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While some brain atrophy is expected in aging, high levels of atrophy in the white matter and high enlargement in the ventricles are associated with earlier progression from normal cognition to MCI, the study found. The researchers also identified diabetes and atypical levels of amyloid beta protein in the cerebrospinal fluid as risk factors for brain atrophy and MCI.
For their research, published online on JAMA Network Open, Yuto Uchida, MD, PhD, and his colleagues at the Johns Hopkins University School of Medicine in Baltimore, Maryland, looked at data for 185 individuals (mean age, 55.4 years; 63% women) who were cognitively normal at baseline and followed for a median of 20 years.
All had been enrolled in a longitudinal cohort study on biomarkers of cognitive decline conducted at Johns Hopkins. Each participant underwent a median of five structural MRI studies during the follow-up period as well as annual cognitive testing. Altogether 60 individuals developed MCI, with eight of them progressing to dementia.
“We hypothesized that annual rates of change of segmental brain volumes would be associated with vascular risk factors among middle-aged and older adults and that these trends would be associated with the progression from normal cognition to MCI,” Uchida and colleagues wrote.
Uniquely Long Follow-Up
Most longitudinal studies using structural MRI count a decade or less of follow-up, the study authors noted. This makes it difficult to discern whether the annual rates of change of brain volumes are affected by vascular risk factors or are useful in predicting MCI, they said. Individual differences in brain aging make population-based studies less informative.
This study’s long timeframe allowed for tracking of brain changes “on an individual basis, which facilitates the differentiation between interindividual and intraindividual variations and leads to more accurate estimations of rates of brain atrophy,” Uchida and colleagues wrote.
People with high levels of atrophy in the white matter and enlargement in the ventricles saw earlier progression to MCI (hazard ratio [HR], 1.86; 95% CI, 1.24-2.49; P = .001). Diabetes mellitus was associated with progression to MCI (HR, 1.41; 95% CI, 1.06-1.76; P = .04), as was a low CSF Abeta42:Abeta40 ratio (HR, 1.48; 95% CI, 1.09-1.88; P = .04).
People with both diabetes and an abnormal amyloid profile were even more vulnerable to developing MCI (HR, 1.55; 95% CI, 1.13-1.98; P = .03). This indicated “a synergic association of diabetes and amyloid pathology with MCI progression,” Uchida and colleagues wrote, noting that insulin resistance has been shown to promote the formation of amyloid plaques, a hallmark of Alzheimer’s disease.
The findings also underscore that “white matter volume changes are closely associated with cognitive function in aging, suggesting that white matter degeneration may play a crucial role in cognitive decline,” the authors noted.
Uchida and colleagues acknowledged the modest size and imbalanced sex ratio of their study cohort as potential weaknesses, as well as the fact that the imaging technologies had changed over the course of the study. Most of the participants were White with family histories of dementia.
Findings May Lead to Targeted Interventions
In an editorial comment accompanying Uchida and colleagues’ study, Shohei Fujita, MD, PhD, of Massachusetts General Hospital, Boston, said that, while a more diverse population sample would be desirable and should be sought for future studies, the results nonetheless highlight “the potential of long-term longitudinal brain MRI datasets in elucidating the interplay of risk factors underlying cognitive decline and the potential benefits of controlling diabetes to reduce the risk of progression” along the Alzheimer’s disease continuum.
The findings may prove informative, Fujita said, in developing “targeted interventions for those most susceptible to progressive brain changes, potentially combining lifestyle modifications and pharmacological treatments.”
Uchida and colleagues’ study was funded by the Alzheimer’s Association, the National Alzheimer’s Coordinating Center, and the National Institutes of Health. The study’s corresponding author, Kenichi Oishi, disclosed funding from the Richman Family Foundation, Richman, the Sharp Family Foundation, and others. Uchida and Fujita reported no relevant financial conflicts of interest.
A version of this article first appeared on Medscape.com.
While some brain atrophy is expected in aging, high levels of atrophy in the white matter and high enlargement in the ventricles are associated with earlier progression from normal cognition to MCI, the study found. The researchers also identified diabetes and atypical levels of amyloid beta protein in the cerebrospinal fluid as risk factors for brain atrophy and MCI.
For their research, published online on JAMA Network Open, Yuto Uchida, MD, PhD, and his colleagues at the Johns Hopkins University School of Medicine in Baltimore, Maryland, looked at data for 185 individuals (mean age, 55.4 years; 63% women) who were cognitively normal at baseline and followed for a median of 20 years.
All had been enrolled in a longitudinal cohort study on biomarkers of cognitive decline conducted at Johns Hopkins. Each participant underwent a median of five structural MRI studies during the follow-up period as well as annual cognitive testing. Altogether 60 individuals developed MCI, with eight of them progressing to dementia.
“We hypothesized that annual rates of change of segmental brain volumes would be associated with vascular risk factors among middle-aged and older adults and that these trends would be associated with the progression from normal cognition to MCI,” Uchida and colleagues wrote.
Uniquely Long Follow-Up
Most longitudinal studies using structural MRI count a decade or less of follow-up, the study authors noted. This makes it difficult to discern whether the annual rates of change of brain volumes are affected by vascular risk factors or are useful in predicting MCI, they said. Individual differences in brain aging make population-based studies less informative.
This study’s long timeframe allowed for tracking of brain changes “on an individual basis, which facilitates the differentiation between interindividual and intraindividual variations and leads to more accurate estimations of rates of brain atrophy,” Uchida and colleagues wrote.
People with high levels of atrophy in the white matter and enlargement in the ventricles saw earlier progression to MCI (hazard ratio [HR], 1.86; 95% CI, 1.24-2.49; P = .001). Diabetes mellitus was associated with progression to MCI (HR, 1.41; 95% CI, 1.06-1.76; P = .04), as was a low CSF Abeta42:Abeta40 ratio (HR, 1.48; 95% CI, 1.09-1.88; P = .04).
People with both diabetes and an abnormal amyloid profile were even more vulnerable to developing MCI (HR, 1.55; 95% CI, 1.13-1.98; P = .03). This indicated “a synergic association of diabetes and amyloid pathology with MCI progression,” Uchida and colleagues wrote, noting that insulin resistance has been shown to promote the formation of amyloid plaques, a hallmark of Alzheimer’s disease.
The findings also underscore that “white matter volume changes are closely associated with cognitive function in aging, suggesting that white matter degeneration may play a crucial role in cognitive decline,” the authors noted.
Uchida and colleagues acknowledged the modest size and imbalanced sex ratio of their study cohort as potential weaknesses, as well as the fact that the imaging technologies had changed over the course of the study. Most of the participants were White with family histories of dementia.
Findings May Lead to Targeted Interventions
In an editorial comment accompanying Uchida and colleagues’ study, Shohei Fujita, MD, PhD, of Massachusetts General Hospital, Boston, said that, while a more diverse population sample would be desirable and should be sought for future studies, the results nonetheless highlight “the potential of long-term longitudinal brain MRI datasets in elucidating the interplay of risk factors underlying cognitive decline and the potential benefits of controlling diabetes to reduce the risk of progression” along the Alzheimer’s disease continuum.
The findings may prove informative, Fujita said, in developing “targeted interventions for those most susceptible to progressive brain changes, potentially combining lifestyle modifications and pharmacological treatments.”
Uchida and colleagues’ study was funded by the Alzheimer’s Association, the National Alzheimer’s Coordinating Center, and the National Institutes of Health. The study’s corresponding author, Kenichi Oishi, disclosed funding from the Richman Family Foundation, Richman, the Sharp Family Foundation, and others. Uchida and Fujita reported no relevant financial conflicts of interest.
A version of this article first appeared on Medscape.com.
While some brain atrophy is expected in aging, high levels of atrophy in the white matter and high enlargement in the ventricles are associated with earlier progression from normal cognition to MCI, the study found. The researchers also identified diabetes and atypical levels of amyloid beta protein in the cerebrospinal fluid as risk factors for brain atrophy and MCI.
For their research, published online on JAMA Network Open, Yuto Uchida, MD, PhD, and his colleagues at the Johns Hopkins University School of Medicine in Baltimore, Maryland, looked at data for 185 individuals (mean age, 55.4 years; 63% women) who were cognitively normal at baseline and followed for a median of 20 years.
All had been enrolled in a longitudinal cohort study on biomarkers of cognitive decline conducted at Johns Hopkins. Each participant underwent a median of five structural MRI studies during the follow-up period as well as annual cognitive testing. Altogether 60 individuals developed MCI, with eight of them progressing to dementia.
“We hypothesized that annual rates of change of segmental brain volumes would be associated with vascular risk factors among middle-aged and older adults and that these trends would be associated with the progression from normal cognition to MCI,” Uchida and colleagues wrote.
Uniquely Long Follow-Up
Most longitudinal studies using structural MRI count a decade or less of follow-up, the study authors noted. This makes it difficult to discern whether the annual rates of change of brain volumes are affected by vascular risk factors or are useful in predicting MCI, they said. Individual differences in brain aging make population-based studies less informative.
This study’s long timeframe allowed for tracking of brain changes “on an individual basis, which facilitates the differentiation between interindividual and intraindividual variations and leads to more accurate estimations of rates of brain atrophy,” Uchida and colleagues wrote.
People with high levels of atrophy in the white matter and enlargement in the ventricles saw earlier progression to MCI (hazard ratio [HR], 1.86; 95% CI, 1.24-2.49; P = .001). Diabetes mellitus was associated with progression to MCI (HR, 1.41; 95% CI, 1.06-1.76; P = .04), as was a low CSF Abeta42:Abeta40 ratio (HR, 1.48; 95% CI, 1.09-1.88; P = .04).
People with both diabetes and an abnormal amyloid profile were even more vulnerable to developing MCI (HR, 1.55; 95% CI, 1.13-1.98; P = .03). This indicated “a synergic association of diabetes and amyloid pathology with MCI progression,” Uchida and colleagues wrote, noting that insulin resistance has been shown to promote the formation of amyloid plaques, a hallmark of Alzheimer’s disease.
The findings also underscore that “white matter volume changes are closely associated with cognitive function in aging, suggesting that white matter degeneration may play a crucial role in cognitive decline,” the authors noted.
Uchida and colleagues acknowledged the modest size and imbalanced sex ratio of their study cohort as potential weaknesses, as well as the fact that the imaging technologies had changed over the course of the study. Most of the participants were White with family histories of dementia.
Findings May Lead to Targeted Interventions
In an editorial comment accompanying Uchida and colleagues’ study, Shohei Fujita, MD, PhD, of Massachusetts General Hospital, Boston, said that, while a more diverse population sample would be desirable and should be sought for future studies, the results nonetheless highlight “the potential of long-term longitudinal brain MRI datasets in elucidating the interplay of risk factors underlying cognitive decline and the potential benefits of controlling diabetes to reduce the risk of progression” along the Alzheimer’s disease continuum.
The findings may prove informative, Fujita said, in developing “targeted interventions for those most susceptible to progressive brain changes, potentially combining lifestyle modifications and pharmacological treatments.”
Uchida and colleagues’ study was funded by the Alzheimer’s Association, the National Alzheimer’s Coordinating Center, and the National Institutes of Health. The study’s corresponding author, Kenichi Oishi, disclosed funding from the Richman Family Foundation, Richman, the Sharp Family Foundation, and others. Uchida and Fujita reported no relevant financial conflicts of interest.
A version of this article first appeared on Medscape.com.
FROM JAMA NETWORK OPEN