Age-related cerebral white matter hyperintensities(WMHs)are a ubiquitous finding on MRI in older individuals.They are associated with cognitive decline,dementia,disability and death.Changes are thought to result from ...Age-related cerebral white matter hyperintensities(WMHs)are a ubiquitous finding on MRI in older individuals.They are associated with cognitive decline,dementia,disability and death.Changes are thought to result from small infarcts secondary to arteriosclerosis.However,the anatomic distribution of WMHs is often non-arterial,and one that parallels the deep venous system.There is discrepant evidence for the role of conventional vascular risk factors such as hypertension,carotid atherosclerosis and diabetes in age-related WMHs.Interventions targeting these vascular risk factors lack efficacy in preventing the progression of disease.There is evidence for age-related hemodynamic cervical venous dysfunction resulting in reduced internal jugular vein venous compliance,venous dilatation and venous reflux.Increased blood-brain barrier(BBB)permeability is also noted with aging.Both hemodynamic venous dysfunction and increased BBB permeability are associated with WMHs.It is proposed that age-related WMHs are a sequalae of venous dysfunction.Venous dysfunction results initially in increased transmission of venous pressures to the brain.Subsequent BBB disruption leads to increased permeability with progression to end-stage findings of age-related WMHs.展开更多
Objective Exosomal long noncoding RNAs(lnc RNAs) are the key to diagnosing and treating various diseases. This study aimed to investigate the diagnostic value of plasma exosomal lnc RNAs in white matter hyperintensiti...Objective Exosomal long noncoding RNAs(lnc RNAs) are the key to diagnosing and treating various diseases. This study aimed to investigate the diagnostic value of plasma exosomal lnc RNAs in white matter hyperintensities(WMH).Methods We used high-throughput sequencing to determine the differential expression(DE) profiles of lnc RNAs in plasma exosomes from WMH patients and controls. The sequencing results were verified in a validation cohort using q RT-PCR. The diagnostic potential of candidate exosomal lnc RNAs was proven by binary logistic analysis and receiver operating characteristic(ROC) curves. The diagnostic value of DE exo-lnc RNAs was determined by the area under the curve(AUC). The WMH group was then divided into subgroups according to the Fazekas scale and white matter lesion site, and the correlation of DE exo-lnc RNAs in the subgroup was evaluated.Results In our results, four DE exo-lnc RNAs were identified, and ROC curve analysis revealed that exolnc_011797 and exo-lnc_004326 exhibited diagnostic efficacy for WMH. Furthermore, WMH subgroup analysis showed exo-lnc_011797 expression was significantly increased in Fazekas 3 patients and was significantly elevated in patients with paraventricular matter hyperintensities.Conclusion Plasma exosomal lnc RNAs have potential diagnostic value in WMH. Moreover, exolnc_011797 is considered to be a predictor of the severity and location of WMH.展开更多
Background and Purpose - MRI segmentation and mapping techniques were used to assess evidence in support of categorical distinctions between periventricular white matter hyperintensities (PVWMH) and deep WMH (DWMH). Q...Background and Purpose - MRI segmentation and mapping techniques were used to assess evidence in support of categorical distinctions between periventricular white matter hyperintensities (PVWMH) and deep WMH (DWMH). Qualitative MRI studies generally identify 2 categories of WMH on the basis of anatomical localization. Separate pathophysiologies and behavioral consequences are often attributed to these 2 classes of WMH. However, evidence to support these empirical distinctions has not been rigorously sought. Methods - MRI analysis of 55 subjects included quantification of WMH volume, mapping onto a common anatomical image, and spatial localization of each WMH voxel. WMH locations were then divided into PVWMH and DWMH on the basis of distance from the lateral ventricles and correlations, with total WMH volume determined. Periventricular distance histograms of WMH voxels were also calculated. Results - PVWMH and DWMH were highly correlated with total WMH (R2 > 0.95) and with each other (R2 >0.87). Mapping of all WMH revealed smooth expansion from around central cerebrospinal fluid spaces into more distal cerebral white matter with increasing WMH volume. Conclusion - PVWMH, DWMH, and total WMH are highly correlated with each other. Moreover, spatial analysis failed to identify distinct subpopulations for PVWMH and DWMH. These results suggest that categorical distinctions between PVWMH and DWMH may be arbitrary, and conclusions regarding individual relationships between causal factors or behavior for PVWMH and DWMH may more accurately reflect total WMH volume relationships.展开更多
A mathematical model was developed to predict the risk of having a stroke as a person ages. The age component was derived from the concept that the change in risk of stroke with age is a function of the current risk o...A mathematical model was developed to predict the risk of having a stroke as a person ages. The age component was derived from the concept that the change in risk of stroke with age is a function of the current risk of developing a stroke. This equation modeled the trend with age reported in the literature for two different data sets with R<sup>2</sup> values of 0.97 or better for both men and women. A second equation of a similar nature was developed to predict the accumulation of white matter hyperintensities, WMH, as a person ages. It appears that each equation includes a set of common risk factors. This set of common risk factors allows an individual’s risk for stroke to be based on measured WMH. A third equation links WMH with the risk of developing a stroke. This equation allows an individual to use measured WMH from brain scans to predict the future risk of developing a stroke. In theory, a person with a relatively high measurement of WMH can project future risk for stroke with age and use counter measures such as exercise and medications to keep other risk factors low as a person continues to age.展开更多
Background White matter hyperintensity(WMH)progression is well documented;WMH regression is more contentious,which might reflect differences in defining WMH change.We compared four existing WMH change definitions in o...Background White matter hyperintensity(WMH)progression is well documented;WMH regression is more contentious,which might reflect differences in defining WMH change.We compared four existing WMH change definitions in one population to determine the effect of definition on WMH regression.Methods We recruited patients with minor non-disabling ischaemic stroke who underwent MRI 1-3 months after stroke and 1 year later.We assessed WMH volume(in absolute mL and%intracranial volume)and applied four different definitions,including two thresholds(based on SD or mL),percentile and quintile approaches.Results In 198 participants,mean age 65.5(SD=11.13),baseline WMH volume was 15.46 mL(SD=19.2),the mean net WMH volume change was 0.98 mL(SD=2.84),range-7.98 to+12.84 mL.Proportion regressing/stable/progressing WMH were threshold 1(SD),29.8%/55.6%/14.6%;threshold 2(mL),29.8%/16.7%/53.5%;percentile approach,28.3%/21.2%/50.5%.The quintile approach includes five groups with quintile 3 reflecting no change(N=40),quintiles 1 and 2 any WMH decrease(N=80)and quintiles 4 and 5 any WMH increase(N=78).Conclusions Different WMH change definitions cause big differences in how participants are categorised;additionally,non-normal WMH distribution precludes use of some definitions.Consistent use of an appropriate definition would facilitate data comparisons,particularly in clinical trials of potential WMH treatments.展开更多
Cerebral small vessel disease(SVD)involves ischemic white matter damage and choroid plexus(CP)dysfunction for cerebrospinal fluid(CSF)production.Given the vascular and CSF links between the eye and brain,this study ex...Cerebral small vessel disease(SVD)involves ischemic white matter damage and choroid plexus(CP)dysfunction for cerebrospinal fluid(CSF)production.Given the vascular and CSF links between the eye and brain,this study explored whether retinal vascular morphology can indicate cerebrovascular injury and CP dysfunction in SVD.We assessed SVD burden using imaging phenotypes like white matter hyperintensities(WMH),perivascular spaces,lacunes,and microbleeds.Cerebrovascular injury was quantified by WMH volume and peak width of skeletonized mean diffusivity(PSMD),while CP volume measured its dysfunction.Retinal vascular markers were derived from fundus images,with associations analyzed using generalized linear models and Pearson correlations.Path analysis quantified contributions of cerebrovascular injury and CP volume to retinal changes.Support vector machine models were developed to predict SVD severity using retinal and demographic data.Among 815 participants,578 underwent ocular imaging.Increased SVD burden markedly correlated with both cerebral and retinal biomarkers,with retinal alterations equally influenced by cerebrovascular damage and CP enlargement.Machine learning models showed robust predictive power for severe SVD burden(AUC was 0.82),PSMD(0.81),WMH volume(0.77),and CP volume(0.80).These findings suggest that retinal imaging could serve as a cost-effective,noninvasive tool for SVD screening based on vascular and CSF connections.展开更多
基金Corresponding to:Anish Kapadia.Department of Medical Imaging,University of Toronto,263 McCaul Street,4th Floor,Ontario,Canada.E-mail:anish.kapadia@mail.utoronto.ca。
文摘Age-related cerebral white matter hyperintensities(WMHs)are a ubiquitous finding on MRI in older individuals.They are associated with cognitive decline,dementia,disability and death.Changes are thought to result from small infarcts secondary to arteriosclerosis.However,the anatomic distribution of WMHs is often non-arterial,and one that parallels the deep venous system.There is discrepant evidence for the role of conventional vascular risk factors such as hypertension,carotid atherosclerosis and diabetes in age-related WMHs.Interventions targeting these vascular risk factors lack efficacy in preventing the progression of disease.There is evidence for age-related hemodynamic cervical venous dysfunction resulting in reduced internal jugular vein venous compliance,venous dilatation and venous reflux.Increased blood-brain barrier(BBB)permeability is also noted with aging.Both hemodynamic venous dysfunction and increased BBB permeability are associated with WMHs.It is proposed that age-related WMHs are a sequalae of venous dysfunction.Venous dysfunction results initially in increased transmission of venous pressures to the brain.Subsequent BBB disruption leads to increased permeability with progression to end-stage findings of age-related WMHs.
文摘Objective Exosomal long noncoding RNAs(lnc RNAs) are the key to diagnosing and treating various diseases. This study aimed to investigate the diagnostic value of plasma exosomal lnc RNAs in white matter hyperintensities(WMH).Methods We used high-throughput sequencing to determine the differential expression(DE) profiles of lnc RNAs in plasma exosomes from WMH patients and controls. The sequencing results were verified in a validation cohort using q RT-PCR. The diagnostic potential of candidate exosomal lnc RNAs was proven by binary logistic analysis and receiver operating characteristic(ROC) curves. The diagnostic value of DE exo-lnc RNAs was determined by the area under the curve(AUC). The WMH group was then divided into subgroups according to the Fazekas scale and white matter lesion site, and the correlation of DE exo-lnc RNAs in the subgroup was evaluated.Results In our results, four DE exo-lnc RNAs were identified, and ROC curve analysis revealed that exolnc_011797 and exo-lnc_004326 exhibited diagnostic efficacy for WMH. Furthermore, WMH subgroup analysis showed exo-lnc_011797 expression was significantly increased in Fazekas 3 patients and was significantly elevated in patients with paraventricular matter hyperintensities.Conclusion Plasma exosomal lnc RNAs have potential diagnostic value in WMH. Moreover, exolnc_011797 is considered to be a predictor of the severity and location of WMH.
文摘Background and Purpose - MRI segmentation and mapping techniques were used to assess evidence in support of categorical distinctions between periventricular white matter hyperintensities (PVWMH) and deep WMH (DWMH). Qualitative MRI studies generally identify 2 categories of WMH on the basis of anatomical localization. Separate pathophysiologies and behavioral consequences are often attributed to these 2 classes of WMH. However, evidence to support these empirical distinctions has not been rigorously sought. Methods - MRI analysis of 55 subjects included quantification of WMH volume, mapping onto a common anatomical image, and spatial localization of each WMH voxel. WMH locations were then divided into PVWMH and DWMH on the basis of distance from the lateral ventricles and correlations, with total WMH volume determined. Periventricular distance histograms of WMH voxels were also calculated. Results - PVWMH and DWMH were highly correlated with total WMH (R2 > 0.95) and with each other (R2 >0.87). Mapping of all WMH revealed smooth expansion from around central cerebrospinal fluid spaces into more distal cerebral white matter with increasing WMH volume. Conclusion - PVWMH, DWMH, and total WMH are highly correlated with each other. Moreover, spatial analysis failed to identify distinct subpopulations for PVWMH and DWMH. These results suggest that categorical distinctions between PVWMH and DWMH may be arbitrary, and conclusions regarding individual relationships between causal factors or behavior for PVWMH and DWMH may more accurately reflect total WMH volume relationships.
文摘A mathematical model was developed to predict the risk of having a stroke as a person ages. The age component was derived from the concept that the change in risk of stroke with age is a function of the current risk of developing a stroke. This equation modeled the trend with age reported in the literature for two different data sets with R<sup>2</sup> values of 0.97 or better for both men and women. A second equation of a similar nature was developed to predict the accumulation of white matter hyperintensities, WMH, as a person ages. It appears that each equation includes a set of common risk factors. This set of common risk factors allows an individual’s risk for stroke to be based on measured WMH. A third equation links WMH with the risk of developing a stroke. This equation allows an individual to use measured WMH from brain scans to predict the future risk of developing a stroke. In theory, a person with a relatively high measurement of WMH can project future risk for stroke with age and use counter measures such as exercise and medications to keep other risk factors low as a person continues to age.
基金Supported by the UK Dementia Research Institute[award number UK DRI-4002]through UK DRI Ltd.Principally funded by the UK Medical Research Council(ACCJ,CA,DJG,JMW)The Row Fogo Centre for Research into Aging and the Brain(ACCJ,CA,DJG,MVH,JMW)+12 种基金the Fondation Leducq Network(16 CVD 05)Stroke Association‘Small Vessel Disease-Spotlight on Symptoms(SVD-SOS)’(SAPG 19n100068)British Heart Foundation(RE/18/5/34216)Alzheimer’s Society(ref 486(AS-CP 18b 001))University of Edinburgh College of Medicine and Veterinary Medicine(ACCJ)Wellcome trust(DJG).Biotechnology and Biological Sciences Research Council,and the Economic and Social Research Council(BB/W008793/1SMM)The Scottish Chief Scientist Office(CAF/18/08UC)Mexican National Council of Science and Technology(CONACYT,2021-000007-01EXTF 00234)the Rowling Clinic(CA).NHS Lothian Research and Development Office(MJT)The Stroke Association(SA PDF 18\100026,SA PDF 23\100007,TSA LECT 2015/04,16 VAD 07SW,MSS,FND).
文摘Background White matter hyperintensity(WMH)progression is well documented;WMH regression is more contentious,which might reflect differences in defining WMH change.We compared four existing WMH change definitions in one population to determine the effect of definition on WMH regression.Methods We recruited patients with minor non-disabling ischaemic stroke who underwent MRI 1-3 months after stroke and 1 year later.We assessed WMH volume(in absolute mL and%intracranial volume)and applied four different definitions,including two thresholds(based on SD or mL),percentile and quintile approaches.Results In 198 participants,mean age 65.5(SD=11.13),baseline WMH volume was 15.46 mL(SD=19.2),the mean net WMH volume change was 0.98 mL(SD=2.84),range-7.98 to+12.84 mL.Proportion regressing/stable/progressing WMH were threshold 1(SD),29.8%/55.6%/14.6%;threshold 2(mL),29.8%/16.7%/53.5%;percentile approach,28.3%/21.2%/50.5%.The quintile approach includes five groups with quintile 3 reflecting no change(N=40),quintiles 1 and 2 any WMH decrease(N=80)and quintiles 4 and 5 any WMH increase(N=78).Conclusions Different WMH change definitions cause big differences in how participants are categorised;additionally,non-normal WMH distribution precludes use of some definitions.Consistent use of an appropriate definition would facilitate data comparisons,particularly in clinical trials of potential WMH treatments.
基金partially supported by the R&D Program of Beijing Municipal Education Commission(KM202410025017)National Natural Science Foundation of China(62171297,61931013,and 82272072)+3 种基金Natural Science Foundation of Beijing Municipality(7242267)Beijing Scholars Program([2015]160)Nature Cultivation Fund of Capital Medical University(PYZ23035)Research Incubation Fund of Yanjing Medical College of Capital Medical University(23kypyz02).
文摘Cerebral small vessel disease(SVD)involves ischemic white matter damage and choroid plexus(CP)dysfunction for cerebrospinal fluid(CSF)production.Given the vascular and CSF links between the eye and brain,this study explored whether retinal vascular morphology can indicate cerebrovascular injury and CP dysfunction in SVD.We assessed SVD burden using imaging phenotypes like white matter hyperintensities(WMH),perivascular spaces,lacunes,and microbleeds.Cerebrovascular injury was quantified by WMH volume and peak width of skeletonized mean diffusivity(PSMD),while CP volume measured its dysfunction.Retinal vascular markers were derived from fundus images,with associations analyzed using generalized linear models and Pearson correlations.Path analysis quantified contributions of cerebrovascular injury and CP volume to retinal changes.Support vector machine models were developed to predict SVD severity using retinal and demographic data.Among 815 participants,578 underwent ocular imaging.Increased SVD burden markedly correlated with both cerebral and retinal biomarkers,with retinal alterations equally influenced by cerebrovascular damage and CP enlargement.Machine learning models showed robust predictive power for severe SVD burden(AUC was 0.82),PSMD(0.81),WMH volume(0.77),and CP volume(0.80).These findings suggest that retinal imaging could serve as a cost-effective,noninvasive tool for SVD screening based on vascular and CSF connections.
