Variants in the Mitochondrial Intermediate Peptidase (MIPEP) Gene are Associated with Gray Matter Density in the Alzheimer’s Disease Neuroimaging Initiative Cohort

poster abstractCancer and Alzheimer’s disease (AD) incidence is inversely correlated, but the genetic underpinnings of this relationship remain to be elucidated. Recent findings identified lower gray matter density in frontal regions of participants of the Alzheimer’s Disease Neuroimaging Initiative (ADNI) with cancer history compared to those without such history, across diagnostic groups (Nudelman et al., 2014). Pathways proposed to impact cancer and AD, including metabolism and survival, may play an important role in the observed difference. To test this hypothesis, a genome-wide association study (GWAS) using mean frontal gray matter cluster values was performed for all Caucasian participants in this cohort with neuroimaging and genetic data (n=1405). Analysis covaried for age, sex, AD, and cancer history. Of the two genes with the most significant SNPs (p<10-5), WD repeat domain 5B (WDR5B) and mitochondrial intermediate peptidase (MIPEP), MIPEP was selected for further analysis given the hypothesis focus on metabolism. ANOVA analysis of MIPEP top SNP rs8181878 with frontal gray matter cluster values in SPSS indicated that while this SNP is significantly associated with gray matter density (p=2x10-6), no interaction was observed with cancer history or AD diagnosis. Furthermore, whole brain gray matter voxel-wise analysis of this SNP using Statistical Parametric Mapping 8 software showed that minor allele(s) of this SNP were significantly (PFWE<0.05) associated with higher gray matter density. These results suggest that the minor allele of MIPEP SNP rs8181878 may be protective against gray matter density loss, highlighting the importance of metabolic processes in aging and disease

Association of cancer history with Alzheimer's disease onset and structural brain changes

Epidemiological studies show a reciprocal inverse association between cancer and Alzheimer's disease (AD). The common mechanistic theory for this effect posits that cells have an innate tendency toward apoptotic or survival pathways, translating to increased risk for either neurodegeneration or cancer. However, it has been shown that cancer patients experience cognitive dysfunction pre- and post-treatment as well as alterations in cerebral gray matter density (GMD) on MRI. To further investigate these issues, we analyzed the association between cancer history (CA±) and age of AD onset, and the relationship between GMD and CA± status across diagnostic groups in the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort study. Data was analyzed from 1609 participants with information on baseline cancer history and AD diagnosis, age of AD onset, and baseline MRI scans. Participants were CA+ (N = 503) and CA− (N = 1106) diagnosed with AD, mild cognitive impairment (MCI), significant memory concerns (SMC), and cognitively normal older adults. As in previous studies, CA+ was inversely associated with AD at baseline (P = 0.025); interestingly, this effect appears to be driven by non-melanoma skin cancer (NMSC), the largest cancer category in this study (P = 0.001). CA+ was also associated with later age of AD onset (P < 0.001), independent of apolipoprotein E (APOE) ε4 allele status, and individuals with two prior cancers had later mean age of AD onset than those with one or no prior cancer (P < 0.001), suggesting an additive effect. Voxel-based morphometric analysis of GMD showed CA+ had lower GMD in the right superior frontal gyrus compared to CA− across diagnostic groups (Pcrit < 0.001, uncorrected); this cluster of lower GMD appeared to be driven by history of invasive cancer types, rather than skin cancer. Thus, while cancer history is associated with a measurable delay in AD onset independent of APOE ε4, the underlying mechanism does not appear to be cancer-related preservation of GMD

High-J CO emission in the Cepheus E protostellar outflow observed with SOFIA/GREAT

We present and analyze two spectrally resolved high-J CO lines towards the molecular outflow Cep E, driven by an intermediate-mass class 0 protostar. Using the GREAT receiver on board SOFIA, we observed the CO (12--11) and (13--12) transitions (E_u ~ 430 and 500 K, respectively) towards one position in the blue lobe of this outflow, that had been known to display high-velocity molecular emission. We detect the outflow emission in both transitions, up to extremely high velocities (~ 100 km/s with respect to the systemic velocity). We divide the line profiles into three velocity ranges that each have interesting spectral features: standard, intermediate, and extremely high-velocity. One distinct bullet is detected in each of the last two. A large velocity gradient analysis for these three velocity ranges provides constraints on the kinetic temperature and volume density of the emitting gas, >~ 100 K and > ~ 10^4 cm^-3, respectively. These results are in agreement with previous ISO observations and are comparable with results obtained by Herschel for similar objects. We conclude that high-J CO lines are a good tracer of molecular bullets in protostellar outflows. Our analysis suggests that different physical conditions are at work in the intermediate velocity range compared with the standard and extremely high-velocity gas at the observed position.Comment: Accepted for publication in A&A (SOFIA/GREAT special issue

Resting-state fMRI Activity Profile in Prodromal Alzheimer’s Disease and Older Adults with Cognitive Complaints

poster abstractBackground: Resting-state functional MRI (RS-fMRI) has been proposed to detect neurodegenerative disease-related network alterations before brain atrophy has emerged. Disrupted resting-state connectivity in the posterior cingulate cortex (PCC) and hippocampus has been reported in AD (Grecius, 2004), yet results in prodromal AD including MCI vary. Other methods have suggested the feasibility of earlier detection in euthymic older adults with marked cognitive complaints (CC) but normal neuropsychological test performance (Saykin, 2006). The current study was designed to assess RS-fMRI patterns in CC compared with MCI, AD and healthy controls (HC). Methods: To date, 13 CC, 9 HC, 4 MCI and 3 AD participants were scanned at rest with eyes closed on a Siemens 3T. RS-fMRI was analyzed using FSL, AFNI and SPM8. For each individual, the sum of amplitude of low frequency fluctuation (ALFF; 0.01–0.1 Hz) was calculated at each voxel (Biswal, 2010). Using PCC seed ROIs adapted from Fox et al (2005) voxel-wise cross-correlation maps were generated for each subject. Group comparisons and covariate analyses were performed using SPM8 with age as a covariate. Results: Compared to HC, MCI/AD showed decreased ALFF in the PCC (p CC > MCI/AD, p<0.05, effect size: 0.61), and ALFF of hippocampus (HC < CC < MCI/AD, p<0.01, effect size: 0.75). ALFF of PCC was positively correlated with neuropsychological performance (MMSE, DRS and CVLT; r=0.45 to 0.56, p<0.01), while hippocampal ALFF was negatively correlated with performance (r=-0.48 to -0.67, p<0.01). PCC seeded crosscorrelation maps showed decreased hippocampal connectivity in MCI/AD compared to HC or CC (p<0.01). Conclusions: RS-fMRI appears sensitive to early prodromal neurodegenerative changes in regions associated with AD, notably including pre-MCI individuals with CC. While there is decreased functional connectivity between PCC and hippocampus, regionally increased ALFF in hippocampus may indicate a compensatory mechanism in early prodromal AD

Baseline MRI Predictors of Conversion from MCI to Probable AD in the ADNI Cohort

The Alzheimer’s Disease Neuroimaging Initiative (ADNI) is a multi-center study assessing neuroimaging in diagnosis and longitudinal monitoring. Amnestic Mild Cognitive Impairment (MCI) often represents a prodromal form of dementia, conferring a 10-15% annual risk of converting to probable AD. We analyzed baseline 1.5T MRI scans in 693 participants from the ADNI cohort divided into four groups by baseline diagnosis and one year MCI to probable AD conversion status to identify neuroimaging phenotypes associated with MCI and AD and potential predictive markers of imminent conversion. MP-RAGE scans were analyzed using publicly available voxel-based morphometry (VBM) and automated parcellation methods. Measures included global and hippocampal grey matter (GM) density, hippocampal and amygdalar volumes, and cortical thickness values from entorhinal cortex and other temporal and parietal lobe regions. The overall pattern of structural MRI changes in MCI (n=339) and AD (n=148) compared to healthy controls (HC, n=206) was similar to prior findings in smaller samples. MCI-Converters (n=62) demonstrated a very similar pattern of atrophic changes to the AD group up to a year before meeting clinical criteria for AD. Finally, a comparison of effect sizes for contrasts between the MCI-Converters and MCI-Stable (n=277) groups on MRI metrics indicated that degree of neurodegeneration of medial temporal structures was the best antecedent MRI marker of imminent conversion, with decreased hippocampal volume (left > right) being the most robust. Validation of imaging biomarkers is important as they can help enrich clinical trials of disease modifying agents by identifying individuals at highest risk for progression to AD

Multimodal Neuroimaging Predictors for Cognitive Performance Using Structured Sparse Learning

poster abstractRegression models have been widely studied to investigate whether multimodal neuroimaging measures can be used as effective biomarkers for predicting cognitive outcomes in the study of Alzheimer's Disease (AD). Most existing models overlook the interrelated structures either within neuroimaging measures or between cognitive outcomes, and thus may have limited power to yield optimal solutions. To address this issue, we propose to incorporate an L21 norm and/or a group L21 norm (G21 norm) in the regression models. Using ADNI-1 and ADNI-GO/2 data, we apply these models to examining the ability of structural MRI and AV-45 PET scans for predicting cognitive measures including ADAS and RAVLT scores. We focus our analyses on the participants with mild cognitive impairment (MCI), a prodromal stage of AD, in order to identify useful patterns for early detection. Compared with traditional linear and ridge regression methods, these new models not only demonstrate superior and more stable predictive performances, but also identify a small set of imaging markers that are biologically meaningful

Polarisation Observations of VY Canis Majoris Water Vapour 5{32}-4{41} 620.701 GHz Maser Emission with HIFI

CONTEXT: Water vapour maser emission from evolved oxygen-rich stars remains poorly understood. Additional observations, including polarisation studies and simultaneous observation of different maser transitions may ultimately lead to greater insight. AIMS: We have aimed to elucidate the nature and structure of the VY CMa water vapour masers in part by observationally testing a theoretical prediction of the relative strengths of the 620.701 GHz and the 22.235 GHz maser components of ortho water vapour. METHODS: In its high-resolution mode (HRS) the Herschel Heterodyne Instrument for the Infrared (HIFI) offers a frequency resolution of 0.125 MHz, corresponding to a line-of-sight velocity of 0.06 km/s, which we employed to obtain the strength and linear polarisation of maser spikes in the spectrum of VY CMa at 620.701 GHz. Simultaneous ground based observations of the 22.235 GHz maser with the Max-Planck-Institut f\"ur Radioastronomie 100-meter telescope at Effelsberg, provided a ratio of 620.701 GHz to 22.235 GHz emission. RESULTS:We report the first astronomical detection to date of water vapour maser emission at 620.701 GHz. In VY CMa both the 620.701 and the 22.235 GHz polarisation are weak. At 620.701 GHz the maser peaks are superposed on what appears to be a broad emission component, jointly ejected asymmetrically from the star. We observed the 620.701 GHz emission at two epochs 21 days apart, both to measure the potential direction of linearly polarised maser components and to obtain a measure of the longevity of these components. Although we do not detect significant polarisation levels in the core of the line, they rise up to approximately 6% in its wings

Cognitive complaints in older adults at risk for Alzheimer's disease are associated with altered resting-state networks

INTRODUCTION: Pathophysiological changes that accompany early clinical symptoms in prodromal Alzheimer's disease (AD) may have a disruptive influence on brain networks. We investigated resting-state functional magnetic resonance imaging (rsfMRI), combined with brain connectomics, to assess changes in whole-brain functional connectivity (FC) in relation to neurocognitive variables. METHODS: Participants included 58 older adults who underwent rsfMRI. Individual FC matrices were computed based on a 278-region parcellation. FastICA decomposition was performed on a matrix combining all subjects' FC. Each FC pattern was then used as a response in a multilinear regression model including neurocognitive variables associated with AD (cognitive complaint index [CCI] scores from self and informant, an episodic memory score, and an executive function score). RESULTS: Three connectivity independent component analysis (connICA) components (RSN, VIS, and FP-DMN FC patterns) associated with neurocognitive variables were identified based on prespecified criteria. RSN-pattern, characterized by increased FC within all resting-state networks, was negatively associated with self CCI. VIS-pattern, characterized by an increase in visual resting-state network, was negatively associated with CCI self or informant scores. FP-DMN-pattern, characterized by an increased interaction of frontoparietal and default mode networks (DMN), was positively associated with verbal episodic memory. DISCUSSION: Specific patterns of FC were differently associated with neurocognitive variables thought to change early in the course of AD. An integrative connectomics approach relating cognition to changes in FC may help identify preclinical and early prodromal stages of AD and help elucidate the complex relationship between subjective and objective indices of cognitive decline and differences in brain functional organization

The APEX-CHAMP+ view of the Orion Molecular Cloud 1 core - Constraining the excitation with submillimeter CO multi-line observations

A high density portion of the Orion Molecular Cloud 1 (OMC-1) contains the prominent, warm Kleinmann-Low (KL) nebula that is internally powered by an energetic event plus a farther region in which intermediate to high mass stars are forming. Its outside is affected by ultraviolet radiation from the neighboring Orion Nebula Cluster and forms the archetypical photon-dominated region (PDR) with the prominent bar feature. Its nearness makes the OMC-1 core region a touchstone for research on the dense molecular interstellar medium and PDRs. Using the Atacama Pathfinder Experiment telescope (APEX), we have imaged the line emission from the multiple transitions of several carbon monoxide (CO) isotopologues over the OMC-1 core region. Our observations employed the 2x7 pixel submillimeter CHAMP+ array to produce maps (~ 300 arcsec x 350 arcsec) of 12CO, 13CO, and C18O from mid-J transitions (J=6-5 to 8-7). We also obtained the 13CO and C18O J=3-2 images toward this region. The 12CO line emission shows a well-defined structure which is shaped and excited by a variety of phenomena, including the energetic photons from hot, massive stars in the nearby Orion Nebula's central Trapezium cluster, active high- and intermediate-mass star formation, and a past energetic event that excites the KL nebula. Radiative transfer modeling of the various isotopologic CO lines implies typical H2 densities in the OMC-1 core region of ~10^4-10^6 cm^-3 and generally elevated temperatures (~ 50-250 K). We estimate a warm gas mass in the OMC-1 core region of 86-285 solar masses.Comment: 11 pages, 9 figures, accepted by A&