Age Related Changes in Cerebrovascular Reactivity and Its Relationship to Global Brain Structure

ACKNOWLEDGMENTS This study was funded by Alzheimer’s Research UK (ARUK) and the Aberdeen Biomedical Imaging Centre, University of Aberdeen. GDW, ADM and CS are part of the SINASPE collaboration (Scottish Imaging Network - A Platform for Scientific Excellence www.SINAPSE.ac.uk). The authors thank Gordon Buchan, Baljit Jagpal, Nichola Crouch, Beverly Maclennan and Katrina Klaasen for their help with running the experiment and Dawn Younie and Teresa Morris for their help with recruitment and scheduling. We also thank the residents of Aberdeen and Aberdeenshire, and further afield, for their generous participation.Peer reviewedPublisher PD

Brainstem volume mediates seasonal variation in depressive symptoms : A cross sectional study in the UK Biobank cohort

This research has been conducted using the UK Biobank resource. UK Biobank was established by the Wellcome Trust medical charity, Medical Research Council, Department of Health, Scottish Government and the Northwest Regional Development Agency. This work was supported by the Aberdeen Biomedical Imaging Centre with financial support from the Roland Sutton Academic Trust (RSAT-0039/R/16) and the Saudi Cultural Bureau in contact with Jazan University (PhD scholarship for NAM). Data Availability: The datasets processed and analysed during the current study are available from the online open access UK Biobank repository (https://www.ukbiobank.ac.uk/). This research was conducted under the UK Biobank Resource under Application Number 24089 (PI Waiter).Peer reviewedPublisher PD

Fuzzy approximate entropy analysis of resting state fMRI signal complexity across the adult life span

Acknowledgment The authors would like to acknowledge the work of the International Consortium for Brain Mapping (ICBM) fMRI community in creating the resting state database and making it publicly available within the framework of the 1000 Functional Connectomes project (https://www.nitrc.org/projects/fcon_1000/). M.O. Sokunbi was supported by an MRC grant G1100629.Peer reviewedPreprin

Klotho, APOEε4, cognitive ability, brain size, atrophy and survival : A study in the Aberdeen Birth Cohort of 1936

We thank the cohort participants who contributed to these studies. The study was supported by the University of Aberdeen Development Trust; the UK’s Biotechnology and Biological Sciences Research Council (BBSRC); the Wellcome Trust; the Chief Scientist Office (Scotland); and the Alzheimer’s Research Trust (now ARUK).Peer reviewedPostprin

Potential of Low Dose Leuco-Methylthioninium Bis(Hydromethanesulphonate) (LMTM) Monotherapy for Treatment of Mild Alzheimer’s Disease : Cohort Analysis as Modified Primary Outcome in a Phase III Clinical Trial

The supplementary material is available in the electronic version of this article: http://dx.doi.org/10.3233/JAD-170560. The study was sponsored by TauRx Therapeutics (Singapore). We thank Lon Schneider and Howard Feldman for their contribution to the Scientific Advisory Board. We gratefully acknowledge study investigators and the generosity of study participants. Authors’ disclosures available online (http://j-alz.com/manuscript disclosures/17-0560r3).Peer reviewedPublisher PD

Nonlinear complexity analysis of brain fMRI signals in schizophrenia

Peer reviewedPublisher PD

Variance in brain volume with advancing age: implications for defining the limits of normality

Background: Statistical models of normal ageing brain tissue volumes may support earlier diagnosis of increasingly common, yet still fatal, neurodegenerative diseases. For example, the statistically defined distribution of normal ageing brain tissue volumes may be used as a reference to assess patient volumes. To date, such models were often derived from mean values which were assumed to represent the distributions and boundaries, i.e. percentile ranks, of brain tissue volume. Since it was previously unknown, the objective of the present study was to determine if this assumption was robust, i.e. whether regression models derived from mean values accurately represented the distributions and boundaries of brain tissue volume at older ages. Materials and Methods: We acquired T1-w magnetic resonance (MR) brain images of 227 normal and 219 Alzheimer’s disease (AD) subjects (aged 55-89 years) from publicly available databanks. Using nonlinear regression within both samples, we compared mean and percentile rank estimates of whole brain tissue volume by age. Results: In both the normal and AD sample, mean regression estimates of brain tissue volume often did not accurately represent percentile rank estimates (errors=-74% to 75%). In the normal sample, mean estimates generally underestimated differences in brain volume at percentile ranks below the mean. Conversely, in the AD sample, mean estimates generally underestimated differences in brain volume at percentile ranks above the mean. Differences between ages at the 5th percentile rank of normal subjects were ~39% greater than mean differences in the AD subjects. Conclusions: While more data are required to make true population inferences, our results indicate that mean regression estimates may not accurately represent the distributions of ageing brain tissue volumes. This suggests that percentile rank estimates will be required to robustly define the limits of brain tissue volume in normal ageing and neurodegenerative disease

MRI and the distribution of bone marrow fat in hip osteoarthritis

Grant support This study was supported by an award (Ref: WHMSB-AU119) from the Translational Medicine Research Collaboration – a consortium made up of the Universities of Aberdeen, Dundee, Edinburgh and Glasgow, the four associated NHS Health Boards (Grampian, Tayside, Lothian and Greater Glasgow & Clyde), Scottish Enterprise and Wyeth. The funder played no part in the design, execution, analysis or publication of this paper. Acknowledgements We are grateful to Mrs D. Younie for kindly arranging the imaging sessions and Mrs B.MacLennan (research radiographer) for acquiring the MR images. We also thank Dr S. Galea-Soler, Dr G. Waiter, Dr.Zhiqing Wu, and Dr K. Yoshida for Kellgren-Lawrence grading, help and advice, and Mr G. Buchan for his expertise making the phantoms.Peer reviewedPostprin