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  • 1
    Online Resource
    Online Resource
    Morphometricity as a measure of the neuroanatomical signature of a trait
    Proceedings of the National Academy of Sciences ; 2016
    In:  Proceedings of the National Academy of Sciences Vol. 113, No. 39 ( 2016-09-27)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 39 ( 2016-09-27)
    Abstract: Complex physiological and behavioral traits, including neurological and psychiatric disorders, often associate with distributed anatomical variation. This paper introduces a global metric, called morphometricity, as a measure of the anatomical signature of different traits. Morphometricity is defined as the proportion of phenotypic variation that can be explained by macroscopic brain morphology. We estimate morphometricity via a linear mixed-effects model that uses an anatomical similarity matrix computed based on measurements derived from structural brain MRI scans. We examined over 3,800 unique MRI scans from nine large-scale studies to estimate the morphometricity of a range of phenotypes, including clinical diagnoses such as Alzheimer’s disease, and nonclinical traits such as measures of cognition. Our results demonstrate that morphometricity can provide novel insights about the neuroanatomical correlates of a diverse set of traits, revealing associations that might not be detectable through traditional statistical techniques.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1604378113
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2016
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    detail.hit.zdb_id: 1461794-8
    SSG: 11
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  • 2
    Online Resource
    Online Resource
    Bayesian model reveals latent atrophy factors with dissociable cognitive trajectories in Alzheimer’s disease
    Proceedings of the National Academy of Sciences ; 2016
    In:  Proceedings of the National Academy of Sciences Vol. 113, No. 42 ( 2016-10-18)
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 113, No. 42 ( 2016-10-18)
    Abstract: We used a data-driven Bayesian model to automatically identify distinct latent factors of overlapping atrophy patterns from voxelwise structural MRIs of late-onset Alzheimer’s disease (AD) dementia patients. Our approach estimated the extent to which multiple distinct atrophy patterns were expressed within each participant rather than assuming that each participant expressed a single atrophy factor. The model revealed a temporal atrophy factor (medial temporal cortex, hippocampus, and amygdala), a subcortical atrophy factor (striatum, thalamus, and cerebellum), and a cortical atrophy factor (frontal, parietal, lateral temporal, and lateral occipital cortices). To explore the influence of each factor in early AD, atrophy factor compositions were inferred in beta-amyloid–positive (Aβ+) mild cognitively impaired (MCI) and cognitively normal (CN) participants. All three factors were associated with memory decline across the entire clinical spectrum, whereas the cortical factor was associated with executive function decline in Aβ+ MCI participants and AD dementia patients. Direct comparison between factors revealed that the temporal factor showed the strongest association with memory, whereas the cortical factor showed the strongest association with executive function. The subcortical factor was associated with the slowest decline for both memory and executive function compared with temporal and cortical factors. These results suggest that distinct patterns of atrophy influence decline across different cognitive domains. Quantification of this heterogeneity may enable the computation of individual-level predictions relevant for disease monitoring and customized therapies. Factor compositions of participants and code used in this article are publicly available for future research.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1611073113
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2016
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
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  • 3
    Online Resource
    Online Resource
    Statistical tests and identifiability conditions for pooling and analyzing multisite datasets
    Proceedings of the National Academy of Sciences ; 2018
    In:  Proceedings of the National Academy of Sciences Vol. 115, No. 7 ( 2018-02-13), p. 1481-1486
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 115, No. 7 ( 2018-02-13), p. 1481-1486
    Abstract: When sample sizes are small, the ability to identify weak (but scientifically interesting) associations between a set of predictors and a response may be enhanced by pooling existing datasets. However, variations in acquisition methods and the distribution of participants or observations between datasets, especially due to the distributional shifts in some predictors, may obfuscate real effects when datasets are combined. We present a rigorous statistical treatment of this problem and identify conditions where we can correct the distributional shift. We also provide an algorithm for the situation where the correction is identifiable. We analyze various properties of the framework for testing model fit, constructing confidence intervals, and evaluating consistency characteristics. Our technical development is motivated by Alzheimer’s disease (AD) studies, and we present empirical results showing that our framework enables harmonizing of protein biomarkers, even when the assays across sites differ. Our contribution may, in part, mitigate a bottleneck that researchers face in clinical research when pooling smaller sized datasets and may offer benefits when the subjects of interest are difficult to recruit or when resources prohibit large single-site studies.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1719747115
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2018
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
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    Online Resource
  • 4
    Online Resource
    Online Resource
    Identification of genetic risk factors in the Chinese population implicates a role of immune system in Alzheimer’s disease pathogenesis
    Proceedings of the National Academy of Sciences ; 2018
    In:  Proceedings of the National Academy of Sciences Vol. 115, No. 8 ( 2018-02-20), p. 1697-1706
    Details
    In: Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, Vol. 115, No. 8 ( 2018-02-20), p. 1697-1706
    Abstract: Alzheimer’s disease (AD) is a leading cause of mortality among the elderly. We performed a whole-genome sequencing study of AD in the Chinese population. In addition to the variants identified in or around the APOE locus (sentinel variant rs73052335, P = 1.44 × 10 −14 ), two common variants, GCH1 (rs72713460, P = 4.36 × 10 −5 ) and KCNJ15 (rs928771, P = 3.60 × 10 −6 ), were identified and further verified for their possible risk effects for AD in three small non-Asian AD cohorts. Genotype–phenotype analysis showed that KCNJ15 variant rs928771 affects the onset age of AD, with earlier disease onset in minor allele carriers. In addition, altered expression level of the KCNJ15 transcript can be observed in the blood of AD subjects. Moreover, the risk variants of GCH1 and KCNJ15 are associated with changes in their transcript levels in specific tissues, as well as changes of plasma biomarkers levels in AD subjects. Importantly, network analysis of hippocampus and blood transcriptome datasets suggests that the risk variants in the APOE , GCH1 , and KCNJ15 loci might exert their functions through their regulatory effects on immune-related pathways. Taking these data together, we identified common variants of GCH1 and KCNJ15 in the Chinese population that contribute to AD risk. These variants may exert their functional effects through the immune system.
    Type of Medium: Online Resource
    ISSN: 0027-8424 , 1091-6490
    URL: Article
    DOI: 10.1073/pnas.1715554115
    RVK:
    TA 1000
    RVK:
    WA 15000
    Language: English
    Publisher: Proceedings of the National Academy of Sciences
    Publication Date: 2018
    detail.hit.zdb_id: 209104-5
    detail.hit.zdb_id: 1461794-8
    SSG: 11
    SSG: 12
    Location Call Number Limitation Availability
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    Online Resource
  • 5
    Online Resource
    Online Resource
    Cholinergic Modulation of Frontoparietal Cortical Network Dynamics Supporting Supramodal Attention
    Society for Neuroscience ; 2018
    In:  The Journal of Neuroscience Vol. 38, No. 16 ( 2018-04-18), p. 3988-4005
    Details
    In: The Journal of Neuroscience, Society for Neuroscience, Vol. 38, No. 16 ( 2018-04-18), p. 3988-4005
    Abstract: A critical function of attention is to support a state of readiness to enhance stimulus detection, independent of stimulus modality. The nucleus basalis magnocellularis (NBM) is the major source of the neurochemical acetylcholine (ACh) for frontoparietal cortical networks thought to support attention. We examined a potential supramodal role of ACh in a frontoparietal cortical attentional network supporting target detection. We recorded local field potentials (LFPs) in the prelimbic frontal cortex (PFC) and the posterior parietal cortex (PPC) to assess whether ACh contributed to a state of readiness to alert rats to an impending presentation of visual or olfactory targets in one of five locations. Twenty male Long–Evans rats underwent training and then lesions of the NBM using the selective cholinergic immunotoxin 192 IgG-saporin (0.3 μg/μl; ACh-NBM-lesion) to reduce cholinergic afferentation of the cortical mantle. Postsurgery, ACh-NBM-lesioned rats had less correct responses and more omissions than sham-lesioned rats, which changed parametrically as we increased the attentional demands of the task with decreased target duration. This parametric deficit was found equally for both sensory targets. Accurate detection of visual and olfactory targets was associated specifically with increased LFP coherence, in the beta range, between the PFC and PPC, and with increased beta power in the PPC before the target's appearance in sham-lesioned rats. Readiness-associated changes in brain activity and visual and olfactory target detection were attenuated in the ACh-NBM-lesioned group. Accordingly, ACh may support supramodal attention via modulating activity in a frontoparietal cortical network, orchestrating a state of readiness to enhance target detection. SIGNIFICANCE STATEMENT We examined whether the neurochemical acetylcholine (ACh) contributes to a state of readiness for target detection, by engaging frontoparietal cortical attentional networks independent of modality. We show that ACh supported alerting attention to an impending presentation of either visual or olfactory targets. Using local field potentials, enhanced stimulus detection was associated with an anticipatory increase in power in the beta oscillation range before the target's appearance within the posterior parietal cortex (PPC) as well as increased synchrony, also in beta, between the prefrontal cortex and PPC. These readiness-associated changes in brain activity and behavior were attenuated in rats with reduced cortical ACh. Thus, ACh may act, in a supramodal manner, to prepare frontoparietal cortical attentional networks for target detection.
    Type of Medium: Online Resource
    ISSN: 0270-6474 , 1529-2401
    URL: Article
    DOI: 10.1523/JNEUROSCI.2350-17.2018
    Language: English
    Publisher: Society for Neuroscience
    Publication Date: 2018
    detail.hit.zdb_id: 1475274-8
    SSG: 12
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  • 6
    Online Resource
    Online Resource
    Calcineurin/NFAT Signaling in Activated Astrocytes Drives Network Hyperexcitability in Aβ-Bearing Mice
    Society for Neuroscience ; 2017
    In:  The Journal of Neuroscience Vol. 37, No. 25 ( 2017-06-21), p. 6132-6148
    Details
    In: The Journal of Neuroscience, Society for Neuroscience, Vol. 37, No. 25 ( 2017-06-21), p. 6132-6148
    Type of Medium: Online Resource
    ISSN: 0270-6474 , 1529-2401
    URL: Article
    DOI: 10.1523/JNEUROSCI.0877-17.2017
    Language: English
    Publisher: Society for Neuroscience
    Publication Date: 2017
    detail.hit.zdb_id: 1475274-8
    SSG: 12
    Location Call Number Limitation Availability
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