In a recent article published in the JAMA Network Open, researchers identified brain regions most affected in middle-aged and older adults with type I diabetes (T1D) to assess whether these structural changes reflected brain atrophy, i.e., loss of neurons and neuronal connections, commonly observed in neurodegenerative diseases, e.g., Alzheimer's disease (AD).
Additionally, xanax chemist warehouse they examined the association between brain atrophy patterns and T1D-related biomedical and metabolic characteristics, including cognition.
Study: Patterns of Regional Brain Atrophy and Brain Aging in Middle- and Older-Aged Adults With Type 1 Diabetes. Image Credit: OrawanPattarawimonchai/Shutterstock.com
Scientists are pursuing evidence of premature brain aging, especially potential early signs of diabetes-associated dementia or mild cognitive impairment (MCI). Yet, it is unknown which brain regions are affected early in middle- and older adults with a long history of T1D.
About the study
In the present study, researchers recruited participants from two cohort studies combined, the Diabetes Control and Complications Trial (DCCT) and Epidemiology of Diabetes Interventions and Complications (EDIC) conducted at 27 clinical centers in the United States (US) and Canada, to evaluate brain neuroimaging markers used to detect brain age and AD-like atrophy.
DCCT, a randomized clinical trial (RCT), ran between 1983 and 1993 and showed the many benefits of intensive glycemic therapy. When that study ended, 96% of the surviving participants enrolled in the observational study, EDIC, i.e., ongoing from 1994 to the present.
Between 2018 and 2019, for the present EDIC magnetic resonance imaging (MRI) ancillary study, researchers invited randomly selected 425 EDIC participants with no end-stage renal disease or a pacemaker-implanted neurostimulator and visual acuity better than 20/40.
Leveraging this data, they evaluated whether middle- and older-aged adults with T1D have advanced brain aging and more AD-like atrophy than the comparison group comprising demographically similar adults without diabetes or any other serious illness, e.g., stroke. The comparison group matched EDIC participants 1:1 by race/ethnicity, age (±5 years), and education.
The team evaluated psychomotor and mental efficiency using verbal fluency, trail-making part B, the grooved pegboard, and the digit symbol substitution test. They derived immediate memory scores from a subtest of the Wechsler memory scale-Wechsler digit symbol substitution test termed the logical memory.
They performed the most recent assessment using an abbreviated battery of all these diabetes-sensitive tests after an average of 32 years of follow-up. Further, they computed MRI and machine learning indices, which helped them estimate brain age and AD-induced atrophy.
For study participants and controls, the team computed a standardized z score and then obtained a summary score by averaging z scores in each domain to get a unit-free measurement of the relative difference from the DCCT baseline assessment.
Furthermore, the researchers used standardized methods to assess diabetes-related risk factors longitudinally for EDIC participants and cross-sectionally for controls.
Alongside, they obtained their detailed medical history, including demographics, medications, physical measurements [e.g., height, weight, body mass index (BMI), pulse rate, and blood pressure], and laboratory workup studies for fasting lipids, albumin excretion rate (AER), hemoglobin A1c (HbA1c), and serum creatinine.
The final study analysis sample included 416 EDIC participants and 99 controls, which the researchers analyzed between July 2020 and April 2022.
The authors did not find evidence of an association between T1D and early AD-related neurodegeneration. However, the study data suggested that individuals with a long history of T1D had brain atrophy patterns ~6 years ahead of the participants' chronological age, which evidenced premature brain aging.
Further, the authors identified vast gray matter atrophy in the putamen, superior frontal and temporal gyrus, middle frontal gyrus, and thalamus in T1D patients. These regions provided data on SPARE-BA measures which indicated more age-related brain atrophy. A prior meta-analysis showed evidence for thalamic atrophy in T1D.
In this study, the authors identified more brain regions affected in T1D patients due to the two-step harmonization of the imaging protocol.
Also, the study participants and control had similar atrophy measures in AD signature regions, suggesting no association between T1D and markedly reduced brain reserve in brain regions prone to AD-related degeneration.
The authors noted SPARE-AD atrophy patterns associated with psychomotor and mental efficiency and memory in EDIC participants, further supporting the notion that different cognitive impairment profiles are associated with regional brain atrophy patterns.
The cohort study findings suggested that T1D accelerated brain aging but did not trigger early signs of neurodegeneration. The brain region with the most marked regional atrophy was the thalamus.
Nonetheless, brain atrophy-linked affected cognition; however, the differences in the middle- and older-aged adults with T1D and controls were modest, even after >38 years of T1D.
Habes, M. et al. (2023) "Patterns of Regional Brain Atrophy and Brain Aging in Middle- and Older-Aged Adults With Type 1 Diabetes", JAMA Network Open, 6(6), p. e2316182. doi: 10.1001/jamanetworkopen.2023.16182. https://jamanetwork.com/journals/jamanetworkopen/fullarticle/2805469
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Tags: Aging, Albumin, Alzheimer's Disease, Blood, Blood Pressure, Body Mass Index, Brain, Clinical Trial, Creatinine, Dementia, Diabetes, Education, Epidemiology, Fasting, HbA1c, Hemoglobin, Imaging, Laboratory, Lipids, Machine Learning, Magnetic Resonance Imaging, Neurodegeneration, Neurodegenerative Diseases, Neuroimaging, Neurons, Pacemaker, Putamen, Renal disease, Stroke, Thalamus, Type 1 Diabetes, Type I Diabetes
Neha is a digital marketing professional based in Gurugram, India. She has a Master’s degree from the University of Rajasthan with a specialization in Biotechnology in 2008. She has experience in pre-clinical research as part of her research project in The Department of Toxicology at the prestigious Central Drug Research Institute (CDRI), Lucknow, India. She also holds a certification in C++ programming.
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