Omics Technologies for Clinical Diagnosis and Gene Therapy: Medical Applications in Human Genetics -  - E-Book

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Beschreibung

Genetic disorders have been the focus of scientists for a long time. The emergence of next-generation sequencing techniques has ushered a new era in genetics and several developments have occurred in human genetics. The scientific perspective has also been widened with omics technologies that allow researchers to analyze genetic sequences and their expression products. An integrated approach is being used not only for diagnosis but also for disease management and therapeutic purposes.

This book highlights emerging areas of omics technology and its application in the diagnosis and management of human genetic disorders. The book covers three areas of research and implementation:

1) Diagnosis (covering conventional strategies to next-generation platforms). This section focuses on the role of in silico analysis, databases and multi-omics of single-cell which will help in designing better
management strategies.
2) Disease Management and therapeutic interventions. This section starts with genetic counselling and progresses to more specific techniques such as pharmacogenomics and personalized medicine, gene editing techniques and their applications in gene therapies and regenerative medicine.
3) Case studies. This section discusses the applications and success of all the above-mentioned strategies on selected human disorders.

This book serves as a handy reference for students and academics studying advanced omics techniques in biochemistry and molecular genetics as part of courses in life sciences, pharmacology and medicine.

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Seitenzahl: 573

Veröffentlichungsjahr: 2003

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Table of Contents
License
BENTHAM SCIENCE PUBLISHERS LTD.
End User License Agreement (for non-institutional, personal use)
Usage Rules:
Disclaimer:
Limitation of Liability:
General:
FOREWORD
PREFACE
List of Contributors
Next-Generation Technologies for Rare Inherited Disorders
Abstract
1. INTRODUCTION
1.1. Whole Genome/Exome Sequencing
1.2. Transcriptomics (RNA-Seq) of Rare Diseases
1.3. DNA Methylation (Methyl-Seq) in Rare Diseases
1.4. Long-Reads Sequencing for Rare Inherited Disorders
1.5. The International Rare Diseases Research Consortium
CONCLUSION AND RECOMMENDATIONS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Genetic Testing for Rare Genetic Disorders
Abstract
1. INTRODUCTION
1.1. Genetic Testing and Its Scope
1.2. Screening and Diagnostic Testing
1.3. Why Genetic Testing?
2. TESTING TECHNOLOGIES
2.1. Detection of Targeted Allele Specific Mutation
2.2. Gene-specific Sanger Sequencing
2.3. Testing for Structural Variations
2.4. Genetic Testing in the NGS Era
3. INCIDENTAL FINDINGS
4. FUTURE PROSPECTS AND CHALLENGES
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Preimplantation, Prenatal, and Postnatal Diagnosis
Abstract
1. INTRODUCTION
1.1. Preimplantation Genetic Diagnosis (PGD)
1.1.1. PGD and In vitro Diagnostic Procedures
1.1.2. Phases of PGD
1.1.3. Embryo Biopsy
1.1.4. Genetic Diagnostic Analysis
1.2. Prenatal Diagnosis (PND)
1.2.1. In Vivo Procedure of PND
1.2.2. Sampling of Fetus Cells
1.2.3. Genetic Diagnostic Analysis
1.3. Postnatal Diagnosis
1.3.1. Chromosomal Abnormalities
1.3.2. Monogenic (Mendelian) Diseases
1.3.3. Polygenic Diseases
2. Preimplantation, Prenatal, and Postnatal Diagnostic Techniques
2.1. Array Comparative Genomic Hybridization (aCGH)
2.2. Fluorescence In Situ Hybridization (FISH)
2.3. Next Generation Sequencing (NGS)
2.4. Whole Genome Amplification (WGA)
3. Prenatal and Postnatal Diagnostic Techniques for Chromosomal Abnormalities, Monogenic, and Polygenic Diseases
3.1. Methylation PCR
3.2. Amniocentesis
3.3. Karyotyping
3.4. Multiplex Ligation Dependent Probe Amplification (MLPA)
3.5. Restriction Fragment Length Polymorphism (RFLP)
3.6. Quantitative Fluorescence Polymerase Chain Reaction (QF-PCR)
3.7. Cell Free Fetal DNA Analysis
3.8. Chromosomal Microarray Analysis
3.9. Chorionic Villus Sampling
4. FUTURE CHALLENGES IN PREIMPLANTATION, PRENATAL AND POSTNATAL DIAGNOSIS
5. FUTURE PROSPECTS
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Genetic Counseling in Inherited Disorders
Abstract
1. INTRODUCTION
2. POPULATION CARRIER SCREENING MECHANISM
2.1. Thalassemia a Case Study
3. RISK ESTIMATION
4. CLINICAL PRACTICES
5. ETHICAL ISSUES
6. FUTURE PROSPECTS
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Genome-Wide Association Studies (GWAS)
Abstract
1. INTRODUCTION
1.1. Rationale
2. BENEFITS OF GWAS
3. SUCCESS STORIES
3.1. Type 2 Diabetes
3.2. Autoimmune Diseases
3.3. Coronary Artery Disease (CAD)
4. LIMITATIONS OF GWAS
5. POST-GWAS ERA: PROSPECTS AND CHALLENGES
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Regenerative Medicine
Abstract
1. INTRODUCTION
2. APPROACHES TO RM
2.1. Cell-based Therapy
2.1.1. Adult Stem Cells
2.1.2. Pluripotent Stem Cell-Based Cell Therapies
2.1.2.1. Embryonic Stem Cells
2.1.2.2. Induced Pluripotent Stem Cells
2.2. Biomaterials
2.3. Implantation of Scaffold Seeded with Cells
3. CLINICAL APPLICATIONS (Case Studies)
3.1. Bladder and Urethra
3.2. Blood Vessels
3.3. Heart
3.4. Liver
3.5. Skin
3.6. Bone
3.7. Cartilage Tissue
4. CHALLENGES AND FUTURE PERSPECTIVES
4.1. Lack of Robust Lineage-Specific Differentiation Protocols
4.2. Tumorigenicity
4.3. Immune Rejection
4.4. Heterogeneity
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Emerging OMICS and Genetic Disease
Abstract
1. INTRODUCTION TO OMICS AND GENETIC DISEASE
2. ADVANCED TECHNIQUES IN “OMICS”
2.1. Emerging Omics Techniques: Genomics and Transcriptomics
2.1.1. Genomics
2.1.2. Transcriptomics
2.2. Emerging Omics Techniques: Proteomics and Metabolomics
2.2.1. Proteomics
2.2.2. Metabolomics
3. OMICS AND DIAGNOSIS OF GENETIC DISEASES
3.1. Back To The Future
3.2. Advances In Omics Technologies For Disease Diagnosis (examples)
3.3. Mendelian Disorders
3.4. Non-mendelian/common Disorders
4. OMICS DATABASES
5. OMICS: GENETIC DISEASE MANAGEMENT AND THERAPEUTICS
6. CHALLENGES AND OPPORTUNITIES
6.1. Reference Populations and Phenotyping
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
References
Integrated Bioinformatics and Computational Biology Approaches: Applications in Diagnosis and Therapeutics
Abstract
1. INTRODUCTION
1.1. Exploration of Disease-Associated Biomarkers
1.2. Computational Models as Tools to Identify Key Biomarkers
1.3. Annotation of Disease Associated Mutations
1.4. Identification of Epigenetic Drivers
2. ROLE OF SYSTEMS BIOINFORMATICS (NETWORK-BASED METHODS FOR HUMAN DISEASE GENE PREDICTION)
2.1. Systems Modelling and Simulation
2.2. Network-Based Diagnostics and Therapeutics
2.3. Tools/ Data Bases Used in Diagnosis and Treatment Regimens
2.4. Contribution of Bioinformatics in Cancer Diagnostics and Therapeutics
3. APPLICATION IN PRECISION MEDICINE AND PHARMACOGENOMICS
3.1. Pharmacogenomics and Pharmacogenetics in Personalized Medicine
3.2. Pharmacogenomics and Pharmacogenetics in Drug Development
3.3. Pharmacogenomics in Establishment of Drug Application Guidelines
4. REVERSE VACCINOLOGY-A PROGRESSIVE STEP TOWARDS THERAPEUTIC INNOVATION
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Multi-omics Data Integration: Applications in Systems Genomics
Abstract
1. INTRODUCTION
1.1. Advanced Techniques in “Omics”
1.2. Omics-Driven Targeted Therapy
1.3. Meta-omics
1.4. Transcriptomics
1.5. Single-Dimensional Transcriptomic Assessment versus Integrated Omics
1.6. Rewards of Integrated Omics
2. PATHWAY PROFILING USING SYSTEM GENOMICS
3. CATEGORIES OF PATHWAY PROFILING AND GENETIC NETWORK
3.1. Metabolic Pathway Profiling
3.2. Signaling Pathways Profiling
3.3. Networks for Protein-Protein Interaction
3.4. Gene Regulatory Networks
4. DESIGNING EXPERIMENTS FOR OMICS DATA INTEGRATION
4.1. Multi-Omics Data from Genome to Phenome: Integration in Systems Genomics
4.2. Software and Tools Used for Integration
4.3. Multi-Omics Factor Analysis (MOFA)
4.4. MixOmics
4.5. Graph-based Clustering of Samples
4.6. Nonnegative Matrix Factorization (NMF)
4.7. Multi-Omics Data Integration (miodin)
4.8. Network-based Integration of Multi-omics Data (NetICS)
4.9. moCluster
4.10. Penalized Multivariate Analysis (PMA)
5. CHALLENGES
6. FUTURE ASPECTS
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Single Cell Omics
Abstract
1. INTRODUCTION
1.1. Single-cell genomics
Single-cell transcriptomics
1.3. Single-cell Proteomics
1.4. Single-cell Metabolomics
2. STRATEGIES FOR SINGLE-CELL ISOLATION
2.1. Fluorescence-Activated Cell Sorting (FACS)
2.2. Magnetic-activated Cell Sorting (MACS)
2.3. Laser Capture Micro-dissection (LCM)
2.4. Manual Cell Picking/micro-manipulation
2.5. Micro-fluidics
3. STRATEGIES FOR SINGLE-CELL SEQUENCING
3.1. Multiple Displacement Amplification
3.2. Multiple Annealing And Looping Based Amplification Cycles
3.3. PCR Based scRNA Sequencing
3.4. In vitro Transcription (IVT)-based Amplification
3.5. Mass Spectrometry
3.6. Single-cell multi-Omics
3.7. Multi-Omics Approaches: Challenges and Opportunities
4. STRATEGIES FOR MULTI-OMICS PROFILING OF SINGLE CELLS
4.1. Combined
4.2. Separate
4.3. Split
4.4. Convert
4.5. Predict
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Pharmacogenomics
Abstract
1. INTRODUCTION
1.1. Application of Pharmacogenomics
1.2. Translating Pharmacogenomics
1.3. Challenges in Pharmacogenomics
1.4. Design and Interpretation of Pharmacogenetics and Pharmacogenomics Studies
1.5. Regulatory Issues in Genetic Testing
1.6. Development of New Genomic Technologies
1.7. Ethical Issues
1.8. Education
1.9. Cost
2. ANTICIPATED BENEFITS OF PHARMACOGENOMICS
2.1. More Powerful Medicines
2.2. Better, Safer Drugs the First Time
2.3. More Accurate Methods of Determining Appropriate Drug Dosages
2.4. Advanced Screening for Disease
2.5. Better Vaccines
2.6. Improvements in the Drug Discovery and Approval Process
2.7. Decrease in the Overall Cost of Health Care
3. PHARMACOGENOMICS TODAY
4. FUTURE OF PHARMACOGENOMICS
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Biomaterials in Gene Therapy for Soft and Hard Tissues
Abstract
1. INTRODUCTION
2. Mechanism of Gene Therapy
2.1. Delivery of Gene for Gene Therapy
2.1.1. Gene Release
2.1.2. Hematopoietic Stem Cells and Gene Therapy
2.1.3. Gene Therapy via T Cells of a Chimeric Antigen (CAR-T)
2.1.4. CRISPR-Cas9
2.1.5. Ethical Issues
3. Types of Gene Delivery Carriers
3.1. Viral Vectors
3.1.1. Polymeric Vectors
3.1.2. Natural Polymeric Vectors
3.1.3. Synthetic Polymeric Vectors
3.2. Non-Viral Vectors
4. Biomaterials For Gene Therapy
5. Gene Therapy is Soft and Hard Tissue (Examples)
5.1. Muscle Tissue
5.2. Nerve Tissue
5.3. Bone Tissues
5.4. Non-Viral Gene Therapy for Bone Engineering
6. FUTURE PROSPECTS
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Induced Pluripotent Stem Cells
Abstract
1. HUMAN EMBRYONIC STEM CELLS
1.1. Human Induced Pluripotent Stem Cells: Origins and Properties
1.2. Applications of Induced Pluripotent Stem Cells
1.3. Disease modelling
1.4. Embryoid Bodies: An in vitro Model of Embryogenesis
1.5. 2D Models
1.6. 3D Models (Examples)
1.7. Drug Testing and Personalized Medicine
1.8. Stem Cell Therapy and Regenerative Medicine
1.9. CHALLENGES TO IPSC-BASED DISEASE MODELLING AND DRUG DISCOVERY/CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Hemoglobinopathies
Abstract
1. INTRODUCTION
1.1. Structure and Genetics of Hemoglobin Synthesis
1.2. α-, β-, γ- and δ-Thalassemia and Related Conditions
1.3. Sickle Cell Hemoglobin
1.4. Other Hemoglobinopathies
2. MOLECULAR DIAGNOSIS OF HEMOGLOBINOPATHIES
2.1. Hemoglobinopathy Screening in Pregnancy
2.2. Diagnosis of Hemoglobinopathies: New Scientific Advances
2.3. Recent Advances in Screening and Diagnosis of Hemoglobinopathies
2.4. New Challenges in the Diagnosis of Hemoglobinopathies: Migration of Populations
3. BLOOD TRANSFUSION THERAPY IN HEMOGLOBINOPATHIES
4. CRISPR-CAS9 GENE EDITING FOR HEMOGLOBINOPATHIES
5. CHALLENGES
6. FUTURE PROSPECTS
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Metabolic Syndromes
Abstract
1. INTRODUCTION
1.1. Background
1.2. Components of MetS
1.2.1. Obesity
1.2.2. Type2 Diabetes
1.2.3. Atherosclerotic Cardiovascular Disease (ASCVD)
1.3. Diagnostic Criteria For Metabolic Syndrome
1.3.1. Clinical Measures For Diagnosis
1.3.2. Elevated Waist Circumference
1.3.3. Elevated Triglycerides
1.3.4. Low HDL-C
1.3.5. Elevated Blood Pressure
1.3.6. Elevated Fasting Glucose
1.3.7. Others (Pro-inflammatory State)
1.3.8. Genetic Determinants of MetS
2. Therapeutics of metabolic disorders
2.1. Pharmacological Therapy
2.1.1. Polypill-Addresses More Than One Cardiometabolic Risk
2.2. Fixed Dose Combination (FDC)
2.2.1. Diabetes
2.2.2. SGLT 2 Inhibitor/DPP 4 Inhibitor
2.2.3. Thiazolidinedione/DPP-4 Inhibitor
2.2.4. Biguanide/DPP-4 Inhibitor FDC
2.2.5. Biguanide/α-Glucosidase Inhibitor
2.2.6. Insulin Combinations
2.2. Diabesity
2.3. Hyperthyroidism
2.4. Methimazole/Triiodothyronine
3. Surgical Treatment
3.1. Bariatric Treatment
3.1.1. Diabesity
3.1.2. Dyslipidemia
4. Gene Therapy
4.1. Leptin Gene Therapy
4.1.1. Diabetes
4.1.2. Diabesity
4.2. ZFN Gene Editing
4.3. CRISPR/ Cas9 Genome Editing
5. Goal of Therapy
CONCLUDING REMARKS
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Intellectual Disabilities
Abstract
1. INTRODUCTION
2. DIAGNOSIS AND CLASSIFICATION OF ID
3. AUTISM SPECTRUM DISORDERS (ASD)
4. MICROCEPHALY
5. ETIOLOGY OF INTELLECTUAL DISABILITIES
6. GENETIC FACTORS
7. DIAGNOSIS
8. TREATMENT
9. PSYCHOTROPIC DRUG INTERVENTIONS
10. SPECIAL EDUCATION
11. INTERVENTION FOR INBORN ERRORS OF METABOLISM
11.1. GENE THERAPY
Conclusion
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Primary Microcephaly and Schizophrenia: Genetics, Diagnostics and Current Therapeutics
Abstract
1. INTRODUCTION
2. PRIMARY MICROCEPHALY
2.1. Clinical Attributes
2.2. Types of Microcephaly
2.3. Incidence
2.4. Genetics of Primary Microcephaly
2.5. Diagnosis
2.6. Management
3. SCHIZOPHRENIA
3.1. Clinical Attributes
3.2. Types of Schizophrenia
3.2.1. Paranoid Schizophrenia
3.2.2. Disorganized Schizophrenia
3.2.3. Catatonic Schizophrenia
3.2.4. Undifferentiated Schizophrenia
3.2.5. Residual Schizophrenia
3.3. Incidence
3.4. Genetics of Schizophrenia
3.5. Diagnosis
3.6. Management
CONCLUSION
CONSENT FOR PUBLICATION
CONFLICT OF INTEREST
ACKNOWLEDGEMENTS
REFERENCES
Omics Technologies for Clinical Diagnosis and Gene Therapy
Medical Applications in Human Genetics
Edited by
Syeda Marriam Bakhtiar
Department of Bioinformatics and Biosciences
Faculty of Health and Life Sciences
Capital University of Science and Technology
Islamabad
Pakistan
&
Erum Dilshad
Department of Bioinformatics and Biosciences
Faculty of Health and Life Sciences
Capital University of Science and Technology
Islamabad
Pakistan

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FOREWORD

Human diseases especially genetic disabilities have always been a focus of research. Research on genetics and molecular genetics has contributed extensively to improving the overall quality of life and management of patients suffering from genetic diseases. With the onset of Omics and Next generation technologies (NGS), the dream of personalized medicine has almost come to reality. Technological advances in the domains of genomics, transcriptomics, proteomics and metabolomics have enabled scientists to explore the genetic and molecular causes in extraordinary detail. These technologies have contributed immensely to advancements related to early and efficient diagnosis, which have revolutionized clinical practices. Despite the contribution of these technologies, it is always felt that none of these technologies alone have the potential to cope with the biological complexity of human diseases. The integration of multiple technologies and a combination of diverse data types is the new approach that has the potential to provide a more comprehensive understanding of biological systems controlling the onset, progression and impact of diseases.

Initially, the focus of research has been on the early diagnosis and methods by which the symptoms of the disease could be eased off. Gene Therapy, personalized medicine, and precision medicine are very promising concepts but there have always been concerns about the access of the general public to these approaches as well as the application for diverse genetic diseases including rare and common diseases, multifactorial diseases including cancers. Omics Technologies have not only provided the scientists with better opportunities for correct diagnosis but also expanded the options for treatment including gene therapy, pharmacogenomics, single-cell omics, regenerative medicine, stem cell technologies and many more. Integrative approaches utilizing engineering and informatics have also widened the knowledge base required for appropriate treatment and management approaches.

This book compiled and edited by scientists working in various domains of genomics and human genetics will not only provide the researchers with new approaches in conventional methods of genetics-based diagnosis and counselling but will also open new avenues for further exploration of genetic causes and treatment options. This book is a great effort to document state-of-the-art techniques and technologies for disease prediction and early diagnosis to disease treatment and prognosis using integrative Omics.

Shahid Mahmood Baig Department of Biological and Biomedical Sciences, Agha Khan University, Karachi Pakistan Chairman, Pakistan Science Foundation

PREFACE

Human inherited disorders have been the focus of attention for a long time. Various books have been written with a focus on classical genetic approaches, clinical diagnostic strategies, and counselling, management strategies. With the emergence of Next-generation techniques, a new era was started and lots of developments have occurred in Human Genetics. The perspective has also been widened with emerging OMICS technologies. An integrated approach is being used not only for diagnosis but also for management and therapeutic purposes. This book is an effort to highlight and compile various emerging areas of OMICS technology and its application in the diagnosis and management of human genetic disorders.

The book is planned with three areas of research and implementation i.e., Diagnosis covering conventional strategies to next-generation platforms. This section focuses on the role of Insilco analysis, databases and multi-omics of single-cell which will help in designing better management strategies. Section II covers management and therapeutic interventions starting with genetic counselling and then including more specific techniques such as pharmacogenomics and personalized medicine, gene editing techniques and their applications in gene therapies and regenerative medicine. Section III focuses on case studies and discusses the applications and success of all the above-mentioned strategies on selected human disorders.

Syeda Marriam Bakhtiar Department of Bioinformatics and Biosciences Faculty of Health and Life Sciences Capital University of Science and Technology Islamabad Pakistan &Erum Dilshad Department of Bioinformatics and Biosciences Faculty of Health and Life Sciences

List of Contributors

Adnan HaiderDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, PakistanAlvina GulAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, PakistanAmina BasheerDepartment of Industrial Biotechnology,Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, PakistanAmjad AliDepartment of Industrial Biotechnology,Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, PakistanAmmara SiddiqueAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, PakistanAmna Naheed KhanDepartment of Bioinformatics and Biosciences, Faculty of Health and Life Sciences, Capital University of Science and Technology (CUST), Islamabad, PakistanAnam NazInstitute of Molecular Biology and Biotechnology (IMBB), The University of Lahore (UOL), Lahore, PakistanAqsa IkramInstitute of Molecular Biology and Biotechnology (IMBB), The University of Lahore (UOL), Lahore, PakistanAmbrin FatimaDepartment of Biological and Biomedical Sciences, The Aga Khan University, Karachi, PakistanAreena Suhail KhanDepartment of Biosciences, COMSATS University Islamabad, Park Road, Islamabad, PakistanAtif Ali Khan KhalilDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, PakistanAttiya KanwalInternational Islamic University Islamabad (IIUI), Islamabad, PakistanAyaz KhanNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, PakistanAysha SaeedDepartment of Biotechnology, Kinnaird College for Women, Lahore, PakistanBibi Nazia MurtazaDepartment of Zoology, Abbottabad University of Science and Technology, Abbottabad, PakistanBisma RauffDepartment of Biomedical Engineering, University of Engineering and Technology (UET), Narowal Campus, Lahore, PakistanBushra BanoInstitute of Basic Medical Sciences, Khyber Medical University, Peshawar, PakistanErum DilshadDepartment of Bioinformatics and Biosciences, Faculty of Health and Life Sciences, Capital University of Science and Technology (CUST), Islamabad, PakistanFaiza NaseerShifa College of Pharmaceutical Sciences, Shifa Tameer-e-Millat University, Islamabad, PakistanFakhra NazirDepartment of Bioinformatics and Biosciences, Capital University of Science and Technology, Islamabad (CUST, Islamabad), Pakistan Department of Biosciences, COMSATS University Islamabad, Sahiwal, PakistanFatima ShahidDepartment of Industrial Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, PakistanFazli SubhanDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, PakistanHafiza Noor Ul AyanNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, Pakistan Institute for Cardiogenetic, University of Lubeck, Lubeck, GermanyHajra QayyumDepartment of Biosciences and Bioinformatics, Capital University of Science and Technology, Islamabad, PakistanHayeqa Shahwar AwanDepartment of Industrial Biotechnology,Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, PakistanHira KazmiCentre for Human Genetics, Hazara University Mansehra, PakistanHumna MasoodInstitute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences-UVAS, Lahore, PakistanHuma TariqDepartment of Zoology, Hazara University, Manshera, PakistanIlyas AhmadInstitute for Cardiogenetic, University of Lubeck, Lubeck, GermanyIram AnjumDepartment of Biotechnology, Kinnaird College for Women, Lahore, PakistanIqra BashirDepartment of Bioinformatics and Biosciences, Faculty of Health and Life Sciences, Capital University of Science and Technology (CUST), Islamabad, PakistanKomal AslamDepartment of Biotechnology, Kinnaird College for Women, Lahore, Pakistan Department of Biotechnology, Lahore College for Women University, Lahore, PakistanMahnoor EjazAtta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, PakistanMahnoor AsifNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, PakistanMaria IqbalNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, Pakistan Centogene GmbH, Rostock, GermanyMaria ShabbirHealthcare Biotechnology, Attaur Rehman School of Applied Biosciences, National University of Science and Technology, Islamabad, PakistanMarriam BakhtiarDepartment of Bioinformatics and Biosciences, Faculty of Health and Life Sciences, Capital University of Science and Technology (CUST), Islamabad, PakistanMuhammad FaheemDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, PakistanMuhammad IlyasCentre for Omic Sciences, Islamia College University Peshawar, Pakistan Department of Bioengineering, University of Engineering and Applied Sciences, Swat, PakistanMuhammad Jawad HassanDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, PakistanMuhammad TariqNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, PakistanMuhammad MaazDepartment of Bioinformatics and Biosciences, Faculty of Health and Life Sciences, Capital University of Science and Technology (CUST), Islamabad, PakistanMuhammad Saad KhanCentre for Bioresource Research, Islamabad, PakistanMuneeba IshtiaqDepartment of Bioinformatics and Biosciences, Capital University of Science and Technology, Islamabad (CUST, Islamabad), PakistanMuhammad NaeemDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, PakistanNarjis KhatoonDepartment of Bioinformatics and Biosciences, Capital University of Science and Technology, Islamabad (CUST, Islamabad), PakistanNaveed Altaf MalikNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, PakistanNaveed Altaf MalikNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, PakistanRabbiah Manzoor MalikDepartment of Bioinformatics and Biosciences, Capital University of Science and Technology, Islamabad (CUST, Islamabad), Pakistan Wah Medical College, WahCantt, PakistanRaees KhanInstitute of Basic Medical Sciences, Khyber Medical University, Peshawar, PakistanSyeda Seema WaseemNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, PakistanShahid Mahmood BaigNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, PakistanSadia NawazInstitute of Biochemistry and Biotechnology, University of Veterinary and Animal Sciences-UVAS, Lahore, PakistanShumaila ZulfiqarNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, Pakistan Department of Biotechnology, Kinnaird College for Women, Lahore, PakistanShafaq RamzanNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, PakistanShahid Mahmood BaigNational Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, PakistanSyeda Marriam BakhtiarDepartment of Biosciences and Bioinformatics, Capital University of Science and Technology, Islamabad, PakistanSabba MehmoodDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, PakistanShifa Tariq AshrafDepartment of Industrial Biotechnology, Atta-ur-Rahman School of Applied Biosciences (ASAB), National University of Sciences and Technology (NUST), Islamabad, PakistanSajjad AhmedDepartment of Zoology, Hazara University, Manshera, PakistanShumaila AzamDepartment of Bioinformatics and Biosciences, Capital University of Science and Technology, Islamabad, PakistanSahar FazalDepartment of Bioinformatics and Biosciences, Capital University of Science and Technology, Islamabad, PakistanSana ElahiDepartment of Bioinformatics and Biosciences, Capital University of Science and Technology (CUST), Islamabad, PakistanSarmad MehmoodDepartment of Pathology, CMH Institute of Medical Sciences, Bahawalpur, PakistanSajjad HaiderDepartment of Chemical Engineering, King Saud University, Riyadh, Saudi ArabiaSyed Babar JamalDepartment of Biological Sciences, National University of Medical Sciences, Rawalpindi, PakistanUzma AbdullahUniversity Institute of Biochemistry and Biotechnology, PMAS-Arid Agriculture University, Rawalpindi, PakistanZafar AliCentre for Biotechnology and Microbiology, University of Swat, Swat, Pakistan

Next-Generation Technologies for Rare Inherited Disorders

Hira Kazmi1,Muhammad Ilyas2,3,*
1 Centre for Human Genetics, Hazara University Mansehra, Pakistan
2 Centre for Omic Sciences, Islamia College University Peshawar, Pakistan
3 Department of Bioengineering, University of Engineering and Applied Sciences, Swat, Pakistan

Abstract

Rare inherited disorders have become a major public health concern in recent years. Owing to a lack of resources, poorly planned primary and basic health care, and inadequate political structures, treatment, and management policies are daunting challenges in many countries. As a result, these diseases need particular attention, especially in less developed areas, where these disorders remain unnoticed. Similarly, the effect of such severe disorders on underprivileged populations is expected to be devastating. Identifying certain genetic markers can provide a valuable explanation for disease etiology, molecular characterization, and pathogenesis. In this chapter, we highlight the importance of next-generation sequencing to explore and recognize the role of novel causative genes in developing successful treatments for the most prevalent rare genetic disorders. DNA methylation and transcriptome markers have been shown to aid in the prediction of common diseases; however, this has not been tested on rare genetic disorders. Since the rate of rare inherited disorders is higher in developing countries, we believe that these populations can provide us with much stronger clues for the genetic and environmental association. These markers, along with other parameters, can be used to systematically build machine learning models to improve risk prediction; this approach has the potential to reshape how we predict disease risk and save many lives around the world.

Keywords: Clinical genomics, Genetic counseling, Next-generation sequencing, Prenatal diagnosis, Rare inherited diseases.
*Corresponding author Muhammad Ilyas: Centre for Omic Sciences, Islamia College University Peshawar, Pakistan and Department of Bioengineering, University of Engineering and Applied Sciences, Swat, Pakistan; E-mail: [email protected]

1. INTRODUCTION

Rare disorders affect more than 300 million people worldwide, with a diagnosis of less than 0.2 million people [1]. Around 80% of these disorders are genetic in

origin and have no treatment at all. Identification of such disease variants in patients can now be done with greater accuracy and lower cost by using whole genome/exome sequencing [2]. Despite this, researchers and policymakers are still grappling with the problems involving the use and interpretation of genotype data. Genetic variations have been used in molecular diagnostic research in the past, but with a few loci [3]. With lower cost, faster, and more precise sequencing technologies, it is easier to perform diagnostic tests at the single nucleotide level. Researchers around the world have created more sophisticated methods to study the role of variants and their associated environment in complex diseases using human genome data generated by the 1000 genome project and other genome research groups [4]. Clinical researchers are now using genome-wide studies to advance diagnostics and provide improved decision-making tools for patients. This is how genomics' impact on health care ushered in a new era of genetic medicine, also known as personalized medicine. It takes a reasonable amount of time and money to get results from a lab to a professional clinic. According to genetic specialists, it takes more than ten years for the pharmaceutical industry to conduct medical research based on FDA policies [5]. The genome-wide study contributes to the possibility of developing diseases that are widespread in the world's population. These common diseases include diabetes, hypertension, cancer, and cardiovascular diseases [6]. Comprehensive knowledge of the genetic structure of such disorders will help detect the vital mechanism of cells and, in the long run, improve our understanding of how various factors affect an individual's health.

Genetic studies have revolutionized many fields of research, with the total economic value of the human genome project estimated to be 796 billion USD [7]. Until recently, it was time-consuming and costly to carry out tests to detect pathogenic mutations. The recent boom in Next-Generation Sequencing (NGS) technologies has been a key to low-cost, fast, and reliable performance for molecular diagnostics. After the publication of the human genome, the main challenge for researchers working in the field of medical genetics has been to translate and use this mass of data in a clinical setting. However, genetic characterizations, which include transcriptomic and epigenomic studies of populations with unusual genetic disorders, are not yet properly investigated in the demographic and epidemiological studies of rare inherited diseases. Genes and variants that may be used as markers for the pre-diagnostic testing of such disorders should be identified. This will potentially benefit patients and families with such neglected and devastating disorders through pre-screening, genetic counseling, and carrier screening, and will provide a step toward fully personalized medicine and therapy [8].

1.1. Whole Genome/Exome Sequencing

Next-generation sequencing (NGS) technology has become the most groundbreaking research achievement in the science world. It refers to a series of modern DNA sequencing procedures which are making significant progress in the sequencing of millions of genomic fragments by employing particularly parallel reactions [9, 10]. The cost of sequencing a genome with NGS technology is cheaper as compared to the Sanger sequencing method [11]. The costs have plunged in the last few years, quickly exceeding Moore's Law, the standard benchmark for the declining cost of technology [12] (Fig. 1.1). Numerous technologies, including cutting-edge chemistries, amplification methodologies, and efficient and high-resolution microscopy, have been redesigned to make this possible. In recent years, genome-wide studies using microarray technology have made significant progress [13]. Microarray chip approaches were initially used for gene expression analysis, but they later found widespread use in the analysis of copy number alterations, microRNA studies, mapping of binding sites for protein-protein and DNA-protein interactions, and genotyping of single nucleotide variants [14]. However, NGS technology has made significant advances and is expected to replace the majority of microchip platforms in the long term [15].

Fig. (1.1)) Cost per genome data - August 2020. Data obtained from National Human Genome Research Institute (https://www.genome.gov).

NGS offers ultra-high throughput and speed for sequencing using massively parallel sequencing, and meets the requirements of depth information regarding genomes. Various platforms are available for NGS including Illumina, ion torrent, solid, and many more. All these platforms work on the workflow comprising, library preparation, sequencing, and data analysis. Library preparation is different for each platform and is the most crucial step as the efficiency of the sequencing depends on this step. The library is usually generated by fragmenting the sequences and attaching adaptor sequencing keeping the multiplexing in consideration. For sequencing, most of the NGS platforms use sequencing by synthesis approach or a modified version such as paired-end sequencing. After the sequencing step, the instrument performs base calling by identifying nucleotides, the data generated is then analyzed, normalized, and annotation is performed by bioinformatics.

Emerging genomics techniques, such as next-generation sequencing (NGS), have been widely used in research settings, and they also offer significant benefits in clinical settings. Despite NGS-based genetic testing's remarkable success in improving the diagnosis of genetic variants in rare diseases, there is still a translational gap between clinical implementation and NGS-based genetic testing. Many factors contribute to the suboptimal implementation of NGS technologies in the detection of rare diseases.

In order to make NGS-based genetic testing to be valid and implemented, the patient value can be clearly explained by providing the physician with the tools for better decision making. In this case, there is often minimal real-world proof that supports NGS based genetic testing. The unavailability of sequencing equipment and high cost for many researchers at this time are still unaffordable; however, due to competing market forces, a significant decline is expected in the coming years.

Before NGS can achieve its potential for patients, clinics and society, there are several obstacles to overcome. The main argument is whether genetics based on NGS will produce reliable and reproducible results to aid in the detection of rare diseases [16]. To deal with this, the goal of genetic testing in the detection of rare diseases must be clarified. Secondly, the relationship between genetic testing service providers, clinicians, and patients must be seamless and coordinated.

Since the introduction of NGS technology, several applications have emerged that have proven to be effective in diagnosing a variety of rare diseases in both research and clinical realm. Various genetic testing programs have been developed globally and the market value is estimated to be 22 billion USD in 2024 [17]. There are more than 10,000 diagnostic tests available from about 500 institutions located in Europe that are largely focused on the detection of the defined causative gene [18]. These screening methods served a variety of clinical purposes. About 86% of the genetic screening tests are for postnatal analysis. Somatic genetics for pediatric cancer and antenatal diagnosis accounted for 5.24% and 5.05% of all diagnostic measurements, respectively. It was not shocking that due to its technical immaturity, pre-implant diagnosis comprised less than 1% of the diagnostic tests available.

Besides, Sanger sequencing is still commonly adopted by the community (55%) as a critical orthogonal verification technique [18, 19]. This panel-based sequencing progressed gradually to the dominant sector (14%) [20]. Almost 90% of all the genetic studies available are diagnostic tests for the detection of genetic mutations, such as SNV, duplication and deletion in the coding area. Such screening tests can be utilized for the diagnosis of thousands of genes linked with rare diseases. These rare diseases include neurological conditions, developmental disorders, inborn metabolic disorders, eye disorders, and bone diseases (Table 1.1).

Table 1.1Details of rare inherited diseases databases and their web addresses.Sr. No.TitleDescriptionDatabase1OrphanetOrphanet is a resource for information on rare diseases and orphan drugs, with over 6,000 diseases covered.www.orpha.net2Online Mendelian Inheritance in Man (OMIM)OMIM is a database of human genes and genetic disorders, with a focus on their relationship.http://www.ncbi.nlm.nih.gov/omim3Gene ReviewsIt focuses on the application of molecular genetic testing in the diagnosis, management, and genetic counseling of patients.http://www.ncbi.nlm.nih.gov/sites/GeneTests/review?db=GeneTests4Genetics Home ReferenceIt provides details about genetic disorders and the genes or chromosomes that are linked to them.http://ghr.nlm.nih.gov/5National Organization for Rare Disorders (NORD)The rare disease database contains over 1200 reports.www.rarediseases.org6Genetic AllianceIt includes over 1,000 disease-specific advocacy groups.www.geneticalliance.org7Genetic Mutation Database of Rare DiseasesIt gives physicians access to a virtual encyclopedia of genetic information at their fingertips, allowing for more accurate and efficient diagnosis of rare diseases.https://www.centogene.com8GDRDThis database is intended for educational or research purposes only, and should not be used for direct diagnostic purposes or medical decision-making without the review of a genetics professional.https://db.cngb.org/gdrd/

1.2. Transcriptomics (RNA-Seq) of Rare Diseases

The accessibility of the entire euchromatic sequence (GRCh37/hg19) allowed researchers to quickly identify disease-causing mutations in over 2850 genes responsible for a wide range of Mendelian disorders as well as statistically important associations between over 1000 loci and over 150 complex diseases and traits [21]. However, the study of human genetic diseases is a challenging task – particularly for multi-factorial diseases –due to the limited contribution of several genes in the phenotype, and frequently due to unknown gene-gene and gene-environment interactions [22].

Approximately 88% (Single Nucleotide Polymorphisms (SNPs)) of genetic variants that contribute to complex diseases and genome wide association (GWAS) traits are located in intronic or intergenic regions [23]. This study strongly suggests that these nucleotide changes are more likely to have unintended consequences by changing gene expression rather than protein activity. Loci with such ability are referred to as expression quantitative trait loci (eQTL). Several studies have conclusively shown that inherited polymorphisms cause gene expression variation and that global gene expression analyses – which do not involve a priori hypothesis – offer a comprehensive approach to the analysis of complex traits and disease pathogenesis [24].

Even though many human genetic disorders have a deep genetic understanding, most research has yet to provide important insights as to the actual contribution or functional significance of certain DNA polymorphisms in the disease's genesis. In this instance, comprehensive transcriptome analysis is quickly becoming a key player, as it is an important discovery method for putting existing genetic knowledge about numerous diseases into context [25].

For transcriptomic analysis, RNA seq is becoming a state-of-the-art technique by detecting transcript isoforms, gene fusions, SNP variants and provides researchers with information regarding changes in response to therapeutics and environmental changes. The techniques involve modifications in NGS technologies to make it more focused regarding targeted RNA sequencing, Single-Cell RNA seq, ultra low input RNA seq, RNA exome capture sequencing and in some cases total RNA sequencing. Ribosome profiling is also done using RNA sequencing. RNA seq helps scientists to determine variants expressed in specific disease state and also helps in identifying gene expression signatures, as well as small RNAs regulating gene expressions.

1.3. DNA Methylation (Methyl-Seq) in Rare Diseases

DNA methylation is one of the first epigenetic changes observed in humans [26]. DNA methyltransferases (DNMT) transfer a methyl group from S-adenyl methionine to the fifth carbon of cytosine residues, forming 5-methylcytosine, a common post-replication modification found in cytosines of the CpG dinucleotide sequence (5mC) [27]. Demethylation is a complex process that can be either active or passive. TET enzymes oxidize 5mCs, allowing DNA methylation at particular loci to be eliminated [28].

The 5mC is converted into 5-hydroxymethylcytosine (5hmC) and 5-formylcytosine (5fC) via step-by-step oxidation in the presence of water, oxygen, and -ketoglutarate, yielding carbon dioxide and succinate. Both 5fC and 5caC can then be substituted with unmodified cytosine using thymine DNA glycosylase's base-excision repair [29].

Although all cells in a multicellular organism have the same genome, the diversity of cell types suggests that genome information is used in the different tools for establishing precise expression programs that determine cell identity [30]. A variety of processes, including epigenetic mechanisms, influence the dynamic regulation of gene expression. Epigenetics has a variety of definitions that stem from the need to fill the gap between genetics and development. It's often compared to several layers of instructions that control the genome's functions and coordinate cell fate decisions.

Complex disorders are characterized by altered epigenetic landscapes, but determining whether they are a cause or a result of disease can be difficult [31]. The finding of inherited epigenetic machinery was a major innovation in medical genetics [32]. These findings help to address gaps in our understanding of epigenetic mechanisms, their activities, and roles in body growth and development, as well as to learn more about the etiology of a variety of human diseases.

Because of the growing body of evidence revealing the importance of DNA methylation in common diseases, scientists have begun to use it as a biomarker to detect epigenetic changes linked to disease [33]. This population-based epidemiology method is said to be capable of investigating the role of epigenetics in common diseases and discovering novel risk factors that may be missed by traditional epigenetic epidemiological methods like the Genome-Wide Association Study (GWAS). This epigenetic epidemiologic process is also known as epigenome-wide association study (EWAS) [34]. Despite the fact that epigenetic epidemiology studies are promising and conceptually straightforward, there are some particular obstacles to this approach.

DNA methylation sequencing depends on bisulphate conversion for the detection of unmethylated cytosines. OCR is used for the identification of converted bases and later NGS modifications exploits amplicon methyl-seq and target enrichment. This method not only provides methylation patterns of CpG, CHH and CHG regions but also covers the emerging regions of interests in human genome important for Epigenomics RoadMap Consortium.

1.4. Long-Reads Sequencing for Rare Inherited Disorders

Long-read sequencing, also known as third generation sequencing, has several benefits over short-read sequencing [9]. Though a short-read sequencer can produce readings of up to 600 bases, long-read sequencing technology can produce readings of more than 10 kb on a regular basis [35]. Short-read sequencing is a low-cost, high-precision approach that supports a wide range of analysis tools and pipelines. However, natural nucleic acid polymers, on the other hand, are eight orders long, and sequencing these short-amplified fragments makes rebuilding and numbering the original molecules more difficult. Thus, the long reads enhanced de-novo assembly, mapping certainty, isoform analysis of transcripts, and structural variations detection. In addition, DNA and RNA sequencing of native molecules removes amplification errors and maintains basic modifications. These capabilities, in combination with ongoing improvements in precision, cost, and throughput have begun to open up a wide array of applications for genomic model and non-model organisms. Long read sequencing is a highly accurate approach and a modification of NGS to sequence the genomes with highly repetitive elements, which otherwise are very challenging.

Long-read sequencing is dominated by two techniques: Oxford Nanopore Technologies (ONT) nanopore sequencing and Pacific Biosciences (PacBio) single-molecular real-time (SMRT) sequencing [36]. The SMRT and nanopore sequencing technologies were first released in 2011 and 2014, respectively, and since then have proven to be useful in a variety of applications. These platforms generate data that is qualitatively different from that generated by the second generation, requiring the use of advanced analysis tools. Over the last decade, the study of pathogenic mutations in rare genetic diseases has focused on massively parallel short-read sequencers that sequence coding regions or the entire genome [37]. Nevertheless, using these methods, the current diagnosis rate is around 50%, and there are still several rare genetic disorders with unidentified causes. There could be several reasons for this, but one possibility is that the responsible mutations are located in regions of the genome that are difficult to sequence using traditional methods (e.g. , tandem repeat expansion or complex chromosomal structural aberrations). Despite the inconveniences of the cost and the shortage of conventional approaches, various studies have examined pathogenic genome changes using long read sequencing techniques. The results of such studies give us hope that using long-read sequencers to identify causative mutations in unsolved genetic disorders will help us better understand human genomes and diseases [38]. Such methods will also be applied to individuals with inherited disorders in prospective molecular diagnostics and therapeutic strategies in the future.

1.5. The International Rare Diseases Research Consortium

The International Rare Disease Consortium (IRDiRC) was established in 2010 to promote international research cooperation and funding in the field of rare disorders, with the goal of discovering 200 new treatments and methods to diagnose the majority of rare disorders by 2020 [39]. The IRDiRC is aimed to speeding up the advancement of research on rare diseases through international cooperation and collaboration to allow people with all rare diseases to be diagnosed and to contribute to developing new treatments for rare disorders. The IRDiRC has grown to include over 50 funding agencies and patient advocacy groups from 20 countries with the objective of improving diagnosis and treatment for individuals with rare disorders (https://irdirc.org).

CONCLUSION AND RECOMMENDATIONS

Next-generation Sequencing approaches have greatly advanced the identification of rare inherited diseases and therefore have become a genetic testing tool for several disease groups. They have made significant progress towards understanding many of the genetic factors that underpin inherited disorders in humans, such as the discovery of disease-causing mutations. Though, the road ahead is still long, particularly in the case of complex diseases, and 'the more we investigate, the more complicated it becomes.' Nonetheless, multiple experiments have conclusively shown that SNPs discovered by GWAS, and located beyond genes’ coding regions can trigger gene expression fluctuation, highlighting the importance of transcriptome and epigenetic studies in several rare diseases.

A public training program, including improving research capacity, training, and collaboration should be developed for public health and genomic research.

There must be new multidisciplinary scientific collaborations and data and approaches that must be shared with researchers worldwide. This will establish datasets, knowledge and fundamental understanding of the genetic basis of rare, inherited diseases.There is an urgent need for holistic treatment covering the scope of the health, social and everyday needs of individuals dealing with a rare disease and their families.Prenatal screening testing and genetic counselling services should be available in hospitals, especially in places where consanguineous marriages are very common.Policymakers, health care professionals, and the general public need to be aware of common and rare genetic diseases.Clinicians are either actual or potential opinion leaders, so they must be well aware of the emerging technologies related to clinical genetics.Problems related to rare genetic disorders should be discussed openly at seminars, conferences, and workshops.Advanced or introductory classes in medical/human genetics should be included in educational institutions' curricula, including medical colleges.The government should support research communities in every way possible so that scientists can get a better understanding of all rare diseases.

CONSENT FOR PUBLICATION

Not applicable.

CONFLICT OF INTEREST

The author declares no conflict of interest, financial or otherwise.

ACKNOWLEDGEMENTS

Declared none.

REFERENCES

[1]Šimić G. Rare diseases and omics-driven personalized medicine. Croat Med J 2019; 60(6): 485-7.[http://dx.doi.org/10.3325/cmj.2019.60.485] [PMID: 31894912][2]Bamshad MJ, Ng SB, Bigham AW, et al. Exome sequencing as a tool for Mendelian disease gene discovery. Nat Rev Genet 2011; 12(11): 745-55.[http://dx.doi.org/10.1038/nrg3031] [PMID: 21946919][3]Posey JE, Rosenfeld JA, James RA, et al. Molecular diagnostic experience of whole-exome sequencing in adult patients. Genet Med 2016; 18(7): 678-85.[http://dx.doi.org/10.1038/gim.2015.142] [PMID: 26633545][4]Cardon LR, Bell JI. Association study designs for complex diseases. Nat Rev Genet 2001; 2(2): 91-9.[http://dx.doi.org/10.1038/35052543] [PMID: 11253062][5]van Dijk EL, Auger H, Jaszczyszyn Y, Thermes C. Ten years of next-generation sequencing technology. Trends Genet 2014; 30(9): 418-26.[http://dx.doi.org/10.1016/j.tig.2014.07.001] [PMID: 25108476][6]Koene RJ, Prizment AE, Blaes A, Konety SH. Shared Risk Factors in Cardiovascular Disease and Cancer. Circulation 2016; 133(11): 1104-14.[http://dx.doi.org/10.1161/CIRCULATIONAHA.115.020406] [PMID: 26976915][7]Bennett ST, Barnes C, Cox A, Davies L, Brown C. Toward the $1000 human genome. Pharmacogenomics 2005; 6(4): 373-82.[http://dx.doi.org/10.1517/14622416.6.4.373] [PMID: 16004555][8]Castellani C, Macek M, Jr, Cassiman JJ, et al. Benchmarks for Cystic Fibrosis carrier screening: A European consensus document. J Cyst Fibros 2010; 9(3): 165-78.[http://dx.doi.org/10.1016/j.jcf.2010.02.005] [PMID: 20363197][9]Kumar KR, Cowley MJ, Davis RL. Next-Generation Sequencing and Emerging Technologies. Semin Thromb Hemost 2019; 45(7): 661-73.[http://dx.doi.org/10.1055/s-0039-1688446] [PMID: 31096307][10]Ari Ş, Arikan M. Next-generation sequencing: Advantages, disadvantages, and future. Plant Omics: Trends and Applications 2016109-35.[http://dx.doi.org/10.1007/978-3-319-31703-8_5][11]Zhang Z, Liu G, Chen Y, et al. Comparison of different sequencing strategies for assembling chromosome-level genomes of extremophiles with variable GC content. iScience 2021; 24(3): 102219.[http://dx.doi.org/10.1016/j.isci.2021.102219] [PMID: 33748707][12]Park ST, Kim J. Trends in Next-Generation Sequencing and a New Era for Whole Genome Sequencing. Int Neurourol J 2016; 20(2) (Suppl. 2): S76-83.[http://dx.doi.org/10.5213/inj.1632742.371] [PMID: 27915479][13]Grant SFA, Hakonarson H. Microarray technology and applications in the arena of genome-wide association. Clin Chem 2008; 54(7): 1116-24.[http://dx.doi.org/10.1373/clinchem.2008.105395] [PMID: 18499899][14]Mullany LE, Wolff RK, Herrick JS, Buas MF, Slattery ML. SNP Regulation of microRNA Expression and Subsequent Colon Cancer Risk. PLoS One 2015; 10(12): e0143894.[http://dx.doi.org/10.1371/journal.pone.0143894] [PMID: 26630397][15]Jia B, Xu S, Xiao G, Lamba V, Liang F. Learning gene regulatory networks from next generation sequencing data. Biometrics 2017; 73(4): 1221-30.[http://dx.doi.org/10.1111/biom.12682] [PMID: 28294287][16]Liu Z, Zhu L, Roberts R, Tong W. Toward clinical implementation of next-generation sequencing-based genetic testing in rare diseases: Where are we? Trends Genet 2019; 35(11): 852-67.[http://dx.doi.org/10.1016/j.tig.2019.08.006] [PMID: 31623871][17]Perakslis E, Coravos A. Is health-care data the new blood? Lancet Digit Health 2019; 1(1): e8-9.[http://dx.doi.org/10.1016/S2589-7500(19)30001-9] [PMID: 33323242][18]Javaher P, Nyoungui E, Kääriäinen H, et al. Genetic screening in Europe. Public Health Genomics 2010; 13(7-8): 524-37.[http://dx.doi.org/10.1159/000294998] [PMID: 20203479][19]Crossley BM, Bai J, Glaser A, et al. Guidelines for Sanger sequencing and molecular assay monitoring. J Vet Diagn Invest 2020; 32(6): 767-75.[http://dx.doi.org/10.1177/1040638720905833] [PMID: 32070230][20]Lee HCH, Lau WL, Ko CH, et al. Flexi-Myo panel strategy: Genomic diagnoses of myopathies and muscular dystrophies by next-generation sequencing. Genet Test Mol Biomarkers 2020; 24(2): 99-104.[http://dx.doi.org/10.1089/gtmb.2018.0185] [PMID: 30907627][21]Ward LD, Kellis M. Interpreting noncoding genetic variation in complex traits and human disease. Nat Biotechnol 2012; 30(11): 1095-106.[http://dx.doi.org/10.1038/nbt.2422] [PMID: 23138309][22]Hahn LW, Ritchie MD, Moore JH. Multifactor dimensionality reduction software for detecting gene-gene and gene-environment interactions. Bioinformatics 2003; 19(3): 376-82.[http://dx.doi.org/10.1093/bioinformatics/btf869] [PMID: 12584123][23]Costa V, Aprile M, Esposito R, Ciccodicola A. RNA-Seq and human complex diseases: recent accomplishments and future perspectives. Eur J Hum Genet 2013; 21(2): 134-42.[http://dx.doi.org/10.1038/ejhg.2012.129] [PMID: 22739340][24]Stranger BE, Stahl EA, Raj T. Progress and promise of genome-wide association studies for human complex trait genetics. Genetics 2011; 187(2): 367-83.[http://dx.doi.org/10.1534/genetics.110.120907] [PMID: 21115973][25]Parkhomchuk D, Borodina T, Amstislavskiy V, et al. Transcriptome analysis by strand-specific sequencing of complementary DNA. Nucleic Acids Res 2009; 37(18): e123.[http://dx.doi.org/10.1093/nar/gkp596] [PMID: 19620212][26]Jin Z, Liu Y. DNA methylation in human diseases. Genes Dis 2018; 5(1): 1-8.[http://dx.doi.org/10.1016/j.gendis.2018.01.002] [PMID: 30258928][27]Bellizzi D, D’Aquila P, Scafone T, et al. The control region of mitochondrial DNA shows an unusual CpG and non-CpG methylation pattern. DNA Res 2013; 20(6): 537-47.[http://dx.doi.org/10.1093/dnares/dst029] [PMID: 23804556][28]Xu GL, Wong J. Oxidative DNA demethylation mediated by Tet enzymes. Natl Sci Rev 2015; 2(3): 318-28.[http://dx.doi.org/10.1093/nsr/nwv029][29]Bochtler M, Kolano A, Xu GL. DNA demethylation pathways: Additional players and regulators. BioEssays 2017; 39(1): e201600178.[http://dx.doi.org/10.1002/bies.201600178] [PMID: 27859411][30]Whyte WA, Orlando DA, Hnisz D, et al. Master transcription factors and mediator establish super-enhancers at key cell identity genes. Cell 2013; 153(2): 307-19.[http://dx.doi.org/10.1016/j.cell.2013.03.035] [PMID: 23582322][31]Eichler EE, Flint J, Gibson G, et al. Missing heritability and strategies for finding the underlying causes of complex disease. Nat Rev Genet 2010; 11(6): 446-50.[http://dx.doi.org/10.1038/nrg2809] [PMID: 20479774][32]Portela A, Esteller M. Epigenetic modifications and human disease. Nat Biotechnol 2010; 28(10): 1057-68.[http://dx.doi.org/10.1038/nbt.1685] [PMID: 20944598][33]Muka T, Koromani F, Portilla E, et al. The role of epigenetic modifications in cardiovascular disease: A systematic review. Int J Cardiol 2016; 212: 174-83.[http://dx.doi.org/10.1016/j.ijcard.2016.03.062] [PMID: 27038728][34]Birney E, Smith G D, Greally J M. Epigenome-wide association studies and the interpretation of disease-omics. PLoS genetics 2016; 12(6): e1006105.[http://dx.doi.org/10.1371/journal.pgen.1006105][35]Rhoads A, Au KF. PacBio sequencing and its applications. Genomics Proteomics Bioinformatics 2015; 13(5): 278-89.[http://dx.doi.org/10.1016/j.gpb.2015.08.002] [PMID: 26542840][36]Karl MM. Insights into old and new acetogens: transformation barriers and genomics (Doctoral dissertation, Universität Ulm).[37]Mitsuhashi S, Matsumoto N. Long-read sequencing for rare human genetic diseases. J Hum Genet 2020; 65(1): 11-9.[http://dx.doi.org/10.1038/s10038-019-0671-8] [PMID: 31558760][38]Majewski J, Schwartzentruber J, Lalonde E, Montpetit A, Jabado N. What can exome sequencing do for you? J Med Genet 2011; 48(9): 580-9.[http://dx.doi.org/10.1136/jmedgenet-2011-100223] [PMID: 21730106][39]Lochmüller H, Torrent i Farnell J, Le Cam Y, et al. IRDiRC Consortium AssemblyThe International Rare Diseases Research Consortium: Policies and Guidelines to maximize impact. Eur J Hum Genet 2017; 25(12): 1293-302.[http://dx.doi.org/10.1038/s41431-017-0008-z] [PMID: 29158551]

Genetic Testing for Rare Genetic Disorders

Muhammad Tariq1,*,Naveed Altaf Malik1,Ilyas Ahmad2,Syeda Seema Waseem,Shahid Mahmood Baig1
1 National Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, Pakistan
2 Institute for Cardiogenetic, University of Lubeck, Lubeck, Germany
3 Cologne Center for Genomics (CCG), University of Cologne, Germany

Abstract

Rare genetic disorders affect a significant proportion of the global population. A large number of these patients are either misdiagnosed or remain undiagnosed which can have potentially adverse effects, including failure to provide anticipatory prognosis and identify potential treatment. With the completion of HGP, genetic testing has fast grown into a diagnostic discipline introducing new and cost-effective diagnostic tests with reasonable accuracy and specificity. NGS technologies, in particular, changed the field of genetic diagnosis by sequencing the entire genome or subset thereof in a single test and accomplishing diagnosis of virtually all diseases, either congenital or late-onset. These technologies have opened up new opportunities and unique challenges. This chapter discusses the importance of genetic testing, its scope, various technologies and approaches and, finally, the opportunities and challenges accompanying the new age genetic tests.

Keywords: aCGH, ARMS-PCR, Genetic disorders, Genetic testing, Massive Parallel Sequencing, NGS, Targeted Gene Panels, WES.
*Corresponding author Muhammad Tariq: National Institute for Biotechnology and Genetic Engineering College, Pakistan Institute of Engineering and Applied Sciences (NIBGE-C, PIEAS), Faisalabad, Pakistan; E-mail: [email protected]

1. INTRODUCTION

Mendelian disorders are more commonly known as rare inherited disorders, especially among researchers working on these disorders. Around 7000 of these disorders are currently known of which a substantial number of disorders are life-threatening or chronically debilitating [1]. Ironically, however, 40 to 82 of every 1000 live births have one or another genetic disorder [2]. If a total load of genetic disorders constituted by all the inherited disorders together is considered, as much as 8% of the world population presents with a genetic disorder before adolescence [3].

Thus, taken together, the so-called rare genetic disorders are not very rare! Moreover, these disorders are amongst the most difficult to diagnose in clinical practice owing to their genetic heterogeneity [4]. For instance, mutations in more than 150 genes have been implicated in inherited hearing loss only [5]. Thus, a large number of patients are either misdiagnosed or remain undiagnosed. This lack of diagnosis can fail to identify any potential therapeutic intervention and assess the risk of recurrence of the disorder in future pregnancies. Therefore, the completion of the Human Genome Project (HGP) in 2003 was heralded as the dawn of an era of genomic medicine [6] wherein individual genetic information will be used for making clinical decisions and delivery of personalized medicine [7]. Promises of rapid detection of mutations and improved diagnosis and prognosis made by proponents of this project fueled patients' desire for a rapid and accurate molecular diagnosis of their disease [8].

But until appropriate genetic tests are available for individual patients, access to the complete human genome alone cannot materialize the dream of personalized genomic medicine.

1.1. Genetic Testing and Its Scope

Ever since the first DNA test in the late 70s [9], genetic testing has fast grown to become an established diagnostic discipline today. Within the last few decades, genetic testing of disease-causing variants has been extensively used in clinical diagnosis and carrier screening of a large number of inherited disorders. In addition, it has also been used for prenatal diagnosis of the fetus in families with a history of a severe disease. Genetic testing is the procedure that detects variations in DNA to determine a patient’s predisposition to develop diseases and disabilities. Although genetic tests were in use before, their applications increased by an order of several magnitudes after the completion of HGP, changing our medical practice for good (reproductive medicine and oncology, for instance) [10]. Today, these applications span a variety of medical disciplines, such as newborn screening for highly penetrant disorders; diagnostic and carrier testing for inherited disorders; screening for adult onset and complex multifactorial disorders; and evaluation of drug dosage, selection and response in pharmacogenetic testing [11].

In this chapter, we discuss the genetic test and its types, and its importance in the diagnosis of rare genetic disorders. The utility of a particular genetic test, in the clinic, depends on the degree of genetic heterogeneity of the disease being investigated and prospects for therapeutic intervention. The selection of genetic tests and platforms is also guided by the nature of the disease, patient’s age, family history and available specimen. Some of the tests can rapidly detect gene variants previously implicated in similar, or the same, diseases (allele-specific tests) while others are tailor-made for examining the entire coding sequence of one or more genes in search of as yet undiscovered causative variants; each strategy has its strengths and weaknesses [12]. Prenatal whole genome sequencing (WGS), for instance, is useful for detecting carrier status in a large number of heterogeneous rare disorders [13], whereas in single-gene disorders, such as beta-thalassemia, molecular diagnosis can be accomplished in routine by simple and low-cost PCR amplification [14].

1.2. Screening and Diagnostic Testing

A genetic test is different from other clinical tests in that the routine clinical test is purely diagnostic and is meant to select appropriate interventions for a patient. However, a genetic test can serve both as a screening test and as a diagnostic test. As a screening test, it can be used to screen asymptomatic individuals to identify those predisposed to disease or screen for a mutation with potential risk to an unborn child (fetus). As a diagnostic test, it is used to testify the presence of an active disease process. Predictive testing can assess a healthy individual’s risk of developing a disease, way before its onset, although it cannot predict its onset and severity [15]. The primary objective of a screening test is to identify individuals who can benefit from further diagnostic testing. Diagnostic tests have higher sensitivity and specificity and specifically, look for a particular clinical condition [16].

1.3. Why Genetic Testing?

For a family with a history of a genetic disorder, genetic testing enables the parents to make decisions during pregnancy based on the information provided by the test, coupled with genetic counselling. An expecting family can, for instance, decide to terminate or continue their pregnancy based on the result of a prenatal genetic test [17