker identification. In summary, I have identified novel biomarker signatures for the diagnosis and prognosis of PD and AD using high variable data capture methods and multivariate computational approaches. </p

The medial prefrontal cortex is crucial for the maintenance of persistent licking and the expression of incentive contrast

We examined the role of the medial prefrontal cortex (mPFC) in reward processing and the control of consummatory behavior. Rats were trained in an operant licking procedure in which they received alternating access to solutions with relatively high and low levels of sucrose (20% and 4%, w/v). Each level of sucrose was available for fixed intervals of 30 seconds over 30 minute test sessions. Over several days of training, rats came to lick persistently when the high level of sucrose was available and suppressed licking when the low level of sucrose was available. Pharmacological inactivations of the mPFC, specifically the rostral part of the prelimbic area, greatly reduced intake of the higher value fluid and only slightly increased intake of the lower value fluid. In addition, the inactivations altered within-session patterns and microstructural measures of licking. Rats licked equally for the high and low levels of sucrose at the beginning of the test sessions and relearned to reduce intake of the low value fluid over the test sessions. Durations of licking bouts (clusters of licks with inter-lick intervals <0.5 sec) were reduced for the high value fluid and there were many more brief licking bouts (<1 sec) when the low value fluid was available. These effects were verified using an alternative approach (optogenetic silencing using archaerhodopsin) and were distinct from inactivation of the ventral striatum, which simply increased overall intake. Our findings suggest that the mPFC is crucial for the maintenance of persistent licking and the expression of learned feeding strategies

Predicting progression to Alzheimer's disease with human hippocampal progenitors exposed to serum

Adult hippocampal neurogenesis is important for learning and memory and is altered early in Alzheimer's disease. As hippocampal neurogenesis is modulated by the circulatory systemic environment, evaluating a proxy of how hippocampal neurogenesis is affected by the systemic milieu could serve as an early biomarker for Alzheimer's disease progression. Here, we used an in vitro assay to model the impact of systemic environment on hippocampal neurogenesis. A human hippocampal progenitor cell line was treated with longitudinal serum samples from individuals with mild cognitive impairment, who either progressed to Alzheimer's disease or remained cognitively stable. Mild cognitive impairment to Alzheimer's disease progression was characterized most prominently with decreased proliferation, increased cell death and increased neurogenesis. A subset of 'baseline' cellular readouts together with education level were able to predict Alzheimer's disease progression. The assay could provide a powerful platform for early prognosis, monitoring disease progression and further mechanistic studies