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    Differential Methylation Profile in Fragile X Syndrome-Prone Offspring Mice after in Utero Exposure to Lactobacillus Reuteri
    (MDPI, 2022-07-22) AlOlaby, Reem R.; Zafarullah, Marwa; Barboza, Mariana; Peng, Gang; Varian, Bernard J.; Erdman, Susan E.; Lebrilla, Carlito; Tassone, Flora; Medical and Molecular Genetics, School of Medicine
    Environmental factors such as diet, gut microbiota, and infections have proven to have a significant role in epigenetic modifications. It is known that epigenetic modifications may cause behavioral and neuronal changes observed in neurodevelopmental disabilities, including fragile X syndrome (FXS) and autism (ASD). Probiotics are live microorganisms that provide health benefits when consumed, and in some cases are shown to decrease the chance of developing neurological disorders. Here, we examined the epigenetic outcomes in offspring mice after feeding of a probiotic organism, Lactobacillus reuteri (L. reuteri), to pregnant mother animals. In this study, we tested a cohort of Western diet-fed descendant mice exhibiting a high frequency of behavioral features and lower FMRP protein expression similar to what is observed in FXS in humans (described in a companion manuscript in this same GENES special topic issue). By investigating 17,735 CpG sites spanning the whole mouse genome, we characterized the epigenetic profile in two cohorts of mice descended from mothers treated and non-treated with L. reuteri to determine the effect of prenatal probiotic exposure on the prevention of FXS-like symptoms. We found several genes involved in different neurological pathways being differentially methylated (p ≤ 0.05) between the cohorts. Among the key functions, synaptogenesis, neurogenesis, synaptic modulation, synaptic transmission, reelin signaling pathway, promotion of specification and maturation of neurons, and long-term potentiation were observed. The results of this study are relevant as they could lead to a better understanding of the pathways involved in these disorders, to novel therapeutics approaches, and to the identification of potential biomarkers for early detection of these conditions.
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    Glucose metabolism patterns: A potential index to characterize brain ageing and predict high conversion risk into cognitive impairment
    (Springer, 2022) Jiang, Jiehui; Sheng, Can; Chen, Guanqun; Liu, Chunhua; Jin, Shichen; Li, Lanlan; Jiang, Xueyan; Han, Ying; Alzheimer’s Disease Neuroimaging Initiative; Medical and Molecular Genetics, School of Medicine
    Exploring individual hallmarks of brain ageing is important. Here, we propose the age-related glucose metabolism pattern (ARGMP) as a potential index to characterize brain ageing in cognitively normal (CN) elderly people. We collected 18F-fluorodeoxyglucose (18F-FDG) PET brain images from two independent cohorts: the Alzheimer's Disease Neuroimaging Initiative (ADNI, N = 127) and the Xuanwu Hospital of Capital Medical University, Beijing, China (N = 84). During follow-up (mean 80.60 months), 23 participants in the ADNI cohort converted to cognitive impairment. ARGMPs were identified using the scaled subprofile model/principal component analysis method, and cross-validations were conducted in both independent cohorts. A survival analysis was further conducted to calculate the predictive effect of conversion risk by using ARGMPs. The results showed that ARGMPs were characterized by hypometabolism with increasing age primarily in the bilateral medial superior frontal gyrus, anterior cingulate and paracingulate gyri, caudate nucleus, and left supplementary motor area and hypermetabolism in part of the left inferior cerebellum. The expression network scores of ARGMPs were significantly associated with chronological age (R = 0.808, p < 0.001), which was validated in both the ADNI and Xuanwu cohorts. Individuals with higher network scores exhibited a better predictive effect (HR: 0.30, 95% CI: 0.1340 ~ 0.6904, p = 0.0068). These findings indicate that ARGMPs derived from CN participants may represent a novel index for characterizing brain ageing and predicting high conversion risk into cognitive impairment.
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    Comprehensive analysis of epigenetic clocks reveals associations between disproportionate biological ageing and hippocampal volume
    (Springer, 2022) Milicic, Lidija; Vacher, Michael; Porter, Tenielle; Doré, Vincent; Burnham, Samantha C.; Bourgeat, Pierrick; Shishegar, Rosita; Doecke, James; Armstrong, Nicola J.; Tankard, Rick; Maruff, Paul; Masters, Colin L.; Rowe, Christopher C.; Villemagne, Victor L.; Laws, Simon M.; Alzheimer’s Disease Neuroimaging Initiative (ADNI); Australian Imaging Biomarkers and Lifestyle (AIBL) Study; Medical and Molecular Genetics, School of Medicine
    The concept of age acceleration, the difference between biological age and chronological age, is of growing interest, particularly with respect to age-related disorders, such as Alzheimer's Disease (AD). Whilst studies have reported associations with AD risk and related phenotypes, there remains a lack of consensus on these associations. Here we aimed to comprehensively investigate the relationship between five recognised measures of age acceleration, based on DNA methylation patterns (DNAm age), and cross-sectional and longitudinal cognition and AD-related neuroimaging phenotypes (volumetric MRI and Amyloid-β PET) in the Australian Imaging, Biomarkers and Lifestyle (AIBL) and the Alzheimer's Disease Neuroimaging Initiative (ADNI). Significant associations were observed between age acceleration using the Hannum epigenetic clock and cross-sectional hippocampal volume in AIBL and replicated in ADNI. In AIBL, several other findings were observed cross-sectionally, including a significant association between hippocampal volume and the Hannum and Phenoage epigenetic clocks. Further, significant associations were also observed between hippocampal volume and the Zhang and Phenoage epigenetic clocks within Amyloid-β positive individuals. However, these were not validated within the ADNI cohort. No associations between age acceleration and other Alzheimer's disease-related phenotypes, including measures of cognition or brain Amyloid-β burden, were observed, and there was no association with longitudinal change in any phenotype. This study presents a link between age acceleration, as determined using DNA methylation, and hippocampal volume that was statistically significant across two highly characterised cohorts. The results presented in this study contribute to a growing literature that supports the role of epigenetic modifications in ageing and AD-related phenotypes.
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    Bile reflux alters the profile of the gastric mucosa microbiota
    (Frontiers Media, 2022-09-09) Huang, Gang; Wang, Sui; Wang, Juexin; Tian, Lin; Yu, Yanbo; Zuo, Xiuli; Li, Yanqing; Medical and Molecular Genetics, School of Medicine
    Background: Bile reflux can cause inflammation, gastric mucosa atrophy, and diseases such as stomach cancer. Alkaline bile flowing back into the stomach affects the intragastric environment and can alter the gastric bacterial community. We sought to identify the characteristics of the stomach mucosal microbiota in patients with bile reflux. Methods: Gastric mucosal samples were collected from 52 and 40 chronic gastritis patients with and without bile reflux, respectively. The bacterial profile was determined using 16S rRNA gene analysis. Results: In the absence of H. pylori infection, the richness (based on the Sobs and Chao1 indices; P <0.05) and diversity (based on Shannon indices; P <0.05) of gastric mucosa microbiota were higher in patients with bile reflux patients than in those without. There was a marked difference in the microbiota structure between patients with and without bile reflux (ANOSIM, R=0.058, P=0.011). While the genera, Comamonas, Halomonas, Bradymonas, Pseudomonas, Marinobacter, Arthrobacter, and Shewanella were enriched in patients with bile reflux, the genera, Haemophilus, Porphyromonas, and Subdoligranulum, were enriched in those without bile reflux. Conclusion: Our results demonstrate that bile reflux significantly alters the composition of the gastric microbiota.
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    Determining distinct roles of IL-1α through generation of an IL-1α knockout mouse with no defect in IL-1β expression
    (Frontiers Media, 2022-11-24) Malireddi, R.K. Subbarao; Bynigeri, Ratnakar R.; Kancharana, Balabhaskararao; Sharma, Bhesh Raj; Burton, Amanda R.; Pelletier, Stephane; Kanneganti, Thirumala-Devi; Medical and Molecular Genetics, School of Medicine
    Interleukin 1α (IL-1α) and IL-1β are the founding members of the IL-1 cytokine family, and these innate immune inflammatory mediators are critically important in health and disease. Early studies on these molecules suggested that their expression was interdependent, with an initial genetic model of IL-1α depletion, the IL-1α KO mouse (Il1a-KOline1), showing reduced IL-1β expression. However, studies using this line in models of infection and inflammation resulted in contrasting observations. To overcome the limitations of this genetic model, we have generated and characterized a new line of IL-1α KO mice (Il1a-KOline2) using CRISPR-Cas9 technology. In contrast to cells from Il1a-KOline1, where IL-1β expression was drastically reduced, bone marrow-derived macrophages (BMDMs) from Il1a-KOline2 mice showed normal induction and activation of IL-1β. Additionally, Il1a-KOline2 BMDMs showed normal inflammasome activation and IL-1β expression in response to multiple innate immune triggers, including both pathogen-associated molecular patterns and pathogens. Moreover, using Il1a-KOline2 cells, we confirmed that IL-1α, independent of IL-1β, is critical for the expression of the neutrophil chemoattractant KC/CXCL1. Overall, we report the generation of a new line of IL-1α KO mice and confirm functions for IL-1α independent of IL-1β. Future studies on the unique functions of IL-1α and IL-1β using these mice will be critical to identify new roles for these molecules in health and disease and develop therapeutic strategies.
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    Timing of Newborn Blood Collection Alters Metabolic Disease Screening Performance
    (Frontiers Media, 2021-01-20) Peng, Gang; Tang, Yishuo; Cowan, Tina M.; Zhao, Hongyu; Scharfe, Curt; Medical and Molecular Genetics, School of Medicine
    Blood collection for newborn genetic disease screening is preferably performed within 24-48 h after birth. We used population-level newborn screening (NBS) data to study early postnatal metabolic changes and whether timing of blood collection could impact screening performance. Newborns were grouped based on their reported age at blood collection (AaBC) into early (12-23 h), standard (24-48 h), and late (49-168 h) collection groups. Metabolic marker levels were compared between the groups using effect size analysis, which controlled for group size differences and influence from the clinical variables of birth weight and gestational age. Metabolite level differences identified between groups were correlated to NBS data from false-positive cases for inborn metabolic disorders including carnitine transport defect (CTD), isovaleric acidemia (IVA), methylmalonic acidemia (MMA), and phenylketonuria (PKU). Our results showed that 56% of the metabolites had AaBC-related differences, which included metabolites with either decreasing or increasing levels after birth. Compared to the standard group, the early-collection group had elevated marker levels for PKU (phenylalanine, Cohen's d = 0.55), IVA (C5, Cohen's d = 0.24), MMA (C3, Cohen's d = 0.23), and CTD (C0, Cohen's d = 0.23). These findings correlated with higher false-positive rates for PKU (P < 0.05), IVA (P < 0.05), and MMA (P < 0.001), and lower false-positive rate for CTD (P < 0.001) in the early-collection group. Blood collection before 24 h could affect screening performance for some metabolic disorders. We have developed web-based tools integrating AaBC and other variables for interpretive analysis of screening data.
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    Genetic mosaicism, intrafamilial phenotypic heterogeneity, and molecular defects of a novel missense SLC6A1 mutation associated with epilepsy and ADHD
    (Elsevier, 2021) Poliquin, Sarah; Hughes, Inna; Shen, Wangzhen; Mermer, Felicia; Wang, Juexin; Mack, Taralynn; Xu, Dong; Kang, Jing-Qiong; Medical and Molecular Genetics, School of Medicine
    Background: Mutations in SLC6A1, encoding γ-aminobutyric acid (GABA) transporter 1 (GAT-1), have been recently associated with a spectrum of neurodevelopmental disorders ranging from variable epilepsy syndromes, intellectual disability (ID), autism and others. To date, most identified mutations are de novo. We here report a pedigree of two siblings associated with myoclonic astatic epilepsy, attention deficit hyperactivity disorder (ADHD), and ID. Methods: Next-generation sequencing identified a missense mutation in the SLC6A1 gene (c.373G > A(p.Val125Met)) in the sisters but not in their shared mother who is also asymptomatic, suggesting gonadal mosaicism. We have thoroughly characterized the clinical phenotypes: EEG recordings identified features for absence seizures and prominent bursts of occipital intermittent rhythmic delta activity (OIRDA). The molecular pathophysiology underlying the clinical phenotypes was assessed using a multidisciplinary approach including machine learning, confocal microscopy, and high-throughput 3H radio-labeled GABA uptake assays in mouse astrocytes and neurons. Results: The GAT-1(Val125Met) mutation destabilizes the global protein conformation and reduces transporter protein expression at total and cell surface. The mutant transporter protein was localized intracellularly inside the endoplasmic reticulum (ER) in both HEK293T cells and astrocytes which may directly contribute to seizures in patients. Radioactive 3H-labeled GABA uptake assay indicated the mutation reduced the function of the mutant GAT-1(Val125Met) to ~30% of the wildtype. Conclusions: The seizure phenotypes, ADHD, and impaired cognition are likely caused by a partial loss-of-function of GAT-1 due to protein destabilization resulting from the mutation. Reduced GAT-1 function in astrocytes and neurons may consequently alter brain network activities such as increased seizures and reduced attention.
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    Sugar-Baited Delivery of Small Interfering RNA for Gene Silencing in Adult Mosquitoes
    (Cold Spring Harbor Laboratory, 2022-07-12) Mysore, Keshava; Hapairai, Limb; Realey, Jacob S.; Sun, Longhua; Roethele, Joseph B.; Duman-Scheel, Molly; Medical and Molecular Genetics, School of Medicine
    RNA interference (RNAi), an innate regulatory mechanism that is conserved across many eukaryotic species, has been harnessed for experimental gene silencing in many organisms, including mosquitoes. This protocol describes an optimized method for inducing RNAi in adult Aedes aegypti and Anopheles gambiae mosquitoes that involves feeding them a red-colored sugar bait containing small interfering RNA (siRNA). This oral delivery method is less physically disruptive than delivery by subcutaneous injection, and the use of siRNAs (in contrast to long dsRNAs) for RNAi enables the design of molecules that target conserved sites so that gene function can be studied in multiple species. After feeding, the behavioral and morbidity phenotypes that result from the suppression of target gene expression can then be analyzed.
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    Define and visualize pathological architectures of human tissues from spatially resolved transcriptomics using deep learning
    (Elsevier, 2022-08-24) Chang, Yuzhou; He, Fei; Wang, Juexin; Chen, Shuo; Li, Jingyi; Liu, Jixin; Yu, Yang; Su, Li; Ma, Anjun; Allen, Carter; Lin, Yu; Sun, Shaoli; Liu, Bingqiang; Otero, José Javier; Chung, Dongjun; Fu, Hongjun; Li, Zihai; Xu, Dong; Ma, Qin; Medical and Molecular Genetics, School of Medicine
    Spatially resolved transcriptomics provides a new way to define spatial contexts and understand the pathogenesis of complex human diseases. Although some computational frameworks can characterize spatial context via various clustering methods, the detailed spatial architectures and functional zonation often cannot be revealed and localized due to the limited capacities of associating spatial information. We present RESEPT, a deep-learning framework for characterizing and visualizing tissue architecture from spatially resolved transcriptomics. Given inputs such as gene expression or RNA velocity, RESEPT learns a three-dimensional embedding with a spatial retained graph neural network from spatial transcriptomics. The embedding is then visualized by mapping into color channels in an RGB image and segmented with a supervised convolutional neural network model. Based on a benchmark of 10x Genomics Visium spatial transcriptomics datasets on the human and mouse cortex, RESEPT infers and visualizes the tissue architecture accurately. It is noteworthy that, for the in-house AD samples, RESEPT can localize cortex layers and cell types based on pre-defined region- or cell-type-enriched genes and furthermore provide critical insights into the identification of amyloid-beta plaques in Alzheimer's disease. Interestingly, in a glioblastoma sample analysis, RESEPT distinguishes tumor-enriched, non-tumor, and regions of neuropil with infiltrating tumor cells in support of clinical and prognostic cancer applications.
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    Genetic Testing for Heritable Cardiovascular Diseases in Pediatric Patients: A Scientific Statement From the American Heart Association
    (American Heart Association, 2021) Landstrom, Andrew P.; Kim, Jeffrey J.; Gelb, Bruce D.; Helm, Benjamin M.; Kannankeril, Prince J.; Semsarian, Christopher; Sturm, Amy C.; Tristani-Firouzi, Martin; Ware, Stephanie M.; Medical and Molecular Genetics, School of Medicine
    Genetic diseases that affect the cardiovascular system are relatively common and include cardiac channelopathies, cardiomyopathies, aortopathies, hypercholesterolemias, and structural diseases of the heart and great vessels. The rapidly expanding availability of clinical genetic testing leverages decades of research into the genetic origins of these diseases, helping inform diagnosis, clinical management, and prognosis. Although a number of guidelines and statements detail best practices for cardiovascular genetic testing, there is a paucity of pediatric-focused statements addressing the unique challenges in testing in this vulnerable population. In this scientific statement, we seek to coalesce the existing literature around the use of genetic testing for cardiovascular disease in infants, children, and adolescents.