Greenstone Biosciences’ Post

We are delighted to share that our research paper titled "Landscape of genomic structural variations in Indian population-based cohorts: deeper insights into their prevalence and clinical relevance" is now available via Human Genetics and Genomics Advances (https://lnkd.in/dXtUu8GM). This study highlights #StructuralVariations (a complex form of genetic variation), within an underrepresented study of the Indian population-based cohort. Huge thanks to my guide Bratati Kahali We have encountered challenges in uncovering complex genetic variations and delving deeply into the identified #structuralvariations in disease traits within the human genome. I am also excited about connecting genotype findings with the phenotype data 🙂. Thanks, Mehak Chopra https://lnkd.in/d2V_8Rvn

"A team from the Institute of Human Genetics at the University Hospital Schleswig-Holstein (UKSH), the Faculty of Medicine at Kiel University and the University of Lübeck has developed an algorithm that uses machine learning to predict whether gene variants can be responsible for certain diseases. This enables better diagnoses for rare congenital diseases. By working with the algorithm, called STIGMA (the acronym stands for single-cell tissue-specific gene prioritization using machine learning), the researchers have already identified several new disease genes. Their findings have been published in the American Journal of Human Genetics." #ai #healthcare

Unsolved - Unknome - Undiagnosed As a medical genetics physician, I constantly grapple with the limitations of our field. When offering genetic testing, I have a responsibility to be transparent about its yield - the chance of a definitive answer. Unfortunately, for many patients, that answer remains frustratingly elusive. More than half walk away without a diagnosis, and for some conditions, the odds are even bleaker. This leaves them in a kind of medical purgatory: The Unsolved. As I explain to my patients, this low yield is explained by a simple fact: we don't fully understand half of our 20,000 genes. It's a vast unknown territory. This Friday, on my birthday, I felt a surge of accomplishment while reviewing a genetic disease database. By using my expertise and reclassifying cases from Unsolved to Solved, I made a small contribution to someone's life, getting them out of uncharted territory. Today, fueled by my morning coffee and a recent article in The Scientist, a sobering truth resonated with my daily conversations with patients. The article explored the concept of the "Unknome," the uncharted territory of our genome. It highlighted a harsh reality: most research prioritizes well-known genes, a safer bet for securing funding. This comes at the expense of neglecting the vast unknown. The article is a thought-provoking exploration of the current state of genetic research: https://lnkd.in/dbkxz3hZ Looking ahead, I'm eager to explore new diagnostic strategies for the undiagnosed next week in a European Union course specifically dedicated to rare genetic diseases. It's just one more step, but one with the potential to chip away at the unknown, one diagnosis at a time.

Research & Development and Bioinformatics https://lnkd.in/gv-7F6hi During the last few decades, genetic research has made rapid progress. Key areas of genetic research include diagnosis of disease risk factors, understanding the role of recessive inheritance in disorders that are usually seen as dominant, and developing new treatments for specific disorders genetic disorders, infectious diseases, and non-communicable diseases. Key areas of genetic research include: Genetic test. Gene therapy. Reproductive Genomics. Genetic databank and pharmacogenomics. Genetic research is now entering a new era with the availability of large-scale sequencing data from the human genome project and similar projects for other organisms. Consequently, bioinformaticians are playing an increasingly essential role in genetics research by performing analysis on this large amount of data using automated pipelines to characterize genes, predict their structures, and identify variants in the sequences. #healthquestrcm #RCM #medicalbilling #R&D #bioinformatics #taxes #usa

Groundbreaking developments in human genomics! A recent landmark study, "Nanopore sequencing of 1000 Genomes Project samples to build a comprehensive catalog of human genetic variation" has leveraged long-read sequencing to dive deep into the genetic diversity among human populations. The study aims to enhance the granularity of human genetic variation mapping by generating long-read data from at least 800 samples of the renowned 1000 Genomes Project. Initial analysis of the first 100 samples has already yielded an average of 24,543 high-confidence structural variations (SVs) per genome, including shared and private SVs that could disrupt gene function and pathogenic expansions in disease-associated repeats not detectable by short reads. This comprehensive SV catalog could transform clinical genetics by facilitating the discovery of pathogenic variants in unsolved cases. By providing a robust resource for variant filtering and prioritization, this endeavor could significantly improve the diagnostic yield for individuals with suspected genetic conditions. Moreover, the study showcases the power of long-reads in uncovering complex genomic features such as repeat expansions and methylation patterns, offering new insights into their roles in human diseases. It's a significant leap forward in our quest to elucidate the genetic basis of diseases and paves the way for personalized medicine. This huge milestone in the 1000 Genomes Project introduces a highly valuable resource for understanding the complex landscape of human genetic variation. Check it out the link in the comment!

A study found that changes to certain parts of the genetic code due to environmental factors in early development could increase the risk of developing Alzheimer's disease, especially for Black individuals compared to white. Key Findings: • Scientists examined brain tissue samples from 17 donors, comprising nine brains with Alzheimer’s and eight without. The donors were divided into groups based on ethnicity, with both non-Hispanic white and non-Hispanic Black individuals represented. In the Alzheimer’s group, there were five samples from Black donors and four from white donors. • The researchers sequenced the complete genome of each sample and subsequently identified regions of the genome in Alzheimer’s brains that exhibited either higher or lower levels of methylation compared to healthy brains. • They identified 120 distinct differently methylated implant control regions in the Alzheimer’s brains. Among these, 40 were present in both Black and white populations. However, 81 were exclusive to the Black population, while 27 were exclusive to the white population. • The variably methylated implant control regions shared by both populations are linked to (MEST/MESTIT1), a gene expressed paternally, and NLRP1, a gene implicated in brain inflammation and predicted to be imprinted. #SOTMember co-author of this study: • #SOTRetiredMember Randy Jirtle of North Carolina State University Learn more: https://lnkd.in/gKyeYxbY

Extra fingers and hearts: Pinpointing changes to our genetic instructions that disrupt development Researchers find a vulnerability within our genomes that can cause developmental defects such as extra fingers and heart disorders. Scientists can now predict which single-letter changes to the DNA within our genomes will alter genetic instructions and disrupt development, leading to changes such as the growth of extra digits and hearts. Such knowledge opens the door to predictions of which enhancer variants underlie disease in order to harness the full potential of our genomes for better human health. Our genomes provide the instructions for proper growth and development. Millions of genomic switches, known as enhancers, control the location and timing of gene expression, which in turn ensures the correct proteins are made in the right cells at the right time throughout our lives. New research from University of California San Diego Assistant Professor Emma Farley's lab shows how we can now predict which single base-pair changes to the DNA within our genomes will alter these instructions and disrupt development, causing extra digits and hearts. We now have genome sequences for over half a million people and counting. These genomes hold the key to how each of us comes to be and the promise of attaining precision medicine tailored to an individual's own genetic makeup. Yet we cannot take full advantage of these datasets since we don't understand a critical aspect of the genome: enhancers, which act as switches to control when and where our genes are expressed as proteins. Most genetic variants or mutations that cause disease lie within these enhancers. A central challenge has been to determine which sequence changes within enhancers matter and which do not. Thus far, pinpointing such causal enhancer variants has been akin to searching for a needle in a haystack.the Farley lab has addressed this challenge by achieving the ability to predict which changes to enhancers would cause changes in gene expression across thousands of enhancers and cell types. This ability to predict causal enhancer variants is rooted in a deep understanding of how enhancers function. The researchers showed that enhancers activate gene expression by binding proteins known as transcription factors very weakly. Adhering to this rule ensures enhancers activate gene expression, and thus protein production, at the right level, place and time. The Farley lab found that single-letter changes to our genome that strengthen the interaction of an enhancer with a transcription factor cause enhancers to switch on gene expression inappropriately and make proteins at the wrong level, time and/or place. #finger #heart #genetic #genome #dna #proteins #mutations #variants #cells #protein

Recent studies have shown that the genomes in each of our cells are not static but are continuously changing because of the somatic mutations that occur as we develop and age. With the evolution of more accurate methods of single-cell sequencing, we now know that those somatic mutations are present at higher levels than previously anticipated. The question has become: are those mutations just passengers of life with little consequence, or do they contribute to the formation of human diseases? Dr. Charles Gawad explores this question, its implications, and research trends in the January edition of Genetic Engineering & Biotechnology News: https://lnkd.in/ei3eHAJ8

What are the differences between Genetic Disease and Hereditary Disease? - 1st Most Asked Questions by SuperDNA's clients: Genetic disease occurs because of an alteration (aka mutation) in our DNA that can be caused by an error in DNA replication or by environmental factors (e.g. cigarette smoke or exposure to radiation). The disease can manifest itself at any age. On the other hand, a hereditary disease is caused by alterations in the DNA, and transmitted from parents to children. In an example of cancer, hereditary cancer represents only about 5-20% of all cancers while the most common cause of cancer are acquired mutations. That explains why not all cancers are transmitted down the family line. Only those that are transmitted from generation to generation are hereditary. And this applies to all diseases. SuperDNA offers the most comprehensive sequencing-based genetic predisposition test that aims to provide key genetic information to people in order to prevent diseases and improve health. Reference - https://lnkd.in/grfdKaRZ #genetictesting #malaysia #mysuperdna #superdna #preventivecare #earlydetection

Genetic Variation, Comparative Genomics, and the Diagnosis of Disease The discovery of mutations associated with human genetic disease is an exercise in comparative genomics (see Glossary). Although there are many different strategies and approaches, the central premise is that affected persons harbor a significant excess of pathogenic DNA variants as compared with a group of unaffected persons (controls) that is either clinically defined1 or established by surveying large swaths of the general population.2 The more exclusive the variant is to the disease, the greater its penetrance, the larger its effect size, and the more relevant it becomes to both disease diagnosis and future therapeutic investigation. The most popular approach used by researchers in human genetics is the case–control design, but there are others that can be used to track variants and disease in a family context or that consider the probability of different classes of mutations based on evolutionary patterns of divergence or de novo mutational change.3,4 Although the approaches may be straightforward, the discovery of pathogenic variation and its mechanism of action often is less trivial, and decades of research can be required in order to identify the variants underlying both mendelian and complex genetic traits (see video, available at NEJM.org). https://lnkd.in/d5bipjuB