Altered nucleus basalis connectivity predicts treatment response in mild cognitive impairment

Purpose: To determine whether functional connectivity (FC) mapping of nucleus basalis of Meynert (NBM) cholinergic network (hereafter, NBM FC) could provide a biomarker of central cholinergic deficits with predictive potential for response to cholinesterase inhibitor (ChEI) treatment.Materials and Methods: The Alzheimer’s Disease Neuroimaging Initiative (ADNI) was approved by the institutional review boards of all participating sites. All participants and their representatives gave written informed consent prior to data collection. NBM FC was examined in 33 healthy control participants, 102 patients with mild cognitive impairment (MCI), and 33 patients with AD by using resting-state functional MRI data from the ADNI database. NBM FC was compared between groups before and after 6 months of ChEI treatment in MCI. Associations between baseline NBM FC and baseline cognitive performance as well as cognitive outcomes after treatment were investigated.Results: Compared with the healthy control group, NBM FC was decreased in patients with untreated MCI and increased in patients with AD treated with ChEI (corrected P ˂ .05). Global cognition (Alzheimer’s Disease Assessment Scale-Cognitive subscale score) was associated with NBM FC (r = −0.349; P ˂ .001). NBM FC was higher 6 months after ChEI compared with before ChEI in treated MCI (corrected P ˂ .05), but did not change at 6 months in patients with untreated MCI (corrected P ˂ .05). Baseline NBM FC in MCI strongly predicted cognitive outcomes 6 months after ChEI (R2 = 0.458; P = .001).Conclusion: Functional dissociation of the nucleus basalis of Meynert from a cortical network may explain the cognitive deficits in dementia and allow for the selection of individuals who are more likely to respond to cholinesterase inhibitors at early disease stages

Activation induced changes in GABA: functional MRS at 7 T with MEGA-sLASER

Functional magnetic resonance spectroscopy (fMRS) has been used to assess the dynamic metabolic responses of the brain to a physiological stimulus non-invasively. However, only limited information on the dynamic functional response of γ-aminobutyric acid (GABA), the primary inhibitory neurotransmitter in the brain, is available. We aimed to measure the activation-induced changes in GABA unambiguously using a spectral editing method, instead of the conventional direct detection techniques used in previous fMRS studies. The Mescher-Garwood-semi-localised by adiabatic selective refocusing (MEGA-sLASER) sequence was developed at 7 T to obtain the time course of GABA concentration without macromolecular contamination. A significant decrease (−12±5%) in the GABA to total creatine ratio (GABA/tCr) was observed in the motor cortex during a period of 10 minutes of hand-clenching, compared to an initial baseline level (GABA/tCr = 0.11±0.02) at rest. An increase in the Glx (glutamate and glutamine) to tCr ratio was also found, which is in agreement with previous findings. In contrast, no significant changes in NAA/tCr and tCr were detected. With consistent and highly efficient editing performance for GABA detection and the advantage of visually identifying GABA resonances in the spectra, MEGA-sLASER is demonstrated to be an effective method for studying of dynamic changes in GABA at 7 T

Genome-wide Association and Population Genetic Analysis of C-Reactive Protein in African American and Hispanic American Women

C-reactive protein (CRP) is a systemic inflammation marker that predicts future cardiovascular risk. CRP levels are higher in African Americans and Hispanic Americans than in European Americans, but the genetic determinants of CRP in these admixed United States minority populations are largely unknown. We performed genome-wide association studies (GWASs) of 8,280 African American (AA) and 3,548 Hispanic American (HA) postmenopausal women from the Women's Health Initiative SNP Health Association Resource. We discovered and validated a CRP-associated variant of triggering receptors expressed by myeloid cells 2 (TREM2) in chromosomal region 6p21 (p = 10−10). The TREM2 variant associated with higher CRP is common in Africa but rare in other ancestral populations. In AA women, the CRP region in 1q23 contained a strong admixture association signal (p = 10−17), which appears to be related to several independent CRP-associated alleles; the strongest of these is present only in African ancestral populations and is associated with higher CRP. Of the other genomic loci previously associated with CRP through GWASs of European populations, most loci (LEPR, IL1RN, IL6R, GCKR, NLRP3, HNF1A, HNF4A, and APOC1) showed consistent patterns of association with CRP in AA and HA women. In summary, we have identified a common TREM2 variant associated with CRP in United States minority populations. The genetic architecture underlying the CRP phenotype in AA women is complex and involves genetic variants shared across populations, as well as variants specific to populations of African descent

Prospective multicentre evaluation and refinement of an analysis tool for magnetic resonance spectroscopy of childhood cerebellar tumours

AbstractBackgroundA tool for diagnosing childhood cerebellar tumours using magnetic resonance (MR) spectroscopy peak height measurement has been developed based on retrospective analysis of single-centre data.ObjectiveTo determine the diagnostic accuracy of the peak height measurement tool in a multicentre prospective study, and optimise it by adding new prospective data to the original dataset.Materials and methodsMagnetic resonance imaging (MRI) and single-voxel MR spectroscopy were performed on children with cerebellar tumours at three centres. Spectra were processed using standard scanner software and peak heights for N-acetyl aspartate, creatine, total choline and myo-inositol were measured. The original diagnostic tool was used to classify 26 new tumours as pilocytic astrocytoma, medulloblastoma or ependymoma. These spectra were subsequently combined with the original dataset to develop an optimised scheme from 53 tumours in total.ResultsOf the pilocytic astrocytomas, medulloblastomas and ependymomas, 65.4% were correctly assigned using the original tool. An optimized scheme was produced from the combined dataset correctly assigning 90.6%. Rare tumour types showed distinctive MR spectroscopy features.ConclusionThe original diagnostic tool gave modest accuracy when tested prospectively on multicentre data. Increasing the dataset provided a diagnostic tool based on MR spectroscopy peak height measurement with high levels of accuracy for multicentre data

Subclinical thyroid dysfunction and cognitive decline in old age

<p>Background: Subclinical thyroid dysfunction has been implicated as a risk factor for cognitive decline in old age, but results are inconsistent. We investigated the association between subclinical thyroid dysfunction and cognitive decline in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER).</p> <p>Methods: Prospective longitudinal study of men and women aged 70–82 years with pre-existing vascular disease or more than one risk factor to develop this condition (N = 5,154). Participants taking antithyroid medications, thyroid hormone supplementation and/or amiodarone were excluded. Thyroid function was measured at baseline: subclinical hyper- and hypothyroidism were defined as thyroid stimulating hormones (TSH) <0.45 mU/L or >4.50 mU/L respectively, with normal levels of free thyroxine (FT4). Cognitive performance was tested at baseline and at four subsequent time points during a mean follow-up of 3 years, using five neuropsychological performance tests.</p> <p>Results: Subclinical hyperthyroidism and hypothyroidism were found in 65 and 161 participants, respectively. We found no consistent association of subclinical hyper- or hypothyroidism with altered cognitive performance compared to euthyroid participants on the individual cognitive tests. Similarly, there was no association with rate of cognitive decline during follow-up.</p> <p>Conclusion: We found no consistent evidence that subclinical hyper- or hypothyroidism contribute to cognitive impairment or decline in old age. Although our data are not in support of treatment of subclinical thyroid dysfunction to prevent cognitive dysfunction in later life, only large randomized controlled trials can provide definitive evidence.</p&gt

Subclinical thyroid dysfunction and cognitive decline in old age

<p>Background: Subclinical thyroid dysfunction has been implicated as a risk factor for cognitive decline in old age, but results are inconsistent. We investigated the association between subclinical thyroid dysfunction and cognitive decline in the PROspective Study of Pravastatin in the Elderly at Risk (PROSPER).</p> <p>Methods: Prospective longitudinal study of men and women aged 70–82 years with pre-existing vascular disease or more than one risk factor to develop this condition (N = 5,154). Participants taking antithyroid medications, thyroid hormone supplementation and/or amiodarone were excluded. Thyroid function was measured at baseline: subclinical hyper- and hypothyroidism were defined as thyroid stimulating hormones (TSH) <0.45 mU/L or >4.50 mU/L respectively, with normal levels of free thyroxine (FT4). Cognitive performance was tested at baseline and at four subsequent time points during a mean follow-up of 3 years, using five neuropsychological performance tests.</p> <p>Results: Subclinical hyperthyroidism and hypothyroidism were found in 65 and 161 participants, respectively. We found no consistent association of subclinical hyper- or hypothyroidism with altered cognitive performance compared to euthyroid participants on the individual cognitive tests. Similarly, there was no association with rate of cognitive decline during follow-up.</p> <p>Conclusion: We found no consistent evidence that subclinical hyper- or hypothyroidism contribute to cognitive impairment or decline in old age. Although our data are not in support of treatment of subclinical thyroid dysfunction to prevent cognitive dysfunction in later life, only large randomized controlled trials can provide definitive evidence.</p&gt

Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution.

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF <5%) coding novel variants. Pathway/gene set enrichment analyses identified lipid particle, adiponectin, abnormal white adipose tissue physiology and bone development and morphology as important contributors to fat distribution, while cross-trait associations highlight cardiometabolic traits. In functional follow-up analyses, specifically in Drosophila RNAi-knockdowns, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). We implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants

PEXO : a global modeling framework for nanosecond timing, microsecond astrometry, and μm/s radial velocities

54 pages, 2 tables, 19 figures, accepted for publication in ApJS, PEXO is available at https://github.com/phillippro/pexoThe ability to make independent detections of the signatures of exoplanets with complementary telescopes and instruments brings a new potential for robust identification of exoplanets and precision characterization. We introduce PEXO, a package for Precise EXOplanetology to facilitate the efficient modeling of timing, astrometry, and radial velocity data, which will benefit not only exoplanet science but also various astrophysical studies in general. PEXO is general enough to account for binary motion and stellar reflex motions induced by planetary companions and is precise enough to treat various relativistic effects both in the solar system and in the target system. We also model the post-Newtonian barycentric motion for future tests of general relativity in extrasolar systems. We benchmark PEXO with the pulsar timing package TEMPO2 and find that PEXO produces numerically similar results with timing precision of about 1 ns, space-based astrometry to a precision of 1{\mu}as, and radial velocity of 1 {\mu}m/s and improves on TEMPO2 for decade-long timing data of nearby targets, due to its consideration of third-order terms of Roemer delay. PEXO is able to avoid the bias introduced by decoupling the target system and the solar system and to account for the atmospheric effects which set a practical limit for ground-based radial velocities close to 1 cm/s. Considering the various caveats in barycentric correction and ancillary data required to realize cm/s modeling, we recommend the preservation of original observational data. The PEXO modeling package is available at GitHub (https://github.com/phillippro/pexo).Peer reviewe

Characterisation of paediatric brain tumours by their MRS metabolite profiles

1H‐magnetic resonance spectroscopy (MRS) has the potential to improve the noninvasive diagnostic accuracy for paediatric brain tumours. However, studies analysing large, comprehensive, multicentre datasets are lacking, hindering translation to widespread clinical practice. Single‐voxel MRS (point‐resolved single‐voxel spectroscopy sequence, 1.5 T: echo time [TE] 23–37 ms/135–144 ms, repetition time [TR] 1500 ms; 3 T: TE 37–41 ms/135–144 ms, TR 2000 ms) was performed from 2003 to 2012 during routine magnetic resonance imaging for a suspected brain tumour on 340 children from five hospitals with 464 spectra being available for analysis and 281 meeting quality control. Mean spectra were generated for 13 tumour types. Mann–Whitney U‐tests and Kruskal–Wallis tests were used to compare mean metabolite concentrations. Receiver operator characteristic curves were used to determine the potential for individual metabolites to discriminate between specific tumour types. Principal component analysis followed by linear discriminant analysis was used to construct a classifier to discriminate the three main central nervous system tumour types in paediatrics. Mean concentrations of metabolites were shown to differ significantly between tumour types. Large variability existed across each tumour type, but individual metabolites were able to aid discrimination between some tumour types of importance. Complete metabolite profiles were found to be strongly characteristic of tumour type and, when combined with the machine learning methods, demonstrated a diagnostic accuracy of 93% for distinguishing between the three main tumour groups (medulloblastoma, pilocytic astrocytoma and ependymoma). The accuracy of this approach was similar even when data of marginal quality were included, greatly reducing the proportion of MRS excluded for poor quality. Children's brain tumours are strongly characterised by MRS metabolite profiles readily acquired during routine clinical practice, and this information can be used to support noninvasive diagnosis. This study provides both key evidence and an important resource for the future use of MRS in the diagnosis of children's brain tumours