No abstract

ObjectiveThere is increasing neuroimaging evidence that type 2 diabetes patients with retinal microvascular complications show abnormal brain functional and structural architecture and are at an increased risk of cognitive decline and dementia. However, changes in the topological properties of the functional brain connectome in diabetic retinopathy (DR) patients remain unknown. The aim of this study was to explore the topological organization of the brain connectome in DR patients using graph theory approaches.MethodsThirty-five DR patients (18 males and 17 females) and 38 healthy controls (HCs) (18 males and 20 females), matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. Graph theory analysis was performed to investigate the topological properties of brain functional connectome at both global and nodal levels.ResultsBoth DR and HC groups showed high-efficiency small-world network in their brain functional networks. Notably, the DR group showed reduction in the clustering coefficient (P=0.0572) and local efficiency (P=0.0151). Furthermore, the DR group showed reduced nodal centralities in the default-mode network (DMN) and increased nodal centralities in the visual network (VN) (P<0.01, Bonferroni-corrected). The DR group also showed abnormal functional connections among the VN, DMN, salience network (SN), and sensorimotor network (SMN). Altered network metrics and nodal centralities were significantly correlated with visual acuity and fasting blood glucose level in DR patients.ConclusionDR patients showed abnormal topological organization of the human brain connectome. Specifically, the DR group showed reduction in the clustering coefficient and local efficiency, relative to HC group. Abnormal nodal centralities and functional disconnections were mainly located in the DMN, VN, SN, and SMN in DR patients. Furthermore, the disrupted topological attributes showed correlations with clinical variables. These findings offer important insight into the neural mechanism of visual loss and cognitive deficits in DR patients.

With the development of next generation sequencing, more and more common inherited diseases have been reported. However, accurate and convenient molecular diagnosis cannot be achieved easily because of the enormous size of disease causing mutations. In this study, we introduced a new single-step method for the genetic analysis of patients and carriers in real clinical settings. All kinds of disease causing mutations can be detected at the same time in patients with Mendelian diseases or carriers. First, we evaluated this technology using YH cell line DNA and 9 samples with known mutations. Accuracy and stability of 99.80% and 99.58% were achieved respectively. Then, a total of 303 patients were tested using our targeted NGS approaches, 50.17% of which were found to have deleterious mutations and molecular confirmation of the clinical diagnosis. We identified 219 disease causing mutations, 43.84% (96/219) of which has never been reported before. Additionally, we developed a new deleteriousness prediction method for nonsynonymous SNVs, and an automating annotation and diagnosis system for Mendelian diseases, thus greatly assisting and enhancing Mendelian diseases diagnosis and helping to make a precise diagnosis for patients with Mendelian diseases.

The study aimed to determine alterations in intrinsic brain activity in retinitis pigmentosa (RP) individuals using the amplitude of low-frequency fluctuation (ALFF)/fractional amplitude of low-frequency fluctuation (fALFF) method. Sixteen RP individuals (10 men and six women) and 14 healthy controls (HCs) (six men and eight women) closely matched in age, sex, and education were enrolled in the study. The ALFF/fALFF method was applied to compare different intrinsic brain activities between the RP group and the HC group. The relationship between the mean ALFF/fALFF signal values of different brain regions and the visual measurements in RP group was analyzed by Pearson correlation. Compared with HCs, RP individuals had significantly lower ALFF values in the bilateral lingual gyrus (LIGG)/cerebellum posterior lobe [Brodmann area (BA) 17,18], but lower fALFF values in the bilateral LIGG/cerebellum anterior lobe (BA 17,18). Meanwhile, RP individuals had significantly higher ALFF in the bilateral precuneus cortex/middle cingulate cortex (BA 7,31), as well as higher fALFF values in the left superior/middle frontal gyrus (BA 9,10) and bilateral supplementary motor area (BA 6,8) (voxel-level P<0.01, cluster-level P<0.05). Moreover, the fALFF values of the bilateral LIGG/cerebellum anterior lobe showed positive relationships with the best-corrected visual acuity (BCVA)-oculus dexter (r=0.574, P=0.020) and BCVA-oculus sinister (r=0.570, P=0.021) in RP individuals; our results provide evidence that RP individuals may have impaired intrinsic brain activity in the primary visual area and the visuomotor coordination area that correlates with BCVA. Moreover, our findings indicate that reorganization of the dorsal visual stream and the parietoprefrontal pathway occurs in RP individuals.

Diabetic retinopathy (DR) patients are at an increased risk of cognitive decline and dementia. There is accumulating evidence that specific functional and structural architecture changes in the brain are related to cognitive impairment in DR patients. However, little is known regarding whether the functional architecture of resting-state networks (RSNs) changes in DR patients. The purpose of this study was to investigate the intranetwork functional connectivity (FC) and functional network connectivity (FNC) of RSN changes in DR patients using independent component analysis (ICA). Thirty-four DR patients (18 men and 16 women; mean age, 53.53±8.67 years) and 38 nondiabetic healthy controls (HCs) (15 men and 23 women; mean age, 48.63±11.83 years), closely matched for age, sex, and education, underwent resting-state magnetic resonance imaging scans. ICA was applied to extract the nine RSNs. Then, two-sample t-tests were conducted to investigate different intranetwork FCs within nine RSNs between the two groups. The FNC toolbox was used to assess interactions among RSNs. Pearson correlation analysis was conducted to explore the relationship between intranetwork FCs and clinical variables in the DR group. A receiver operating characteristic (ROC) curve was conducted to assess the ability of the intranetwork FCs of RSNs in discriminating between the two groups. Compared to the HC group, DR patients showed significant decreased intranetwork FCs within the basal ganglia network (BGN), visual network (VN), ventral default mode network (vDMN), right executive control network (rECN), salience network (SN), left executive control network (lECN), auditory network (AN), and dorsal default mode network (dDMN). In addition, FNC analysis showed increased VN-BGN, VN-vDMN, VN-dDMN, vDMN-lECN, SN-BGN, lECN-dDMN, and AN-BGN FNCs in the DR group, relative to the HC group. Furthermore, altered intranetwork FCs of RSNs were significantly correlated with the glycosylated hemoglobin (HbA1c) level in DR patients. A ROC curve showed that these specific intranetwork FCs of RSNs discriminated between the two groups with a high degree of sensitivity and specificity. Our study highlighted that DR patients had widespread deficits in both low-level perceptual and higher-order cognitive networks. Our results offer important insights into the neural mechanisms of visual loss and cognitive decline in DR patients.