Impact of small vessel disease in the brain on gait and balance

Gait and balance impairment is highly prevalent in older people. We aimed to assess whether and how single markers of small vessel disease (SVD) or a combination thereof explain gait and balance function in the elderly. We analysed 678 community-dwelling healthy subjects from the Lothian Birth Cohort 1936 at the age of 71–74 years who had undergone comprehensive risk factor assessment, gait and balance assessment as well as brain MRI. We investigated the impact of individual SVD markers (white matter hyperintensity – WMH, microbleeds, lacunes, enlarged perivascular spaces, brain atrophy) as seen on structural brain MRI and of a global SVD score on the patients’ performance. A regression model revealed that age, sex, and hypertension significantly explained gait speed. Among SVD markers white matter hyperintensity (WMH) score or volume were additional significant and independent predictors of gait speed in the regression model. A similar association was seen with the global SVD score. Our study confirms a negative impact of SVD-related morphologic brain changes on gait speed in addition to age, sex and hypertension independent from brain atrophy. The presence of WMH seems to be the major driving force for SVD on gait impairment in healthy elderly subjects

Freezing of gait associated with a corpus callosum lesion

Freezing of gait (FoG) is a debilitating feature of Parkinson’s disease and other parkinsonian disorders. This case demonstrates a variant of freezing of gait in a non-parkinsonian patient with a lesion of the anterior corpus callosum. The freezing improved with increased upper extremity sensory input, suggesting that compensatory circuits for use of somatosensory inputs from the arms to postural and locomotor centers were intact. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s40734-016-0030-2) contains supplementary material, which is available to authorized users

The relation between total cerebral small vessel disease burden and gait impairment in patients with minor stroke

Acknowledgements We thank the patients and their families, and the staff of the Brain Research Imaging Centre, Edinburgh, where MRI scanning was performed. Funding The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: The Mild Stroke Study-2 follow up study at three years was funded by Chest Heart Stroke Scotland. The original MSS-2 study was funded by the Wellcome Trust (ref. 088134/Z/09/A) and Row Fogo Charitable Trust. The imaging was performed at the Brain Research Imaging Centre Edinburgh, which is supported by the SINAPSE collaboration and the Chief Scientist Office of the Scottish Government (http://www.bric.ed.ac.uk/). The work was supported by European Union Horizon 2020 (EU H2020), PHC03-15, project No 666881, ’SVDs@Target’, and the Fondation Leducq Transatlantic Network of Excellence for Study of Perivascular Spaces in Small Vessel Disease, ref no. 16 CVD 05. The work reflects the views of the authors and not of the funders. CMJL was supported by the Dutch Alzheimer Foundation and VC holds a NHS Research Scotland Fellowship. The work was performed in the Edinburgh Dementia Research Centre in the UK DementiaResearch InitiativePeer reviewedPublisher PD

Arbeitsmarkt und Demographie

Im vorliegenden Beitrag werden die wechselseitigen Beziehungen von demographischen Veränderungen und Arbeitsmarktentwicklungen anhand eines Literaturüberblicks diskutiert. Insbesondere werden die Effekte von demographischen Strukturen und Prozessen auf die Lohnstruktur und auf die Arbeitslosigkeit präsentiert, wobei sowohl Mikro- als auch Makroansätze diskutiert und die Implikationen der Bevölkerungsalterung für den Arbeitsmarkt besprochen werden. In Mikroansätzen werden z.B. altersspezifische Profile der Humankapitalbildung als optimale Lösung eines individuellen Entscheidungsproblems modelliert. Im Gegensatz dazu werden in Makroansätzen die Beziehung von Makrovariablen, z.B. Jugendarbeitslosigkeit und Besetzungsstärke der eigenen Kohorte, modelliert. Schließlich stellen wir verschiedene theoretische Perspektiven vor, welche Effekte arbeitsmarktrelevanter Faktoren auf die Fertilität untersuchen

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke - the second leading cause of death worldwide - were conducted predominantly in populations of European ancestry(1,2). Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis(3), and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach(4), we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry(5). Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries.</p

Stroke genetics informs drug discovery and risk prediction across ancestries

Previous genome-wide association studies (GWASs) of stroke — the second leading cause of death worldwide — were conducted predominantly in populations of European ancestry1,2. Here, in cross-ancestry GWAS meta-analyses of 110,182 patients who have had a stroke (five ancestries, 33% non-European) and 1,503,898 control individuals, we identify association signals for stroke and its subtypes at 89 (61 new) independent loci: 60 in primary inverse-variance-weighted analyses and 29 in secondary meta-regression and multitrait analyses. On the basis of internal cross-ancestry validation and an independent follow-up in 89,084 additional cases of stroke (30% non-European) and 1,013,843 control individuals, 87% of the primary stroke risk loci and 60% of the secondary stroke risk loci were replicated (P < 0.05). Effect sizes were highly correlated across ancestries. Cross-ancestry fine-mapping, in silico mutagenesis analysis3, and transcriptome-wide and proteome-wide association analyses revealed putative causal genes (such as SH3PXD2A and FURIN) and variants (such as at GRK5 and NOS3). Using a three-pronged approach4, we provide genetic evidence for putative drug effects, highlighting F11, KLKB1, PROC, GP1BA, LAMC2 and VCAM1 as possible targets, with drugs already under investigation for stroke for F11 and PROC. A polygenic score integrating cross-ancestry and ancestry-specific stroke GWASs with vascular-risk factor GWASs (integrative polygenic scores) strongly predicted ischaemic stroke in populations of European, East Asian and African ancestry5. Stroke genetic risk scores were predictive of ischaemic stroke independent of clinical risk factors in 52,600 clinical-trial participants with cardiometabolic disease. Our results provide insights to inform biology, reveal potential drug targets and derive genetic risk prediction tools across ancestries