التفاصيل البيبلوغرافية
| العنوان: |
Searching the Dark Genome for Alzheimer’s Disease Risk Variants |
| المؤلفون: |
Rachel Raybould, Rebecca Sims |
| المصدر: |
Brain Sciences, Vol 11, Iss 3, p 332 (2021) |
| بيانات النشر: |
MDPI AG, 2021. |
| سنة النشر: |
2021 |
| المجموعة: |
LCC:Neurosciences. Biological psychiatry. Neuropsychiatry |
| مصطلحات موضوعية: |
Alzheimer’s disease, long read technology, dark genome, VNTR, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571 |
| الوصف: |
Sporadic Alzheimer’s disease (AD) is a complex genetic disease, and the leading cause of dementia worldwide. Over the past 3 decades, extensive pioneering research has discovered more than 70 common and rare genetic risk variants. These discoveries have contributed massively to our understanding of the pathogenesis of AD but approximately half of the heritability for AD remains unaccounted for. There are regions of the genome that are not assayed by mainstream genotype and sequencing technology. These regions, known as the Dark Genome, often harbour large structural DNA variants that are likely relevant to disease risk. Here, we describe the dark genome and review current technological and bioinformatics advances that will enable researchers to shed light on these hidden regions of the genome. We highlight the potential importance of the hidden genome in complex disease and how these strategies will assist in identifying the missing heritability of AD. Identification of novel protein-coding structural variation that increases risk of AD will open new avenues for translational research and new drug targets that have the potential for clinical benefit to delay or even prevent clinical symptoms of disease. |
| نوع الوثيقة: |
article |
| وصف الملف: |
electronic resource |
| اللغة: |
English |
| تدمد: |
2076-3425 |
| Relation: |
https://www.mdpi.com/2076-3425/11/3/332; https://doaj.org/toc/2076-3425 |
| DOI: |
10.3390/brainsci11030332 |
| URL الوصول: |
https://doaj.org/article/484df129bcc64339a1ba0c82e059cddc |
| رقم الانضمام: |
edsdoj.484df129bcc64339a1ba0c82e059cddc |
| قاعدة البيانات: |
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