1,721,808 research outputs found
Genetic linkage analysis supports the presence of two susceptibility loci for alcoholism and heavy drinking on chromosome 1p22.1-11.2 and 1q21.3-24.2
Full text linkBackground: In order to confirm a previous finding of linkage to alcoholism on chromosome 1 we have carried out a genetic linkage study.Methods: DNA from eighteen families, densely affected by alcoholism, was used to genotype a set of polymorphic microsatellite markers at loci approximately 10 centimorgans apart spanning the short arm and part of the long arm of chromosome 1. Linkage analyses were performed using the classical lod score and a model- free method. Three different definitions of affection status were defined, these were 1. Heavy Drinking ( HD) where affected subjects drank more than the Royal College of Psychiatrists recommended weekly amount. 2. The Research Diagnostic Criteria for alcoholism ( RDCA) 3. Alcohol Dependence Syndrome ( ADS) as defined by Edwards and Gross ( 1976) and now incorporated into ICD10 and DSMIV.Results: Linkage analyses with the markers D1S1588, D1S2134, D1S1675 covering the cytogenetic region 1p22.1- 11.2 all gave positive two point and multipoint lods with a maximum lod of 1.8 at D1S1588 ( 1p22.1) for the RDCA definition of alcoholism. Another lod of 1.8 was found with D1S1653 in the region 1q21.3- 24.2 using the HD affection model.Conclusion: These results both support the presence of linkage in the 1p22.1- 11.2 region which was previously implicated by the USA Collaborative Study of the Genetics of Alcoholism ( COGA) study and also suggest the presence of another susceptibility locus at 1q21.3- 24.2
Statistical methods and analyses in human gene mapping
No full textpublished_or_final_versionPsychiatryDoctoralDoctor of Philosoph
The genetic and personality risk factors associated with pathological gambling in Hong Kong Chinese
No full textpublished_or_final_versionabstractPsychiatryMasterMaster of Philosoph
Genetic architecture and risk prediction of complex diseases
No full textpublished_or_final_versionPsychiatryDoctoralDoctor of Philosoph
Genome-wide association study of bone mineral density in Chinese
No full textpublished_or_final_versionMedicineDoctoralDoctor of Philosoph
Using next-generation sequencing for the diagnosis of paediatric-onset genetic diseases
No full textNext Generation Sequencing (NGS) is a versatile technology that revolutionizes the practice of clinical genetics. The sequencing advancement has been adopted in the genetic diagnosis over the last decade. A proper genetic diagnosis can help the patients by providing better clinical management.
The primary objective of this project is to investigate the application of NGS in diagnosing genetic diseases using two NGS approaches. Multi-gene sequencing panel was used for early-onset bronchiectasis and RASopathies, while whole-exome sequencing (WES) was utilized for prenatally detected structural congenital anomalies (SCAs), and rapid WES for patients with suspected genetic disorders. Functional characterization was integrated into the diagnostic pipeline of NGS gene panel, and the feasibility of performing WES in diverse patients with genetic disorders was discussed.
Gene-panel sequencing was used in the diagnosis of childhood bronchiectasis and identification of causative mutations in patients with RASopathies. Molecular diagnosis was made in six out of 21 (28.6%) children with bronchiectasis, and a
Chinese-specific CFTR mutation was identified. Functional characterization of the CFTR protein with the founder mutation was performed. Results suggested that the protein exhibit reduced glycosylation level with normal gating function. This showed that the mutant protein has an intracellular trafficking defect and causes cystic fibrosis.
On the other hand, an NGS gene panel was used to identify the causative mutations in patients with RASopathies with a primary diagnostic yield of 31.7%. In vitro and in vivo functional assays have been implemented for the interpretation of variants of unclear clinical significance (VUSs). With the integration of functional analysis, the diagnostic rate of the pipeline was improved to 36.5%.
To test the feasibility of using WES in prenatal diagnosis, a total of 33 fetuses with SCAs were tested using a stringent set of interpretation criteria. Overall, diseasecausing mutations were identified in three out of 33 (9.1%), and VUSs were found in six out of 33 (18.2%) fetuses. These findings suggested that it is feasible to adopt WES in a local prenatal setting. And a systematic review of published clinical WES studies showed that the diagnostic yield in this study was comparable with the previous prenatal studies.
To evaluate the clinical utility of rapid WES in patients with an urgent need of genetic diagnosis, 35 patients with suspected genetic conditions were recruited from intensive care units or out-patient clinic. The sequencing pipeline was assessed in three areas: diagnostic yield, turnaround time and clinical implication. The results suggested that disease-causing mutations were found in nine out of 35 (25.7%) patients, with an average turnaround time of eight days. It also showed that all the nine patients who received a genetic diagnosis could also benefit their clinical management.
In summary, the application of both gene-panel sequencing and WES are feasible in the molecular diagnosis of genetic conditions. Furthermore, both sequencing strategies can facilitate clinical diagnosis, and provide necessary medical management for patients. Integration of functional analysis into the sequencing pipeline can also improve the diagnostic performance of an NGS pipeline and clinical values of genetic diagnosis.published_or_final_versionPaediatrics and Adolescent MedicineDoctoralDoctor of Philosoph
An integrative framework to identify gene regulatory programs in mouse notochord and its derived nucleus pulposus cells
No full textThe notochord is a signature of chordate as a flexible rod. It is significant for embryo patterning. In mice, segmentation occurs at E12.5-E15.5 as condensed cells form the vertebrae and non-condensed cells form the intervertebral discs (IVDs). Notochord cells are progenitors and differentiate into chondrocyte-like cells in nucleus pulposus (NP) in IVDs. Although it has been reported that the decrease of notochordal cells in NP is associated with the onset of disc degeneration, the mechanisms remain unclear. Characterizing the gene regulatory programs in mouse notochord and its derived cells, using multiple OMICS data, would help to determine the cellular and molecular basis of notochord and IVD development, and facilitate the induction of stem cells into notochordal cells (NCCs) or NP cells (NPCs) as potential therapy for IVD degeneration.
In this thesis, I first characterized active enhancer profiles, via the analysis of H3K27ac ChIP-seq data, in mice NCCs and NPCs at four developmental stages: embryonic day 8.5-10.5 (E8.5-10.5), embryonic day 12.5 (E12.5), postnatal day 2-3 (P2-3), and adult 8-10 weeks (8-10wks). The profiles for E8.5-10.5 and E12.5 have many differences, while the profiles for E12.5, P2-3 and 8-10wks are much more similar. With integrative analyses of ChIP-seq and RNA-seq data, potential target genes of the enhancers and active transcription factors (TFs) were identified in E12.5 and P2-3 NPCs. Jun-AP1 was shown to be active at P2-3.
I then constructed gene regulatory networks with secondary structure (GRsN) to describe the regulation of groups of genes with groups of TFs. The strategy is based on a linear model via l1-l2,1 and l0-l2,0 norm based Multivariate Sparse Group Lasso (Msgl), estimated using Proximal Gradient Algorithm (PgaMsgl). Thorough simulation studies showed good performance of l0-l2,0 based PgaMsgl for group structured sparse linear regression problems, outperforming Lasso and Group Lasso based methods on simulated problems. We also demonstrated with mouse embryonic stem cell (mESC) data that PgaMsgl can be applied to GRsN construction with two grouping methods. The first considered motif spacing of TFs and promoter-promoter interactions, while the second was purely based on expression profiles. The regulatory relationships of key transcription factors in mESCs were always involved in the results no matter of the model and grouping methods. The application of l0-l2,0 based PgaMsgl on NCC/NPC expression profiles identified regulatory relationships, which are significantly cross-validated with the appearance of the TF’s motif in the enhancer(s) assigned to the target gene. Pathway enrichment of these genes indicates the importance of the AP-1 network, pathways related to extracellular matrix components formation and organization, TGF-β signaling pathway, as well as Smad2/3 signaling in NCCs/NPCs.
This work provides mechanistic insights into the gene regulatory profiles for IVD development, which will be a useful resource for the study of IVD degeneration. The enhancers and regulatory relationships identified may also be useful for improving the induction of ESCs to NCCs/NPCs for the cell therapy of degenerative disc disease.published_or_final_versionBiomedical SciencesDoctoralDoctor of Philosoph
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Detection and characterization of genomics variations in complex diseases
No full textAdvances in genetic research and sequencing technologies over the past decades have driven the development of many cutting-edge mathematical methods and bioinformatic tools for detecting genetic variations ranging from single point mutations to large-scale structural variations. Most of the tools were proposed for detecting germline variations, while the detection of somatic mutations, especially those with low allele frequencies, remains very challenging. This limitation is an impediment to progress in early diagnosis and prevention of diseases, such as cancer and aging-related diseases, especially since low-frequency somatic mutations are believed to play important roles underlying disease aetiology.
Attention deficit hyperactivity disorder (ADHD) and schizophrenia are two complex psychiatric disorders resulting from complex interactions between genetic and environmental risk factors. Previous studies have discovered many disease associated genes, yet the genetic architectures of these two diseases remain incomplete.
Accordingly, the first goal of this thesis is to provide a new method named LFMD, for Low-Frequency Mutations Detection, based on high-depth short-read genome sequencing data. LFMD is a likelihood-based model accounting for PCR duplicates from both strands of original DNA to reduce background noise and unveil low frequency mutations. Based on a site-by-site sensitivity evaluation model, LFMD was demonstrated to achieve superior sensitivity and specificity compared with other state-of-the-art methods. Strikingly, the “barcode free” strategy of LFMD makes it by far the lowest-cost tool. The mitochondrial heterogeneity analysis of 28 samples across different stages of Alzheimer’s Disease showed that the oxidative damage related mutation, C:G>A:T, is significantly enriched in the mid-stage group. This result is consistent with the Mitochondrial Free Radical Theory of Aging, suggesting that Alzheimer’s disease may be linked to the aging of brain cells induced by oxidative damage. However, this was not demonstrated by previous low-frequency mutation studies, suggesting that the method with better sensitivity and precision is essential for detecting low-frequency mutations, which is the prerequisite of elucidating their role in disease aetiology.
The second goal of this thesis is to explore the genetic risk factors of ADHD and schizophrenia using the state-of-the-art whole genome sequencing (WGS) and PacBio long-read sequencing technologies. The 50 de novo mutations (45 SNVs, 3 Indels, 2 CNVs) identified in ADHD provide evidence that the potassium channel genes (GALNT8, KCNK3, KCNJ3, and KCNQ5) contribute to ADHD aetiology. The candidate genes (KCNJ12, OPRM1, CACNA1B, MAP2K3, KMT2C, SYN3 and NXPE1) discovered in schizophrenia demonstrated that genes involved in neurogenesis, neuron development, and neural signal transmission, are involved in the aetiology of schizophrenia.
To sum up, this thesis presents a new method for detecting low-frequency mutations and explored the genetic basis of two complex diseases, ADHD and schizophrenia using state-of-the-art genome sequencing technologies. LFMD is particularly useful in scenarios pursuing high precision, such as in drug resistance prediction, mitochondrial heterogeneity analysis, cancer screening and early diagnosis. The genetic variants and affected genes identified in this thesis extend our current understanding of the genetic risk factors of ADHD and schizophrenia.published_or_final_versionPsychiatryDoctoralDoctor of Philosoph
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