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  1. Evaluation Summary:

    The current manuscript will be of interest to researchers working in aging, diabetes, and neurocognition. This work emphasizes the role of diabetes in brain aging and cognitive functions that are considered an hourly need due to the increasing trend in the prevalence of diabetes around the world. This article provides valuable information about specific brain regions altered during aging and diabetes. Further, this article reports how T2DM accelerates the aging-associated decline in cognition and brain function. Extensive analysis of human datasets and comparison with published data from other researchers support the conclusion of this study. However, as mentioned by the authors, certain decisions like diabetic interventions that do not rescue brain damage need further validation.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. The reviewers remained anonymous to the authors.)

  2. Reviewer #1 (Public Review):

    Antal et al. analyzed human datasets from UK Biobank and compared the results with published data in the literature to prove the association between type-2- diabetes mellitus (T2DM), brain aging, and cognitive deficits. Using highly effective bioinformatics platforms and applying strict correlation parameters combined with statistical analysis, the authors probed the human datasets for cognition, brain degeneration, and brain function. The research focused on five cognition domains and measured structural alterations by quantifying brain atrophy associated with aging and T2DM. Results showed a significant correlation between age, T2DM, and decline in cognition. The executive function domain required for controlling behavior, working memory, and cognitive flexibility decreased during aging, and T2DM further enhanced this decline. Meta-analysis data of published literature supported the authors' findings. The authors analyzed the death of brain cells that occurs during normal aging and T2DM by measuring the loss of grey matter in different brain regions. Increased atrophy was found in brain regions, mainly in the ventral striatum and putamen, in T2DM patients compared to the control group. Interestingly authors did not see any changes in the hippocampus, which plays a significant role in memory and learning. Considering the role of the ventral striatum in understanding and responding to external stimuli and insulin-dependent secretion of neurotransmitters results from the current study bridge the gap between T2DM, insulin resistance, brain atrophy, and executive functions. The authors observed similar alterations in brain activity that support reduced energy utilization in both the healthy and T2DM groups.

    Based on the observed results, the authors concluded that T2DM affects pathways like aging, but it accelerates brain aging and leads to early cognitive decline. The study suggests neuroimaging biomarkers over the traditional biochemical screen for identifying and following the progression of diabetes because the brain irreversible brain damage occurs much earlier than biochemical alterations in blood. This manuscript improves our understanding of how diabetes influences cognitive performances and why most diabetic patients are susceptible to neurodegeneration.


    The major strength of this paper is the dataset used for the study and the rigorous analysis. The UK biobank is the most extensive collection of human datasets available for researchers to perform medical research. The study is well validated by comparing the observed results with a meta-analysis that supports the conclusion of this study.


    Although this study is well designed and executed, specific details that would help the readers to understand this work better are missing. Since T2DM onset time and patient age are closely associated with cognitive decline, the manuscript must provide this information. Though mentioned by the authors, BMI is not the best measure for determining the severity of T2DM. While BMI can be a better measurement for determining risk for diabetes, it does not provide clear information regarding the severity of the disease. Biochemical measures like fasting glucose level in at least two or three consecutive visits would have served as a better marker for disease severity. Further, this study is missing details on the co-morbidities associated with the T2DM group. Diseases like hypertension and cerebrovascular complications common in the aged and T2DM patients can significantly influence cognition and brain atrophy. Probing the analyzed dataset for this information would be helpful to understand how other diseases can exacerbate the effect of T2DM. As the current study is cross-sectional, the data presented here should be considered a preliminary suggestion regarding T2DM and its impact on cognition as individual variations can significantly affect the data and disease outcome.

  3. Reviewer #2 (Public Review):

    This is an important study that explores the impact of age and T2MD status on brain structural indices and cognitive functional status. The study takes advantage of the extensive UK Biobank data set and validates findings using a meta-analysis of the relevant clinical literature with data analysis conducted using the NeuroQuery tool. The major finding is that T2DM is associated with brain structural and cognitive functional changes that are similar to those identified in aging but occurring earlier in chronological age and being accentuated in individuals with longer duration T2DM.

    Strengths of the study include: 1) identification of overlap between the age-sensitive brain structural and functional changes with those in the T2DM group; 2) demonstration that age-related declines occur earlier with T2DM and that the duration of T2DM impacts the extent of change; 3) interesting outcome of the ALFF pointing to reorganization rather than simple decline in "activity" by brain region, 4) the validation showing congruence for structural outcomes and for cognitive outcomes as a function of T2DM status between the UK Biobank and Meta-analysis approaches.

    Some concerns include: 1) It is not clear from the narrative what the healthy control (HC) reference group was, the number of T2D subjects that were included for each of the increments from 50 to 75 years of age, and whether the data were evenly dispersed across that timeline; 2) Although sex, age, and education were pairwise matched for the T2DM analysis, and were used as covariates for the aging analysis, it seems a missed opportunity not to have parsed the data by sex and by BMI; 3) In the abstract the authors conclude that features of brain atrophy may be useful in spotting T2DM and confirming treatment efficacy but this is not supported by the data and analysis shown.