Patterns of progressive atrophy vary with age in Alzheimer's disease patients

Age is not only the greatest risk factor for Alzheimer's disease (AD) but also a key modifier of disease presentation and progression. Here, we investigate how longitudinal atrophy patterns vary with age in mild cognitive impairment (MCI) and AD. Data comprised serial longitudinal 1.5-T magnetic resonance imaging scans from 153 AD, 339 MCI, and 191 control subjects. Voxel-wise maps of longitudinal volume change were obtained and aligned across subjects. Local volume change was then modeled in terms of diagnostic group and an interaction between group and age, adjusted for total intracranial volume, white-matter hyperintensity volume, and apolipoprotein E genotype. Results were significant at p < 0.05 with family-wise error correction for multiple comparisons. An age-by-group interaction revealed that younger AD patients had significantly faster atrophy rates in the bilateral precuneus, parietal, and superior temporal lobes. These results suggest younger AD patients have predominantly posterior progressive atrophy, unexplained by white-matter hyperintensity, apolipoprotein E, or total intracranial volume. Clinical trials may benefit from adapting outcome measures for patient groups with lower average ages, to capture progressive atrophy in posterior cortices

Presumed small vessel disease, imaging and cognition markers in the Alzheimer's Disease Neuroimaging Initiative

MRI-derived features of presumed cerebral small vessel disease are frequently found in Alzheimer’s disease. Influences of such markers on disease-progression measures are poorly understood. We measured markers of presumed small vessel disease (white matter hyperintensity volumes; cerebral microbleeds) on baseline images of newly enrolled individuals in the Alzheimer’s Disease Neuroimaging Initiative cohort (GO and 2) and used linear mixed models to relate these to subsequent atrophy and neuropsychological score change. We also assessed heterogeneity in white matter hyperintensity positioning within biomarker abnormality sequences, driven by the data, using the Subtype and Stage Inference algorithm. This study recruited both sexes and included: controls: [n = 159, mean(SD) age = 74(6) years]; early and late mild cognitive impairment [ns = 265 and 139, respectively, mean(SD) ages =71(7) and 72(8) years, respectively]; Alzheimer’s disease [n = 103, mean(SD) age = 75(8)] and significant memory concern [n = 72, mean(SD) age = 72(6) years]. Baseline demographic and vascular risk-factor data, and longitudinal cognitive scores (Mini-Mental State Examination; logical memory; and Trails A and B) were collected. Whole-brain and hippocampal volume change metrics were calculated. White matter hyperintensity volumes were associated with greater whole-brain and hippocampal volume changes independently of cerebral microbleeds (a doubling of baseline white matter hyperintensity was associated with an increase in atrophy rate of 0.3 ml/year for brain and 0.013 ml/year for hippocampus). Cerebral microbleeds were found in 15% of individuals and the presence of a microbleed, as opposed to none, was associated with increases in atrophy rate of 1.4 ml/year for whole brain and 0.021 ml/year for hippocampus. White matter hyperintensities were predictive of greater decline in all neuropsychological scores, while cerebral microbleeds were predictive of decline in logical memory (immediate recall) and Mini-Mental State Examination scores. We identified distinct groups with specific sequences of biomarker abnormality using continuous baseline measures and brain volume change. Four clusters were found; Group 1 showed early Alzheimer’s pathology; Group 2 showed early neurodegeneration; Group 3 had early mixed Alzheimer’s and cerebrovascular pathology; Group 4 had early neuropsychological score abnormalities. White matter hyperintensity volumes becoming abnormal was a late event for Groups 1 and 4 and an early event for 2 and 3. In summary, white matter hyperintensities and microbleeds were independently associated with progressive neurodegeneration (brain atrophy rates) and cognitive decline (change in neuropsychological scores). Mechanisms involving white matter hyperintensities and progression and microbleeds and progression may be partially separate. Distinct sequences of biomarker progression were found. White matter hyperintensity development was an early event in two sequences

Non-invasive measurements of atherosclerosis in adult cystinosis patients

Item does not contain fulltextBACKGROUND: Cystinosis is characterized by intralysosomal cystine accumulation, causing end stage renal disease around 10 years of age if not treated with cysteamine. Cystine accumulation in blood vessels might increase atheroma formation or arterial stiffness and therefore increase the risk for cardiovascular disease (CVD). This study aimed to investigate the risk for CVD by non-invasive measures of atherosclerosis (NIMA) and to evaluate the effect of cysteamine treatment. PATIENTS AND METHODS: Thirteen Dutch adult cystinosis patients were included. White blood cell (WBC) cystine levels, glomerular filtration rate (GFR) and concommitant medications were obtained from medical records. NIMA included carotid intima-media thickness (cIMT, n = 13), pulse wave velocity (PWV, n = 8) and pulse wave analysis (PWA, n = 6). Results : GFR ranged between 4-95 mL/min/1.73 m(2). All but one patient were treated with cysteamine, mean WBC cystine values ranged between 0.34-1.64 nmol cystine/mg protein, 8 patients had mean WBC cystine levels <1 nmol cystine/mg protein. When compared to healthy subjects, cIMT and PWV levels were above normal values in 1 patient for each measure. PWA measurements showed high augmentation index in three patients who did not receive lipid-lowering medication. When corrected for renal function, cIMT and PWV levels were within the normal range. CONCLUSION: Young adult cystinosis patients treated with cysteamine have no additional risk for CVD when compared to patients with chronic kidney disease of other causes

Genome-wide gene expression analysis supports a developmental model of low temperature tolerance gene regulation in wheat (Triticum aestivum L.)

<p>Abstract</p> <p>Background</p> <p>To identify the genes involved in the development of low temperature (LT) tolerance in hexaploid wheat, we examined the global changes in expression in response to cold of the 55,052 potentially unique genes represented in the Affymetrix Wheat Genome microarray. We compared the expression of genes in winter-habit (winter Norstar and winter Manitou) and spring-habit (spring Manitou and spring Norstar)) cultivars, wherein the locus for the vernalization gene <it>Vrn-A1 </it>was swapped between the parental winter Norstar and spring Manitou in the derived near-isogenic lines winter Manitou and spring Norstar. Global expression of genes in the crowns of 3-leaf stage plants cold-acclimated at 6°C for 0, 2, 14, 21, 38, 42, 56 and 70 days was examined.</p> <p>Results</p> <p>Analysis of variance of gene expression separated the samples by genetic background and by the developmental stage before or after vernalization saturation was reached. Using gene-specific ANOVA we identified 12,901 genes (at <it>p </it>< 0.001) that change in expression with respect to both genotype and the duration of cold-treatment. We examined in more detail a subset of these genes (2,771) where expression was highly influenced by the interaction between these two main factors. Functional assignments using GO annotations showed that genes involved in transport, oxidation-reduction, and stress response were highly represented. Clustering based on the pattern of transcript accumulation identified genes that were up or down-regulated by cold-treatment. Our data indicate that the cold-sensitive lines can up-regulate known cold-responsive genes comparable to that of cold-hardy lines. The levels of expression of these genes were highly influenced by the initial rate and the duration of the gene's response to cold. We show that the <it>Vrn-A1 </it>locus controls the duration of gene expression but not its initial rate of response to cold treatment. Furthermore, we provide evidence that <it>Ta.Vrn-A1 </it>and <it>Ta.Vrt1 </it>originally hypothesized to encode for the same gene showed different patterns of expression and therefore are distinct.</p> <p>Conclusion</p> <p>This study provides novel insight into the underlying mechanisms that regulate the expression of cold-responsive genes in wheat. The results support the developmental model of LT tolerance gene regulation and demonstrate the complex genotype by environment interactions that determine LT adaptation in winter annual cereals.</p

Systematic review of the evidence relating FEV1 decline to giving up smoking

<p>Abstract</p> <p>Background</p> <p>The rate of forced expiratory volume in 1 second (FEV₁) decline ("beta") is a marker of chronic obstructive pulmonary disease risk. The reduction in beta after quitting smoking is an upper limit for the reduction achievable from switching to novel nicotine delivery products. We review available evidence to estimate this reduction and quantify the relationship of smoking to beta.</p> <p>Methods</p> <p>Studies were identified, in healthy individuals or patients with respiratory disease, that provided data on beta over at least 2 years of follow-up, separately for those who gave up smoking and other smoking groups. Publications to June 2010 were considered. Independent beta estimates were derived for four main smoking groups: never smokers, ex-smokers (before baseline), quitters (during follow-up) and continuing smokers. Unweighted and inverse variance-weighted regression analyses compared betas in the smoking groups, and in continuing smokers by amount smoked, and estimated whether beta or beta differences between smoking groups varied by age, sex and other factors.</p> <p>Results</p> <p>Forty-seven studies had relevant data, 28 for both sexes and 19 for males. Sixteen studies started before 1970. Mean follow-up was 11 years. On the basis of weighted analysis of 303 betas for the four smoking groups, never smokers had a beta 10.8 mL/yr (95% confidence interval (CI), 8.9 to 12.8) less than continuing smokers. Betas for ex-smokers were 12.4 mL/yr (95% CI, 10.1 to 14.7) less than for continuing smokers, and for quitters, 8.5 mL/yr (95% CI, 5.6 to 11.4) less. These betas were similar to that for never smokers. In continuing smokers, beta increased 0.33 mL/yr per cigarette/day. Beta differences between continuing smokers and those who gave up were greater in patients with respiratory disease or with reduced baseline lung function, but were not clearly related to age or sex.</p> <p>Conclusion</p> <p>The available data have numerous limitations, but clearly show that continuing smokers have a beta that is dose-related and over 10 mL/yr greater than in never smokers, ex-smokers or quitters. The greater decline in those with respiratory disease or reduced lung function is consistent with some smokers having a more rapid rate of FEV₁decline. These results help in designing studies comparing continuing smokers of conventional cigarettes and switchers to novel products.</p

Systematic review with meta-analysis of the epidemiological evidence relating smoking to COPD, chronic bronchitis and emphysema

<p>Abstract</p> <p>Background</p> <p>Smoking is a known cause of the outcomes COPD, chronic bronchitis (CB) and emphysema, but no previous systematic review exists. We summarize evidence for various smoking indices.</p> <p>Methods</p> <p>Based on MEDLINE searches and other sources we obtained papers published to 2006 describing epidemiological studies relating incidence or prevalence of these outcomes to smoking. Studies in children or adolescents, or in populations at high respiratory disease risk or with co-existing diseases were excluded. Study-specific data were extracted on design, exposures and outcomes considered, and confounder adjustment. For each outcome RRs/ORs and 95% CIs were extracted for ever, current and ex smoking and various dose response indices, and meta-analyses and meta-regressions conducted to determine how relationships were modified by various study and RR characteristics.</p> <p>Results</p> <p>Of 218 studies identified, 133 provide data for COPD, 101 for CB and 28 for emphysema. RR estimates are markedly heterogeneous. Based on random-effects meta-analyses of most-adjusted RR/ORs, estimates are elevated for ever smoking (COPD 2.89, CI 2.63-3.17, n = 129 RRs; CB 2.69, 2.50-2.90, n = 114; emphysema 4.51, 3.38-6.02, n = 28), current smoking (COPD 3.51, 3.08-3.99; CB 3.41, 3.13-3.72; emphysema 4.87, 2.83-8.41) and ex smoking (COPD 2.35, 2.11-2.63; CB 1.63, 1.50-1.78; emphysema 3.52, 2.51-4.94). For COPD, RRs are higher for males, for studies conducted in North America, for cigarette smoking rather than any product smoking, and where the unexposed base is never smoking any product, and are markedly lower when asthma is included in the COPD definition. Variations by sex, continent, smoking product and unexposed group are in the same direction for CB, but less clearly demonstrated. For all outcomes RRs are higher when based on mortality, and for COPD are markedly lower when based on lung function. For all outcomes, risk increases with amount smoked and pack-years. Limited data show risk decreases with increasing starting age for COPD and CB and with increasing quitting duration for COPD. No clear relationship is seen with duration of smoking.</p> <p>Conclusions</p> <p>The results confirm and quantify the causal relationships with smoking.</p

Thalamus involvement in genetic frontotemporal dementia assessed using structural and diffusion MRI: a GENFI study

Data availability: Anonymized data may be shared upon reasonable request from a qualified academic investigator for the purpose of replication of procedures and results detailed in this article.Supplementary data are available online at: https://academic.oup.com/braincomms/article/7/6/fcaf420/8301026#supplementary-data .Thalamic subregions are commonly, but variably, affected by different forms of frontotemporal dementia. We aimed to better characterize thalamic subregional involvement in genetic frontotemporal dementia with a recently published thalamus segmentation tool that utilizes structural and diffusion MRI, offering additional assessment of mean diffusivity and a more fine-grained analysis of the pulvinar specifically compared to previous studies. Using this tool, we performed thalamus segmentations in MRI scans from C9orf72, GRN and MAPT mutation carriers and mutation non-carriers with suitable 3-Tesla MRI cross-sectional data from the GENetic Frontotemporal dementia Initiative. Mutation carriers were divided according to their genetic group and Clinical Dementia Rating® Dementia Staging Instrument plus National Alzheimer’s Coordinating Center Behaviour and Language Domains global score (0 or 0.5: presymptomatic/prodromal stage, 1 or higher: symptomatic stage). Following stringent quality control and harmonization across sites and scanners, we compared volumes and mean diffusivity values of thalamic subregions in C9orf72 (47 presymptomatic, 10 symptomatic), GRN (57 presymptomatic, 11 symptomatic) and MAPT (31 presymptomatic, 12 symptomatic) mutation carriers to those in 109 mutation non-carriers with analyses of covariance including age and sex (and total intracranial volume for volumetric comparisons) as covariates. Presymptomatic C9orf72 expansion carriers showed smaller volumes (3–8% difference from non-carriers) and higher mean diffusivity (2–5% difference from non-carriers) for several thalamic subregions, including all pulvinar subdivisions. We found subtly larger volumes of the ventral anterior subregion and the non-medial pulvinar (3% difference from non-carriers for both) in presymptomatic GRN mutation carriers, and of the anteroventral subregion (5% difference from non-carriers) in presymptomatic MAPT mutation carriers. Symptomatic mutation carriers in all three genetic groups showed significantly smaller volumes and widespread higher mean diffusivity of thalamic subregions compared with non-carriers, which were overall most prominent in subregions involved in associative and limbic functions (the midline, medial pulvinar, anteroventral, mediodorsal, laterodorsal and lateral posterior subregions). Notably smaller volume (12–23% difference from non-carriers) and higher mean diffusivity (16–23% difference from non-carriers) of the most medial part of the medial pulvinar was a shared feature across the three genetic groups at the symptomatic stage. Overall, our study confirms that thalamic subregions are affected in genetic frontotemporal dementia and identifies prominent involvement of the most medial part of the medial pulvinar as a potential unifying feature in the variable pattern of thalamic subregional involvement across the main genetic groups.This work was primarily funded by Alzheimer’s Research UK (ARUK-IRG2019A003). S.S. and D.C.A. are also supported by the Wellcome Trust (221915). D.C.A. and H.F.J.T. are also supported by the UK Medical Research Council (MR/W031566/1, EP/Y028856/1) and the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre. M.B. is supported by a Fellowship award from the Alzheimer’s Society, UK (AS-JF-19a-004-517). M.B. acknowledges the support of NVIDIA Corporation with the donation of the Titan V GPU used for part of the analyses in this research. J.E.I. is also supported by the National Institute of Health (1RF1MH123195, 1R01AG070988, 1UM1MH130981, 1RF1AG080371, 1R21NS138995). J.B.R. has received funding from the Wellcome Trust (103838; 220258) and is supported by the Cambridge University Centre for Frontotemporal Dementia, the UK Medical Research Council (MC_UU_00030/14; MR/T033371/1) and the National Institute for Health Research Cambridge Biomedical Research Centre (NIHR203312: BRC-1215-20014), and the Holt Fellowship. The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care. D.M.C. is supported by the UK Dementia Research Institute which receives its funding from Dementia Research Institute Ltd, funded by the UK Medical Research Council, Alzheimer’s Society and Alzheimer’s Research UK, Alzheimer’s Association (SG-666374-UK BIRTH COHORT) and the National Institute for Health and Care Research University College London Hospitals Biomedical Research Centre. J.C.V.S., L.C.J. and H.S. are supported by the Dioraphte Foundation grant 09-02-03-00, Association for Frontotemporal Dementias Research Grant 2009, Netherlands Organization for Scientific Research grant HCMI 056-13-018, ZonMw Memorabel (Deltaplan Dementie, project number 733 051 042), ZonMw Onderzoeksprogramma Dementie (YOD-INCLUDED, project number 10510032120002), Alzheimer Nederland and the Bluefield Project. R.S.-V. is supported by Alzheimer’s Research UK Clinical Research Training Fellowship (ARUK-CRF2017B-2) and has received funding from Fundació Marató de TV3, Spain (grant no. 20143810). C.G. received funding from EU Joint Programme-Neurodegenerative Disease Research-Prefrontals Vetenskapsrådet Dnr 529-2014-7504, Vetenskapsrådet 2019-0224, Vetenskapsrådet 2015-02926, Vetenskapsrådet 2018-02754, the Swedish FTD Inititative-Schörling Foundation, Alzheimer Foundation, Brain Foundation, Dementia Foundation and Region Stockholm ALF-project. D.G. received support from the EU Joint Programme-Neurodegenerative Disease Research and the Italian Ministry of Health (PreFrontALS) grant 733051042. R.V. has received funding from the Mady Browaeys Fund for Research into Frontotemporal Dementia. J.L. received funding for this work from the Deutsche Forschungsgemeinschaft German Research Foundation under Germany’s Excellence Strategy within the framework of the Munich Cluster for Systems Neurology (EXC 2145 SyNergy—ID 390857198). M.O. has received funding from Germany’s Federal Ministry of Education and Research (BMBF). E.F. has received funding from a Canadian Institute of Health Research grant #327387. M.M. has received funding from a Canadian Institute of Health Research operating grant and the Weston Brain Institute and Ontario Brain Institute. F.M. is supported by the Tau Consortium and has received funding from the Carlos III Health Institute (PI19/01637). J.D.R. is supported by the Bluefield Project and the National Institute for Health and Care Research, University College London Hospitals Biomedical Research Centre, and has received funding from a UK Medical Research Council Clinician Scientist Fellowship (MR/M008525/1) and a Miriam Marks Brain Research UK Senior Fellowship. Several authors of this publication (J.C.V.S., M.S., R.V., A.d.M., M.O., R.V. and J.D.R.) are members of the European Reference Network for Rare Neurological Diseases (ERN-RND)—Project ID No 739510. This work was also supported by the EU Joint Programme-Neurodegenerative Disease Research GENFI-PROX grant [2019-02248; to J.D.R., M.O., B.B., C.G., J.C.V.S. and M.S.]

Concurrent validity of the PSYCH-6, a very short scale for detecting anxiety and depression, among oncology outpatients

Objective: To improve the acceptability of screening for depression and anxiety among patients with cancer there is a need for scales that are both very short and accurate. To date no very short questionnaire has been found to provide optimal performance for screening in oncology populations and other candidates must be examined. This study examined the concurrent validity of a relatively new, very short scale, the six item PSYCH-6 subscale of the Somatic and Psychological Health Report (SPHERE-12), in an oncology outpatient population. Methods: Cross-sectional survey of 340 oncology outpatients attending a regional hospital in Newcastle, Australia. The performance of the PSYCH-6 against the Hospital Anxiety and Depression Scale (HADS) was evaluated using correlation, Cohen's kappa, positive agreement and negative agreement. Results: The PSYCH-6 subscale of the SPHERE-12, at a cut-off point of 3, had substantial agreement with the total score of the HADS (HADS-T; κ = 0.73, p < 0.001). Negative agreement (0.92) was marginally higher than positive agreement (0.80). Conclusions: The PSYCH-6 scale of the SPHERE-12 at a cut-off point of 3 is an equivalent instrument to the HADS-T for detecting cases and excluding non-cases of anxiety and depression and is suitable for deployment in oncology populations