The genetic basis of autosomal dominant nonsyndromic hearing loss is complex. Genetic factors are responsible for approximately 50% of cases with congenital hearing loss. However, no previous studies have documented the clinical phenotype and genetic basis of autosomal dominant nonsyndromic hearing loss in Mongolians.

Despite significant advances in the treatment of major depression, there is a high degree of variability in how patients respond to treatment. Approximately 70% of patients show some improvement following standard antidepressant treatment and are classified as having non-refractory depressive disorder (NDD), while the remaining 30% of patients do not respond to treatment and are classified as having refractory depressive disorder (RDD). At present, there are no objective, neurological markers which can be used to identify individuals with depression and predict clinical outcome. We therefore examined the diagnostic and prognostic potential of pre-treatment structural neuroanatomy using support vector machine (SVM). Sixty-one drug-naïve adults suffering from depression and 42 healthy volunteers were scanned using structural magnetic resonance imaging (sMRI). Patients then received standard antidepressant medication (either tricyclic, typical serotonin-norepinephrine reuptake inhibitor or typical selective serotonin reuptake inhibitor). Based on clinical outcome, we selected two groups of RDD (n=23) and NDD (n=23) patients matched for age, sex and pre-treatment severity of depression. Diagnostic accuracy of gray matter was 67.39% for RDD (p=0.01) and 76.09% for NDD (p<0.001), while diagnostic accuracy of white matter was 58.70% for RDD (p=0.13) and 84.65% for NDD (p<0.001). SVM applied to gray matter correctly distinguished between RDD and NDD patients with an accuracy of 69.57% (p=0.006); in contrast, SVM applied to white matter predicted clinical outcome with an accuracy of 65.22% (p=0.02). These results indicate that both gray and white matter have diagnostic and prognostic potential in major depression and may provide an initial step towards the use of biological markers to inform clinical treatment. Future studies will benefit from the integration of structural neuroimaging with other imaging modalities as well as genetic, clinical and cognitive information.

The aim of this study is to examine whether advanced magnetic resonance imaging (MRI) techniques can detect early brain injury caused by intrauterine inflammation and inappropriate initial respiratory support in preterm lambs.

Mongolians have played a significant role in modern human evolution, especially after the rise of Genghis Khan (1162[?]-1227). Although the social cultural impacts of Genghis Khan and the Mongolian population have been well documented, explorations of their genome structure and genetic imprints on other human populations have been lacking. We here present the genome of a Mongolian male individual. The genome was de novo assembled using a total of 130.8-fold genomic data produced from massively parallel whole-genome sequencing. We identified high-confidence variation sets, including 3.7 million single nucleotide polymorphisms (SNPs) and 756,234 short insertions and deletions. Functional SNP analysis predicted that the individual has a pathogenic risk for carnitine deficiency. We located the patrilineal inheritance of the Mongolian genome to the lineage D3a through Y haplogroup analysis and inferred that the individual has a common patrilineal ancestor with Tibeto-Burman populations and is likely to be the progeny of the earliest settlers in East Asia. We finally investigated the genetic imprints of Mongolians on other human populations using different approaches. We found varying degrees of gene flows between Mongolians and populations living in Europe, South/Central Asia, and the Indian subcontinent. The analyses demonstrate that the genetic impacts of Mongolians likely resulted from the expansion of the Mongolian Empire in the 13th century. The genome will be of great help in further explorations of modern human evolution and genetic causes of diseases/traits specific to Mongolians.

Congenital heart disease (CHD) is the most frequent birth defect worldwide. The number of adult patients with CHD, now referred to as ACHD, is increasing with improved surgical and treatment interventions. However the mechanisms whereby ACHD predisposes patients to heart dysfunction are still unclear. ACHD is strongly associated with metabolic syndrome, but how ACHD interacts with poor modern lifestyle choices and other comorbidities, such as hypertension, obesity, and diabetes, is mostly unknown.

Magnetic resonance imaging (MRI) is by nature a multi-modality technique that provides complementary information about different aspects of diseases. So far no attempts have been reported to assess the potential of multi-modal MRI in discriminating individuals with and without migraine, so in this study, we proposed a classification approach to examine whether or not the integration of multiple MRI features could improve the classification performance between migraine patients without aura (MWoA) and healthy controls. Twenty-one MWoA patients and 28 healthy controls participated in this study. Resting-state functional MRI data was acquired to derive three functional measures: the amplitude of low-frequency fluctuations, regional homogeneity and regional functional correlation strength; and structural MRI data was obtained to measure the regional gray matter volume. For each measure, the values of 116 pre-defined regions of interest were extracted as classification features. Features were first selected and combined by a multi-kernel strategy; then a support vector machine classifier was trained to distinguish the subjects at individual level. The performance of the classifier was evaluated using a leave-one-out cross-validation method, and the final classification accuracy obtained was 83.67% (with a sensitivity of 92.86% and a specificity of 71.43%). The anterior cingulate cortex, prefrontal cortex, orbitofrontal cortex and the insula contributed the most discriminative features. In general, our proposed framework shows a promising classification capability for MWoA by integrating information from multiple MRI features.

Post-traumatic stress disorder (PTSD) is a debilitating psychiatric disorder. It can be difficult to discern the symptoms of PTSD and obtain an accurate diagnosis. Different magnetic resonance imaging (MRI) modalities focus on different aspects, which may provide complementary information for PTSD discrimination. However, none of the published studies assessed the diagnostic potential of multimodal MRI in identifying individuals with and without PTSD. In the current study, we investigated whether the complementary information conveyed by multimodal MRI scans could be combined to improve PTSD classification performance. Structural and resting-state functional MRI (rs-fMRI) scans were conducted on 17 PTSD patients, 20 trauma-exposed controls without PTSD (TEC) and 20 non-traumatized healthy controls (HC). Gray matter volume (GMV), amplitude of low-frequency fluctuations (ALFF), and regional homogeneity were extracted as classification features, and in order to integrate the information of structural and functional MRI data, the extracted features were combined by a multi-kernel combination strategy. Then a support vector machine (SVM) classifier was trained to distinguish the subjects at individual level. The performance of the classifier was evaluated using the leave-one-out cross-validation (LOOCV) method. In the pairwise comparison of PTSD, TEC, and HC groups, classification accuracies obtained by the proposed approach were 2.70, 2.50, and 2.71% higher than the best single feature way, with the accuracies of 89.19, 90.00, and 67.57% for PTSD vs. HC, TEC vs. HC, and PTSD vs. TEC respectively. The proposed approach could improve PTSD identification at individual level. Additionally, it provides preliminary support to develop the multimodal MRI method as a clinical diagnostic aid.

To investigate the clinical features and the underlying causal gene of a family with hereditary late-onset deafness in Inner Mongolia of China, and to provide evidence for the early genetic screening and diagnosis of this disease.

Although several magnetic resonance imaging (MRI) studies have been conducted in children with obsessive-compulsive disorder (OCD), the brain structural abnormalities in OCD, especially in children, are not yet well characterized. We aimed to identify gray matter (GM) abnormalities in the early stage of pediatric OCD and examine the relationship between these structural abnormalities with clinical characteristics. Examinations of 30 first-episode, treatment-naive pediatric OCD patients without any comorbidities and 30 matched healthy controls (HCs) were performed with 3.0 T magnetic resonance imaging (MRI). Voxel-based morphometry (VBM) following Diffeomorphic Anatomical Registration using Exponentiated Lie algebra (DARTEL) was used to conduct voxel-wise tests for group differences in regional gray matter volume (GMV). Compared to HCs, the patient group exhibited more GMV in the bilateral putamen and left orbitofrontal cortex (OFC) and less GMV in the left inferior parietal lobule (IPL). The GMV alternation in the right putamen of OCD patients was positively correlated with Hamilton Anxiety Rating Scale (HAM-A) scores, while the GMV alternation in the left IPL exhibited a trend to negatively correlate with HAM-A scores. Our current results suggest that the GM abnormalities were defined in the early stage of pediatric OCD. Moreover, these findings provided further evidence of brain GM abnormalities that are not only present in the classical fronto-striatal-thalamic circuit but also in the default mode network (DMN), which may represent the interaction of abnormally functional organization of both network in pediatric OCD.

The large scale genome wide association studies (GWAS) have identified approximately 80 single nucleotide polymorphisms (SNPs) conferring susceptibility to type 2 diabetes (T2D). However, most of these loci have not been replicated in diverse populations and much genetic heterogeneity has been observed across ethnic groups. We tested 28 SNPs previously found to be associated with T2D by GWAS in a Mongolian sample of Northern China (497 diagnosed with T2D and 469 controls) for association with T2D and diabetes related quantitative traits. We replicated T2D association of 11 SNPs, namely, rs7578326 (IRS1), rs1531343 (HMGA2), rs8042680 (PRC1), rs7578597 (THADA), rs1333051 (CDKN2), rs6723108 (TMEM163), rs163182 and rs2237897 (KCNQ1), rs1387153 (MTNR1B), rs243021 (BCL11A), and rs10229583 (PAX4) in our sample. Further, we showed that risk allele of the strongest T2D associated SNP in our sample, rs757832 (IRS1), is associated with increased level of TG. We observed substantial difference of T2D risk allele frequency between the Mongolian sample and the 1000G Caucasian sample for a few SNPs, including rs6723108 (TMEM163) whose risk allele reaches near fixation in the Mongolian sample. Further study of genetic architecture of these variants in susceptibility of T2D is needed to understand the role of these variants in heterogeneous populations.

Several studies have shown that the clinical phenotypes of dentinogenesis imperfecta type II (DGI-II) may be caused by mutations in dentin sialophosphoprotein (DSPP). However, no previous studies have documented the clinical phenotype and genetic basis of DGI-II in a Mongolian family from China.

Leukemia inhibitory factor (LIF) and Ciliary Neurotrophic factor (CNTF) are members of the interleukin-6 family of cytokines, defined by use of the gp130 molecule as an obligate receptor. In the murine experimental autoimmune encephalomyelitis (EAE) model, antagonism of LIF and genetic deletion of CNTF worsen disease. The potential mechanism of action of these cytokines in EAE is complex, as gp130 is expressed by all neural cells, and could involve immuno-modulation, reduction of oligodendrocyte injury, neuronal protection, or a combination of these actions. In this study we aim to investigate whether the beneficial effects of CNTF/LIF signalling in EAE are associated with axonal protection; and whether this requires signalling through oligodendrocytes. We induced MOG₃₅₋₅₅ EAE in CNTF, LIF and double knockout mice. On a CNTF null background, LIF knockout was associated with increased EAE severity (EAE grade 2.1±0.14 vs 2.6±0.19; P<0.05). These mice also showed increased axonal damage relative to LIF heterozygous mice, as indicated by decreased optic nerve parallel diffusivity on MRI (1540±207 µm²-/s vs 1310±175 µm²-/s; P<0.05), and optic nerve (-12.5%) and spinal cord (-16%) axon densities; and increased serum neurofilament-H levels (2.5 fold increase). No differences in inflammatory cell numbers or peripheral auto-immune T-cell priming were evident. Oligodendrocyte-targeted gp130 knockout mice showed that disruption of CNTF/LIF signalling in these cells has no effect on acute EAE severity. These studies demonstrate that endogenous CNTF and LIF act centrally to protect axons from acute inflammatory destruction via an oligodendrocyte-independent mechanism.