The prevalence of type 2 diabetes mellitus (T2DM) has increased rapidly and T2DM has become one of the most significant metabolic diseases and major worldwide health problems. Studies have shown that T2DM patients are often accompanied by central nervous system damage, including cognitive impairment (Pasquier et al., 2006; McCrimmon et al., 2012; Degen et al., 2016).

Brain iron deposition has been identified to be associated with cognitive decline in various neurodegenerative diseases, such as Alzheimer’s disease (AD) and Parkinson’s disease (PD) (Du et al., 2018; Ayton et al., 2020; Thomas et al., 2020). A few T2DM studies (Yang et al., 2018; Li et al., 2020a,b) have found increased brain iron deposits in gray nuclei, which is related to cognitive decline.

In recent years, Quantitative susceptibility mapping (QSM) has been regarded as the preferred method for quantitative analysis of brain iron because it can quantify the magnetic susceptibility of tissue accurately (Langkammer et al., 2012; Yan et al., 2018). There are many approaches to obtain QSM now, and among them, strategically acquired gradient echo (STAGE) is a rapid multi-contrast and multi-parametric imaging sequence that provides multiple qualitative and quantitative images including QSM. Meanwhile, the QSM reconstruction from STAGE data helps to improve the signal-to-noise ratio and yields fewer artifacts (Gharabaghi et al., 2020). Previous studies have found that STAGE provides a reproducible standardization for iron content measurement (Chen et al., 2018; He et al., 2022).

Post-mortem studies showed that there was a significant correlation between magnetic susceptibility values (MSV) in QSM and histochemical iron contents in brain tissues (Langkammer et al., 2012; Sun et al., 2015; Hametner et al., 2018; Lee et al., 2018; Lewis et al., 2018; Wang et al., 2020). The magnetic susceptibility of biological tissue reflects its magnetization under external magnetic fields, its value can describe the compositional changes in tissues (Guo et al., 2018). However, the MSV measurement methods used in different studies are inconsistent. In a T2DM study, Li et al. (2020b) detected more iron overloading nuclei using voxel-based analysis than region of interest (ROI)-based analysis (Li et al., 2020a), indicating that voxel-based analysis is more sensitive in brain iron detection. However, their measurements are based on the whole structure, which cannot reflect the uneven distribution of iron in the substructures well. More studies have found heterogeneity in brain iron deposition, even in the same nucleus (Sakurai et al., 2010; Wang et al., 2012; Han et al., 2013; Ghassaban et al., 2019; Lee and Lee, 2019). The method of whole-structure-iron measurement is difficult to display regional iron changes in nucleus. ROI-based regional high iron analysis may have a higher diagnostic value than whole structural iron analysis, and reduces the possible error of manually ROI drawing (Wang et al., 2012, 2016) greatly. Previous studies (Ghassaban et al., 2019) have reported abnormal iron deposition in the substantia nigra (SN), especially in regional high iron areas, which can be used as a biomarker to distinguish patients with PD from healthy controls (HC) and to assess the severity of the disease.

However, the previous T2DM studies about brain iron loads (Yang et al., 2018; Li et al., 2020a,b) were analyzed based on the whole nuclei rather than the regional ones. To our knowledge, there is no study on the correlation between the heterogeneity distribution of brain iron and cognitive state in T2DM patients up to now.

Based on the above, we intend to quantitatively analyze the whole-structural volumes, regional MSV and volumes in various nuclei, and to explore the relationship between these parameters and cognitive state in T2DM patients.

Iron deposition has been found associated with oxidative phosphorylation, while increasing levels of oxidative stress may add the risk of T2DM (Rajpathak et al., 2009). Iron overload could generate reactive oxygen species, thereby destroying DNA, eventually leading to end in neuronal cell death and memory decline (Rouault, 2001; Poon et al., 2004; Melis et al., 2013; Cozzi et al., 2019). Previous studies have shown that a history of T2DM could increase iron deposition in some structures of deep gray matter in elderly individuals (Li et al., 2021). The elevated glucose level may aggravate the iron deposition, and iron accumulation produce damage to brain cells resulting in insulin resistance. The relationship between them seems to be bidirectional (Biessels et al., 1998; Fernández-Real et al., 2002).

With QSM, increased water has a limited effect on relaxation values, so the confounding effect can be avoided, this technique is highly sensitive and represents the most accurate way to measure brain iron levels (Yan et al., 2018). Non-invasive quantitative analysis of brain iron deposition can be achieved by MSV measurement based QSM. Because of the lower confounding effect of myelin and negligible contribution from other paramagnetic materials, QSM has proven to be an accurate method of measuring iron content in deep gray matter structures (Langkammer et al., 2012). In post-mortem studies, QSM contrast is significantly correlated with histochemical measurements of iron in these regions, demonstrating its accuracy at identifying iron deposition (Langkammer et al., 2012; Sun et al., 2015; Hametner et al., 2018; Lee et al., 2018; Lewis et al., 2018; Wang et al., 2020).

The precise mechanisms underlying the higher iron concentration in T2DM are not understood yet. This study combined R_II iron content and volume changes of gray matter nuclei in T2DM patients. The differences patterns were explored not only from the perspective of regional high iron and volume, but also from the perspective of whole region volume, and the relationship between abnormal R_II iron accumulation and cognitive decline were also evaluated. In this study, it was found that the MSV_RII, V_RII, and V_RII/V_wh of all gray matter nuclei in T2DM group were increased, but the V_wh of most gray matter nuclei in T2DM group was decreased. Correlation analysis showed that the MSV_RII of gray matter nuclei was correlated with cognitive function.

Our results showed that there has abnormal R_II iron deposition of gray matter nuclei in T2DM patients, after multiple comparison correction. There were significant differences in bilateral HCN, right PUT, right GP and left DN, while another ROI-based study found only PUT had significant difference (Li et al., 2020a). It suggests that regional iron analysis have higher diagnostic sensitivity than whole structural iron analysis. In addition, our results were partially consistent with another voxel-based study (Li et al., 2020b). Significant differences in HCN, PUT and GP on the right were found in both studies. Besides that, significant differences in left HCN and DN were also found. We thought that because of the uneven and relatively concentrated distribution of brain iron, the measurement of R_II iron is more sensitive, to find more areas of iron distribution difference.

A previous study on PD showed that the deposition of iron in the lateral SN pars compacta may be related to neuronal loss (Martin et al., 2008). Another study found that excessive iron accumulation was associated with region-specific advanced atrophy (Lee et al., 2013, 2015). Brain iron abnormally accumulates in a number of neurological disorders such as AD, PD leads to the neurotoxicity of oxidative stress which can promote neuron loss and degeneration, and may manifest as brain atrophy (Dixon et al., 2012; Ward et al., 2014; Rao et al., 2022; Yang et al., 2022). Lots of people believe that insulin resistance and diminished insulin signaling in the brain play a role in glucose hypometabolism (Freiherr et al., 2013; Ferreira et al., 2018). Since glucose is the primary source of energy for neurons, greatly reduced glucose metabolism is likely to affect both normal brain function and the processes of repairing and replacing critical cellular components for brain function when they are lost or damaged as a result of disease (Rao et al., 2022), and may also manifest as brain atrophy.

In this study, we found that iron deposition does exist in T2DM, and the iron deposition is accompanied by the reduction of the V_wh, but the V_RII of T2DM was higher than that of HC group, thereby more V_RII/V_wh regions with statistically significant differences than V_RII and V_wh regions were detected. This fully shows that the uneven iron distribution in the gray matter nuclei of T2DM patients, and the effect of secondary atrophy is offset by the fact that the area with high iron deposition is larger than HC, which is manifested by the increase of V_RII. There was no significant correlation between MSV_RII and V_wh in T2DM group, maybe the changes of MSV_RII and V_wh are not synchronized, the shrinkage of the V_wh is caused by a combination of various factors, which needs further research.

Complicated changes of cerebral parenchymal microstructure were happened in T2DM patients, a single variable cannot be used to indicate the pathological changes. The results of this study also showed that compared with a single QSM parameter, the maximum AUC of combined parameters was 0.86, the sensitivity was 87.5%, the specificity was 75.9%, and a higher diagnostic value of comprehensive multiple parameters was found.

Brain iron level was strongly correlated with magnetic susceptibility in vivo and brain iron overload has recently been found associated with early cognitive impairment in animal and human models (Fujiwara et al., 2017; Wu et al., 2020). So far as we know, this is the first time to study the relationship between R_II iron and cognitive function in T2DM. We found that the MSV_RII of gray matter nuclei with significant differences were negatively correlated with cognitive impairment in T2DM after being corrected by multiple comparisons.

A prior research of iron deposition in T2DM patients found that the susceptibility values of the left PUT showed a close association with MMSE scores but not related to MoCA (Yang et al., 2018; Li et al., 2020a). However, we found the MSV_RII of the PUT in T2DM patients were significantly greater than HCs and not only had a close relationship with MMSE, but also negatively correlated with CVLT and MoCA scores. This result indicated that the MSV_RII reflect the cognitive function impairment more obviously than global susceptibility values due to the uneven distribution of iron in gray matter nuclei.

Globus pallidus exceeding all other gray nuclei has the highest iron concentration in the human brain (Langkammer et al., 2010; Modica et al., 2015). It is a target region of several neurodegenerative diseases with primary brain iron accumulation etiologies (Rouault, 2013), that had been confirmed in AD and multiple sclerosis (Wang et al., 2014; Fujiwara et al., 2017). Functionally, GP serves a range of cognitive and emotional functions (Schroder et al., 2013). In an MRI case-control study, multivariate regression analysis was used to identify the independent associations of brain iron overload and cognitive performance (Blasco et al., 2014). This result and our results strengthen the hypothesis that brains with regional high iron have a close relationship with cognitive decline. We found that the MSV_RII in the right GP had the highest correlation with List A LDFR. As List A LDFR is a reliable and quick test that is more sensitive to the deficit and gives more detailed information about verbal memory than a rough screening tool such as MMSE (Fox et al., 1998). We estimated that deficits in list learning and recall are hallmarks of T2DM.

Head of caudate nucleus not only regulate the movement of the body, but also has a certain impact on the sensory conduction process which is an important part of brain learning and memory system. We found that the increase of MSV_RII in the right HCN was significantly associated with the decrease of CVLT trials 1–5 Sum, List A SDFR, List A LDFR and MMSE scores. The change of MSV_RII in HCN can reflect cognitive impairment sensitively in T2DM.

There are some limitations in this study. Firstly, the sample size was relatively small, a larger sample size is required to validate our findings. Secondly, manually outlining ROI will inevitably lead to small errors, we did not measure the iron content in the whole area, and R_II analysis greatly reduces the possibility of such errors. Thirdly, we only targeted gray matter nuclei rich in iron content, regions closely related to cognition, such as the hippocampus and amygdala, were not included. Fourth, only QSM quantitative measurement of STAGE was used for analysis, other quantitative images can also be used for further study in the future.

In T2DM patients, excessive and heterogeneous iron deposition as well as volume reduction occurs in deep gray nuclei. The MSV in high iron regions can better evaluate the distribution of iron, which is related to the decline of cognitive function. Further evaluations are needed to explore iron burden and volume atrophy in dementia pathology of T2DM in the future.

The original contributions presented in this study are included in this article/supplementary material, further inquiries can be directed to the corresponding authors.

The studies involving humans have been reviewed and approved by the First Affiliated Hospital of Dalian Medical University (PJ-KS-KY-2018-140). The patients/participants provided their written informed consent to participate in this study.

RH and BG: conceptualization, study design, data curation and measurement, formal analysis, visualization, and writing—original draft. ST, YaL, YJ, WL, and YuL: data curation, software application, formal analysis, and investigation. QS: study design, data collection, supervision, and project administration. WW and YM: conceptualization, study design, funding acquisition, supervision, and writing—review and editing. All authors contributed to the article and approved the submitted version.