Dirk Keene

GENOME-WIDE ANALYSIS OF AMYLOID BETA (AB) PEPTIDE OBTAINED FROM HISTELIDE IDENTIFIES SUGGESTIVE HITS IN RHBDF1, GRID1, AND PTPRD REGIONS IN THE ADULT CHANGES IN THOUGHT (ACT) STUDY

Rhonda K. Roby, Jeffrey L. Tilson, Ramon Diaz-Arrastia, Sid E. O’Bryant, Kirk C. Wilhelmsen, University of North Texas Health Science Center, Fort Worth, Texas, United States; University of North Texas Health Science Center, Ft. Worth, Texas, United States; University of North Texas Health Science Center, Fort Worth, Texas, United States; UT Southwestern Medical Center, Dallas, Texas, United States; University of North Texas Health Science Center, Ft. Worth, Texas, United States; University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, United States; Uniformed Services University of the Health Sciences, Rockville, Maryland, United States. Contact e-mail: Robert.Barber@ unthsc.edu

A computational framework identifying concordant gene expression-neuropathology associations reveals Complex I as a potential Alzheimer's disease therapeutic target

Identifying gene expression markers for Alzheimer’s disease (AD) neuropathology through meta-analysis is a complex undertaking because available data are often from different studies and/or brain regions involving study-specific confounders and/or region-specific biological processes. Here, we developed a probabilistic model-based framework, DECODER, leveraging these discrepancies to identify robust biomarkers for complex phenotypes. Our experiments present: (1) DECODER’s potential as a general meta-analysis framework widely applicable to various diseases (e.g., AD and cancer) and phenotypes (e.g., Amyloid-β (Aβ) pathology, tau pathology, and survival), (2) our results from a meta-analysis using 1,746 human brain tissue samples from nine brain regions in three studies — the largest expression meta-analysis for AD, to our knowledge —, and (3) in vivo validation of identified modifiers of Aβ toxicity in a transgenic Caenorhabditis elegans model expressing AD-associated Aβ, which pinpoints mitochondrial Complex I as a critical mediator of proteostasis and a promising pharmacological avenue toward treating AD.Identifying gene expression markers for Alzheimer9s disease (AD) neuropathology through meta-analysis is a complex undertaking because available data are often from different studies and/or brain regions involving study-specific confounders and/or region-specific biological processes. Here, we developed a probabilistic model-based framework, DECODER, leveraging these discrepancies to identify robust biomarkers for complex phenotypes. Our experiments present: (1) DECODER9s potential as a general meta-analysis framework widely applicable to various diseases (e.g., AD and cancer) and phenotypes (e.g., Amyloid-β; (Aβ) pathology, tau pathology, and survival), (2) our results from a meta-analysis using 1,746 human brain tissue samples from nine brain regions in three studies -- the largest expression meta-analysis for AD, to our knowledge --, and (3) in vivo validation of identified modifiers of Aβ toxicity in a transgenic Caenorhabditis elegans model expressing AD-associated Aβ, which pinpoints mitochondrial Complex I as a critical mediator of proteostasis and a promising pharmacological avenue toward treating AD.We examine, across nine human brain regions, the spectrum of genome-wide gene expression associations with Alzheimer9s disease (AD) neuropathology using 1,746 human individuals from three AD studies. We introduce a new computational approach, DECODER, that leverages discrepancies across different brain regions or different studies in order to identify robust expression markers for complex neuropathological phenotypes. Our computational evaluation experiments demonstrate: (1) the possibility of performing meta-analysis in the highly challenging AD setting where datasets involve study-specific confounders or brain region-specific biological processes, (2) DECODER9s potential as a general meta-analysis framework widely applicable to various diseases (e.g., AD, cancer) or phenotypes (e.g., neuropathology, survival), and (3) provide new insights into the similarity of brain regions in terms of expression associations with AD hallmarks. We further extend these computational advances through in vivo validation of novel genes using a transgenic Caenorhabditis elegans model expressing AD-associated amyloid beta. Our approach yields several novel genetic modifiers of amyloid beta toxicity and pinpoints Complex I of the mitochondrial electron transport chain (mETC) as a critical mediator of proteostasis and a promising potential pharmacological avenue toward treating AD.

DECODER: A probabilistic approach to integrate big data reveals mitochondrial Complex I as a potential therapeutic target for Alzheimer's disease

Identifying gene expression markers for Alzheimer’s disease (AD) neuropathology through meta-analysis is a complex undertaking because available data are often from different studies and/or brain regions involving study-specific confounders and/or region-specific biological processes. Here, we developed a probabilistic model-based framework, DECODER, leveraging these discrepancies to identify robust biomarkers for complex phenotypes. Our experiments present: (1) DECODER’s potential as a general meta-analysis framework widely applicable to various diseases (e.g., AD and cancer) and phenotypes (e.g., Amyloid-β (Aβ) pathology, tau pathology, and survival), (2) our results from a meta-analysis using 1,746 human brain tissue samples from nine brain regions in three studies — the largest expression meta-analysis for AD, to our knowledge —, and (3) in vivo validation of identified modifiers of Aβ toxicity in a transgenic Caenorhabditis elegans model expressing AD-associated Aβ, which pinpoints mitochondrial Complex I as a critical mediator of proteostasis and a promising pharmacological avenue toward treating AD.Identifying gene expression markers for Alzheimer9s disease (AD) neuropathology through meta-analysis is a complex undertaking because available data are often from different studies and/or brain regions involving study-specific confounders and/or region-specific biological processes. Here, we developed a probabilistic model-based framework, DECODER, leveraging these discrepancies to identify robust biomarkers for complex phenotypes. Our experiments present: (1) DECODER9s potential as a general meta-analysis framework widely applicable to various diseases (e.g., AD and cancer) and phenotypes (e.g., Amyloid-β; (Aβ) pathology, tau pathology, and survival), (2) our results from a meta-analysis using 1,746 human brain tissue samples from nine brain regions in three studies -- the largest expression meta-analysis for AD, to our knowledge --, and (3) in vivo validation of identified modifiers of Aβ toxicity in a transgenic Caenorhabditis elegans model expressing AD-associated Aβ, which pinpoints mitochondrial Complex I as a critical mediator of proteostasis and a promising pharmacological avenue toward treating AD.We examine, across nine human brain regions, the spectrum of genome-wide gene expression associations with Alzheimer9s disease (AD) neuropathology using 1,746 human individuals from three AD studies. We introduce a new computational approach, DECODER, that leverages discrepancies across different brain regions or different studies in order to identify robust expression markers for complex neuropathological phenotypes. Our computational evaluation experiments demonstrate: (1) the possibility of performing meta-analysis in the highly challenging AD setting where datasets involve study-specific confounders or brain region-specific biological processes, (2) DECODER9s potential as a general meta-analysis framework widely applicable to various diseases (e.g., AD, cancer) or phenotypes (e.g., neuropathology, survival), and (3) provide new insights into the similarity of brain regions in terms of expression associations with AD hallmarks. We further extend these computational advances through in vivo validation of novel genes using a transgenic Caenorhabditis elegans model expressing AD-associated amyloid beta. Our approach yields several novel genetic modifiers of amyloid beta toxicity and pinpoints Complex I of the mitochondrial electron transport chain (mETC) as a critical mediator of proteostasis and a promising potential pharmacological avenue toward treating AD.

A probabilistic approach to using big data reveals Complex I as a potential Alzheimer's disease therapeutic target

Identifying gene expression markers for Alzheimer’s disease (AD) neuropathology through meta-analysis is a complex undertaking because available data are often from different studies and/or brain regions involving study-specific confounders and/or region-specific biological processes. Here, we developed a probabilistic model-based framework, DECODER, leveraging these discrepancies to identify robust biomarkers for complex phenotypes. Our experiments present: (1) DECODER’s potential as a general meta-analysis framework widely applicable to various diseases (e.g., AD and cancer) and phenotypes (e.g., Amyloid-β (Aβ) pathology, tau pathology, and survival), (2) our results from a meta-analysis using 1,746 human brain tissue samples from nine brain regions in three studies — the largest expression meta-analysis for AD, to our knowledge —, and (3) in vivo validation of identified modifiers of Aβ toxicity in a transgenic Caenorhabditis elegans model expressing AD-associated Aβ, which pinpoints mitochondrial Complex I as a critical mediator of proteostasis and a promising pharmacological avenue toward treating AD.Identifying gene expression markers for Alzheimer9s disease (AD) neuropathology through meta-analysis is a complex undertaking because available data are often from different studies and/or brain regions involving study-specific confounders and/or region-specific biological processes. Here, we developed a probabilistic model-based framework, DECODER, leveraging these discrepancies to identify robust biomarkers for complex phenotypes. Our experiments present: (1) DECODER9s potential as a general meta-analysis framework widely applicable to various diseases (e.g., AD and cancer) and phenotypes (e.g., Amyloid-β; (Aβ) pathology, tau pathology, and survival), (2) our results from a meta-analysis using 1,746 human brain tissue samples from nine brain regions in three studies -- the largest expression meta-analysis for AD, to our knowledge --, and (3) in vivo validation of identified modifiers of Aβ toxicity in a transgenic Caenorhabditis elegans model expressing AD-associated Aβ, which pinpoints mitochondrial Complex I as a critical mediator of proteostasis and a promising pharmacological avenue toward treating AD.We examine, across nine human brain regions, the spectrum of genome-wide gene expression associations with Alzheimer9s disease (AD) neuropathology using 1,746 human individuals from three AD studies. We introduce a new computational approach, DECODER, that leverages discrepancies across different brain regions or different studies in order to identify robust expression markers for complex neuropathological phenotypes. Our computational evaluation experiments demonstrate: (1) the possibility of performing meta-analysis in the highly challenging AD setting where datasets involve study-specific confounders or brain region-specific biological processes, (2) DECODER9s potential as a general meta-analysis framework widely applicable to various diseases (e.g., AD, cancer) or phenotypes (e.g., neuropathology, survival), and (3) provide new insights into the similarity of brain regions in terms of expression associations with AD hallmarks. We further extend these computational advances through in vivo validation of novel genes using a transgenic Caenorhabditis elegans model expressing AD-associated amyloid beta. Our approach yields several novel genetic modifiers of amyloid beta toxicity and pinpoints Complex I of the mitochondrial electron transport chain (mETC) as a critical mediator of proteostasis and a promising potential pharmacological avenue toward treating AD.

A GENOMIC AND CELL FUNCTION APPROACH TO IDENTIFYING CELL-TYPE-SPECIFIC BIOLOGICAL NETWORKS IN ALZHEIMER'S DISEASE

weight) loading pb-gal (30 mg/mouse) or buffer containing pbgal or only buffer. Immunofluorescenece studies was conducted by injecting single dose of liposomal formulations (w15.2 mmoles phospholipids/kg body weight) loading pGFP (30 mg/mouse). After 7 days, the brains were embedded in OCT compound and snap frozen in the liquid nitrogen. Tissue sections (30 mm thick) were cut using cryostat, fixed in acetone andmethanol and incubated with primary antibody (anti-GFP antibody 1:100, Invitrogen) at 4 C overnight. Thereafter, sections were incubated with Alexa Fluor 488 secondary antibody diluted to 1:200 and observed by confocal microscope. Results: A dual-functionalized liposome was developed to cross BBB and deliver gene to brain cells. The system could reach brain parenchyma and release pDNA in the cytoplasm of neurons, induce b-galactosidase production in vivo, thereby eliciting a better effect than the non-modified liposomes as well as naked pDNA. The study illustrated the superior ability of dual-functionalized liposomes to accumulate in the brain and transfect neurons. Conclusions:These results indicated that the liposomal formulation might be an efficient gene carrier and considered a promising approach for gene therapy of CNS diseases.

LONGITUDINAL COGNITIVE PERFORMANCE OF ALZHEIMER’S DISEASE NEUROPATHOLOGICAL SUBTYPES IN THE RELIGIOUS ORDERS STUDY AND MEMORY AND AGING PROJECT

verage score LP 0.25 (-0.24, 0.73) HpSp -1.03 (-1.76, -0.31) Time -0.25 (-0.27, -0.23) LP * time 0.02 (-0.03, 0.06) HpSp * time -0.10 (-0.18, -0.02) emory score LP 0.38 (-0.40, 1.16) HpSp -1.40 (-2.57, -0.23) Time -0.38 (-0.41, -0.34) LP * time 0.03 (-0.04, 0.10) HpSp * time -0.14 (-0.26, -0.02) isuospatial score LP 0.18 (-0.12, 0.47) HpSp -0.54 (-1.00, -0.08) Time -0.07 (-0.09, -0.05) LP * time 0.01 (-0.03, 0.04) Background:Alzheimer’s disease (AD) is an emerging public health crisis that poses a huge societal burden, and cheap and reliable early screening for preventive treatment is urgently needed.Methods:We demonstrated that Obatoclax, a fluorescent drug that is undergoing phase III anti-cancer trial, could be re-positioned as an imaging agent for preliminary screening of AD via near infrared fluorescence ocular imaging (NIRFOI), due to the transparency of eyes. Results:We showed that Obatoclax could bind to amyloid b (Ab) species, including monomers, oligomers and fibril aggregates in solutions, and could be used to stain Ab plaques from brain slices of AD mice and AD patients. In vivo NIRFOI results suggested that NIRFOI with Obatoclax could differentiate transgenic AD mice (5XFAD) from age-matched wild type (WT) mice. Conclusions: We believe that NIRFOI with Obatoclax has the potential for early preliminary imaging screening of AD patients with a primary care setting in the future. HpSp * time -0.03 (-0.10, 0.04) xecutive functioning score P4-331 LONGITUDINAL COGNITIVE LP 0.03 (-0.31, 0.36) HpSp -0.49 (-1.00, 0.02) Time -0.17 (-0.19, -0.15) LP * time -0.00 (-0.04, 0.03) HpSp * time -0.02 (-0.09, 0.05) PERFORMANCE OFALZHEIMER’S DISEASE NEUROPATHOLOGICAL SUBTYPES IN THE RELIGIOUS ORDERS STUDYAND MEMORYAND AGING PROJECT anguage score LP 0.38 (-0.37, 1.13) HpSp -1.78 (-2.91, -0.66) Time -0.33 (-0.37, -0.30) LP * time 0.03 (-0.04, 0.11) HpSp * time -0.24 (-0.37, -0.11)

A NON-HUMAN PRIMATE MODEL OF EARLY ALZHEIMER’S DISEASE PATHOLOGIC CHANGE

various forms and might contain some unstable forms, it is difficult to quantify AbO in degenerative status, such as SDS-PAGE. Therefore, quantitative method of AbO has not been established. Previously, mouse monoclonal anti-AbO form antibody (m6H4) was generated by Matsubara and colleagues (Life Sciences, 2012). In this study, we establish the quantitative measure method of AbO by dot blot assay using m6H4 specific to AbO form in undegenerated status. Methods: Synthetic Ab1–40 monomer and 5-Carboxytetramethylrhodamine (5-TAMRA)-labeled Ab1–40 monomer dissolved in 0.1% ammonium solution (100 mM) were ultra-centrifuged at 540,000 g for 20 h at 4 C to obtain seed-free supernatant. The supernatant fromAb1–40 and 5-TAMRA-labeledAb1–40monomerswere co-incubated to synthesize AbOs at 37 C for 0, 1, 4 and 20 h. Preparing soluble AbOs, the incubated AbO solution were ultra-centrifuged at 100,000 g for 1 h at 4 C. For dot blot assay, 1 mL of soluble AbOs solutions (0, 5, 10, 25 and 50 mM) were spotted on nitrocellulose membrane, and incubated with m6H4 and mouse monoclonal antiAb antibody (4G8) reactive to 17-24 amino acid residue of Ab followed byHRP-labeled secondary antibody and the chemiluminescent substrate. Chemiluminescent signals were visualized using ChemiDoc Touch and quantified using Image Lab software (Bio-Rad Laboratories, Inc.). Results:Signal intensity of AbOs detected by m6H4 demonstrated time-dependent and concentration-dependent upward trends, enabled to make calibration curves which correlation coefficient at each time points were above 0.83 to 0.99. In contrast, signal intensity of Ab monomer and oligomer detected by 4G8 was stable over the period, and detected as concentration-dependent upward trends. The correlation coefficients of calibration curves by 4G8 at each timewere above 0.99. These results suggested that dot blot assay usingm6H4was able to detect AbO specific time dependent and concentration-dependent changes. Conclusions: Production levels of AbOs detected by m6H4 might show time-dependent and concentration-dependent increase. Dot blot assay using our newly developed AbOs specific antibody could be able to quantitate synthetic AbOs.

AUTOPSY FINDINGS OF CEREBRAL β-AMYLOIDOSIS, TAUOPATHY, AND NEURODEGENERATION (A, T AND N) IN A COMMUNITY-BASED SAMPLE: IMPLICATIONS FOR DEMENTIA MITIGATION STRATEGIES

one visit with cognitive testing. There were 57 (20%) with LP, 22 (8%) with HpSp and 213 (73%) with tAD. For memory, language, and global scores, the HpSp group declined significantly faster, compared to tAD, while the LP group did not (Table 1). The HpSp group did not have relatively better memory performance prior to, at or after dementia diagnosis.Conclusions:The relative frequency and rate of cognitive decline of AD neuropathological subtypes in a population-based sample were similar to previous reports from a convenience sample. However, AD neuropathological subtypes may be incongruous with clinical AD subtypes defined by relative cognitive impairment.

THE POLY(A) BINDING PROTEIN MSUT2 MODULATES GLIOSIS IN TAUOPATHY

also examined in other tauopathies (FTLD-Tau and corticobasal degeneration), other rare amyloidoses (familial Danish dementia, HCHWA-D, Hungarian amyloidosis), and in Down syndrome. Interaction of secernin-1 with phosphorylated tau or Ab in human cortical tissue was examined using co-immunoprecipitation. Results: Immunohistochemistry showed that secernin-1 is a neuronal protein that abundantly accumulates in NFTs and plaque-associated dystrophic neurites in AD. Quantification of secernin-1 immunohistochemistry confirmed that there was significantly more secernin-1 inside NFTs in comparison to surrounding neurons (p<0.0001). Secernin-1 colocalization in NFTs appeared early in NFT development; secernin-1 was present in NFTs in MCI and secernin-1 colocalized with the antibodyMC1, a marker of early NFT development. Additionally, there was increased secernin-1 expression in Down syndrome. Unexpectedly, secernin-1 did not colocalize with phosphorylated tau positive lesions in other types of tauopathies, suggesting that its presence is specific to NFTs in AD. Co-immunoprecipitation studies showed that secernin-1 directly bound to phosphorylated tau in human AD brains. Further co-immunoprecipitation studies are ongoing to determine whether secernin-1 also binds to Ab. Conclusions:Here we present evidence that secernin-1 is a novel early marker of NFTs in AD. Protein binding studies suggest that its presence in NFTs is a result of direct binding to phosphorylated tau. As such, secernin-1 has potential as a novel therapeutic target for AD and could serve as a useful biomarker for AD.

THE CONTRIBUTION OF SEX-SPECIFIC ASSOCIATIONS IN GENETIC STUDIES OF ALZHEIMER’S DISEASE PATHOLOGY

Figure 2. X Chromosome variant rs11094635-G demonstrates a protective effect on longitudinal beta-amyloid accumulation. A. Mean annual percent 18 Leigh Christopher, Grace Tam, Valerio Napolioni, Yongha Kim, Michael D. Greicius, Stanford University, Stanford, CA, USA. Contact e-mail: lchris@stanford.edu change in [ F] AV45 in males according to genotype demonstrating reduced beta-amyloid accumulation in the G genotype. B. Mean annual percent change in [F] AV45 in females demonstrating reduced beta-amyloid accumulation with increasing G allele dosage. Background:Brain beta-amyloid accumulation is a hallmark characteristic of Alzheimer’s disease (AD); however, it is unknown whether common genetic variation on the X-Chromosome plays a role. Thus, we performed an X Chromosome-Wide Association Study (XWAS) to discover single nucleotide polymorphisms (SNPs) associated with longitudinal accumulation of beta-amyloid in the brain as a proxy for disease progression. Methods: Participants were part of the Alzheimer’s Disease Neuroimaging Initiative (ADNI, n1⁄4 621). [F] AV45 PET scans were acquired and pre-processed. [F] AV45 is a radiotracer that binds to beta-amyloid plaques. Genotype data underwent standard quality control and were imputed. XWAS 2.0 was used to run a sex-stratified test (analyzed according to Stouffer’s method) with mean annual percent change in global [F] AV45 (cerebellum normalized) as the quantitative trait. We then tested whether significant variants associated with 1) baseline CSF tau levels 2) longitudinal change in cognitive performance (memory, language and global cognition) using a linear mixed effects model in an independent dataset. Results:A variant upstream of the geneMTM1, rs11094635, was significantly associated with beta-amyloid accumulation (Figure 1, rs11094635 C/G, MAF1⁄4 0.30, Stouffers Z 1⁄4 -4.81, p 1⁄4 1.5 x 10). The minor allele (G) demonstrated a protective effect on beta-amyloid accumulation (Figure 2). Dosage of the minor allele was also associated with lower baseline CSF tau levels (p< 0.05) and a less rapid decline on Boston Naming Task scores in individuals who converted to AD (p1⁄40.012). As a post-hoc analysis, we ran a gene-based test for both beta-amyloid accumulation and AD risk (in a separate case control dataset) to see whether overlapping genes contribute