KIBRA: A New Gateway to Learning and Memory?

The genetic locus encoding KIBRA, a member of the WWC family of proteins, has recently been shown to be associated with human memory performance through genome-wide single nucleotide polymorphism screening. Gene expression analysis and a variety of functional studies have further indicated that such a role is biologically plausible for KIBRA. Here, we review the existing literature, illustrate connections between the different lines of evidence, and derive models based on KIBRA's function(s) in the brain that can be further tested experimentally

Common BACE2 Polymorphisms are Associated with Altered Risk for Alzheimer's Disease and CSF Amyloid Biomarkers in APOE ε4 Non-Carriers

It was recently suggested that beta-site amyloid precursor protein (APP)-cleaving enzyme 2 (BACE2) functions as an amyloid beta (A beta)-degrading enzyme; in addition to its better understood role as an APP secretase. Due to this finding we sought to understand the possible genetic risk contributed by the BACE2 locus to the development of late-onset Alzheimer's disease (AD). In this study, we report that common single nucleotide polymorphism (SNP) variation in BACE2 is associated with altered AD risk in apolipoprotein E gene (APOE) epsilon 4 variant (e4) non-carriers. In addition, in e4 non-carriers diagnosed with AD or mild cognitive impairment (MCI), SNPs within the BACE2 locus are associated with cerebrospinal fluid (CSF) levels of A beta 1-42. Further, SNP variants in BACE2 are also associated with BACE2 RNA expression levels suggesting a potential mechanism for the CSF A beta 1-42 findings. Lastly, overexpression of BACE2 in vitro resulted in decreased A beta 1-40 and A beta 1-42 fragments in a cell line model of A beta production. These findings suggest that genetic variation at the BACE2 locus modifies AD risk for those individuals who don't carry the e4 variant of APOE. Further, our data indicate that the biological mechanism associated with this altered risk is linked to amyloid generation or clearance possibly through BACE2 expression changes.National Institute on Aging (NIA); National Alzheimer's Coordinating Center (NACC) [U01 AG016976]; National Institute on Aging: Ruth Seemann, John Hopkins Alzheimer's Disease Research Center (NIA) [AG05146, P50 AG16570, AG05128]; NINDS [NS39764]; Glaxo Smith Kline [P50-AG053760, AG05144, P50AG05681, P50 AG05136, P30-AG13846, 211002]; Arizona Biomedical Research Commission [4001, 0011, 05_ 901]; Michael J. Fox Foundation [AG10161, HHSN-271-2013-00030C]; McGowan Endowment; Medical Research Council, local NHS trusts and Newcastle University; Medical Research Council; Safa Al-Sarraj; Netherlands Brain Bank; Stichting MS Research, Brain Net Europe; Hersenstichting Nederland Breinbrekend Werk, International Parkinson Fonds; Internationale Stiching Alzheimer Onderzoek; NIH-NIA [R01-AG041232]; State of Arizona DHS (Arizona Alzheimer's Consortium) - NIH EUREKA [R01-AG034504]; NIH intramural funds; UK Dementia Research Institute; DRI Ltd - UK Medical Research Council; Alzheimer's Society; Alzheimer's Research UK - Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health) [U01 AG024904]; DOD ADNI (Department of Defense) [W81XWH-12-2-0012]; National Institute on Aging; National Institute of Biomedical Imaging and Bioengineering; Alzheimer'sAssociation; Alzheimer's Drug Discovery Foundation; Araclon Biotech; Biogen; Bristol-Myers Squibb Company; CereSpir, Inc.; Cogstate; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd; Fujirebio; Johnson & Johnson Pharmaceutical Research & Development LLC.; Merck Co., Inc.; Meso Scale Diagnostics; NeuroRx Research; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Takeda Pharmaceutical Company; Canadian Institutes of Health Research isproviding funds; ADNI clinical sites in Canada; Foundation for the National Institutes of Health; Northern California Institute for Research and Education; Laboratory for Neuro Imaging at the University of Southern CaliforniaOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Regional covariance of white matter hyperintensity volume patterns associated with hippocampal volume in healthy aging

Hippocampal volume is particularly sensitive to the accumulation of total brain white matter hyperintensity volume (WMH) in aging, but how the regional distribution of WMH volume differentially impacts the hippocampus has been less studied. In a cohort of 194 healthy older adults ages 50–89, we used a multivariate statistical method, the Scaled Subprofile Model (SSM), to (1) identify patterns of regional WMH differences related to left and right hippocampal volumes, (2) examine associations between the multimodal neuroimaging covariance patterns and demographic characteristics, and (3) investigate the relation of the patterns to subjective and objective memory in healthy aging. We established network covariance patterns of regional WMH volume differences associated with greater left and right hippocampal volumes, which were characterized by reductions in left temporal and right parietal WMH volumes and relative increases in bilateral occipital WMH volumes. Additionally, we observed lower expression of these hippocampal-related regional WMH patterns were significantly associated with increasing age and greater subjective memory complaints, but not objective memory performance in this healthy older adult cohort. Our findings indicate that, in cognitively healthy older adults, left and right hippocampal volume reductions were associated with differences in the regional distribution of WMH volumes, which were exacerbated by advancing age and related to greater subjective memory complaints. Multivariate network analyses, like SSM, may help elucidate important early effects of regional WMH volume on brain and cognitive aging in healthy older adults

Identification of disease causing loci using an array-based genotyping approach on pooled DNA

BACKGROUND: Pooling genomic DNA samples within clinical classes of disease followed by genotyping on whole-genome SNP microarrays, allows for rapid and inexpensive genome-wide association studies. Key to the success of these studies is the accuracy of the allelic frequency calculations, the ability to identify false-positives arising from assay variability and the ability to better resolve association signals through analysis of neighbouring SNPs. RESULTS: We report the accuracy of allelic frequency measurements on pooled genomic DNA samples by comparing these measurements to the known allelic frequencies as determined by individual genotyping. We describe modifications to the calculation of k-correction factors from relative allele signal (RAS) values that remove biases and result in more accurate allelic frequency predictions. Our results show that the least accurate SNPs, those most likely to give false-positives in an association study, are identifiable by comparing their frequencies to both those from a known database of individual genotypes and those of the pooled replicates. In a disease with a previously identified genetic mutation, we demonstrate that one can identify the disease locus through the comparison of the predicted allelic frequencies in case and control pools. Furthermore, we demonstrate improved resolution of association signals using the mean of individual test-statistics for consecutive SNPs windowed across the genome. A database of k-correction factors for predicting allelic frequencies for each SNP, derived from several thousand individually genotyped samples, is provided. Lastly, a Perl script for calculating RAS values for the Affymetrix platform is provided. CONCLUSION: Our results illustrate that pooling of DNA samples is an effective initial strategy to identify a genetic locus. However, it is important to eliminate inaccurate SNPs prior to analysis by comparing them to a database of individually genotyped samples as well as by comparing them to replicates of the pool. Lastly, detection of association signals can be improved by incorporating data from neighbouring SNPs

Extracellular microRNAs in blood differentiate between ischaemic and haemorrhagic stroke subtypes.

Rapid identification of patients suffering from cerebral ischaemia, while excluding intracerebral haemorrhage, can assist with patient triage and expand patient access to chemical and mechanical revascularization. We sought to identify blood-based, extracellular microRNAs 15 (ex-miRNAs) derived from extracellular vesicles associated with major stroke subtypes using clinical samples from subjects with spontaneous intraparenchymal haemorrhage (IPH), aneurysmal subarachnoid haemorrhage (SAH) and ischaemic stroke due to cerebral vessel occlusion. We collected blood from patients presenting with IPH (n = 19), SAH (n = 17) and ischaemic stroke (n = 21). We isolated extracellular vesicles from plasma, extracted RNA cargo, 20 sequenced the small RNAs and performed bioinformatic analyses to identify ex-miRNA biomarkers predictive of the stroke subtypes. Sixty-seven miRNAs were significantly variant across the stroke subtypes. A subset of exmiRNAs differed between haemorrhagic and ischaemic strokes, and LASSO analysis could distinguish SAH from the other subtypes with an accuracy of 0.972 ± 0.002. Further analyses predicted 25 miRNA classifiers that stratify IPH from ischaemic stroke with an accuracy of 0.811 ± 0.004 and distinguish haemorrhagic from ischaemic stroke with an accuracy of 0.813 ± 0.003. Blood-based, ex-miRNAs have predictive value, and could be capable of distinguishing between major stroke subtypes with refinement and validation. Such a biomarker could one day aid in the triage of patients to expand the pool eligible for effective treatment

Extracellular microRNAs in blood differentiate between ischaemic and haemorrhagic stroke subtypes

Rapid identification of patients suffering from cerebral ischaemia, while excluding intracerebral haemorrhage, can assist with patient triage and expand patient access to chemical and mechanical revascularization. We sought to identify blood-based, extracellular microRNAs 15 (ex-miRNAs) derived from extracellular vesicles associated with major stroke subtypes using clinical samples from subjects with spontaneous intraparenchymal haemorrhage (IPH), aneurysmal subarachnoid haemorrhage (SAH) and ischaemic stroke due to cerebral vessel occlusion. We collected blood from patients presenting with IPH (n = 19), SAH (n = 17) and ischaemic stroke (n = 21). We isolated extracellular vesicles from plasma, extracted RNA cargo, 20 sequenced the small RNAs and performed bioinformatic analyses to identify ex-miRNA biomarkers predictive of the stroke subtypes. Sixty-seven miRNAs were significantly variant across the stroke subtypes. A subset of exmiRNAs differed between haemorrhagic and ischaemic strokes, and LASSO analysis could distinguish SAH from the other subtypes with an accuracy of 0.972 +/- 0.002. Further analyses predicted 25 miRNA classifiers that stratify IPH from ischaemic stroke with an accuracy of 0.811 +/- 0.004 and distinguish haemorrhagic from ischaemic stroke with an accuracy of 0.813 +/- 0.003. Blood-based, ex-miRNAs have predictive value, and could be capable of distinguishing between major stroke subtypes with refinement and validation. Such a biomarker could one day aid in the triage of patients to expand the pool eligible for effective treatment.Open access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]

Seizure-Induced Arc mRNA Expression Thresholds in Rat Hippocampus and Perirhinal Cortex

Immediate-early genes (IEGs) are rapidly and transiently induced following excitatory neuronal activity including maximal electroconvulsive shock treatment (ECT). The rapid RNA response can be blocked by the sodium channel antagonist tetrodotoxin (TTX), without blocking seizures, indicating a role for electrical stimulation in electroconvulsive shock-induced mRNA responses. In behaving animals, Arc mRNA is selectively transcribed following patterned neuronal activity and rapidly trafficked to dendrites where it preferentially accumulates at active synapses for local translation. Here we examined whether there is a relationship between the current intensities that elicit seizures and the threshold for Arc mRNA transcription in the rat hippocampus and perirhinal cortex (PRC). Animals received ECT of varying current intensities (0, 20, 40 65, 77 and 85 mA) and were sacrificed 5 min later. While significantly more CA1, CA3 and perirhinal pyramidal cells expressed Arc at the lowest stimulus intensity compared to granule cells, there was an abrupt threshold transition that occurred in all four regions at 77 mA. This precise threshold for Arc expression in all temporal lobe neurons examined may involve regulation of the calcium-dependent mechanisms that are upstream to activity-dependent IEG transcription

Family history of Alzheimer's disease alters cognition and is modified by medical and genetic factors

In humans, a first-degree family history of dementia (FH) is a well-documented risk factor for Alzheimer's disease (AD); however, the influence of FH on cognition across the lifespan is poorly understood. To address this issue, we developed an internet-based paired-associates learning (PAL) task and tested 59,571 participants between the ages of 18-85. FH was associated with lower PAL performance in both sexes under 65 years old. Modifiers of this effect of FH on PAL performance included age, sex, education, and diabetes. The Apolipoprotein E epsilon 4 allele was also associated with lower PAL scores in FH positive individuals. Here we show, FH is associated with reduced PAL performance four decades before the typical onset of AD; additionally, several heritable and non-heritable modifiers of this effect were identified.Mueller Family Charitable Trust; Arizona Department of Health Services; National Institutes of Health [R01-AG041232, R01-AG049465-05]; Flinn FoundationOpen access journalThis item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at [email protected]