Novogene’s Technical Support Supervisor, Dr Shelly Pathak, along with collaborator Dr Payal Ganguly, Postdoctoral Research Fellow at the University of Leeds, published a review article entitled “Aging, Bone Marrow and Next-Generation Sequencing (NGS): Recent Advances and Future Perspectives” in the International Journal of Molecular Science in November 2021. To mark the publication of their review article Dr Pathak and Dr Ganguly delivered a Novogene webinar outlining the findings of the paper. You can listen back to the webinar on-demand here.
The global aging population, classified as individuals over 60 years of age, is predicted to be over 2 billion strong by 2050, increasing to 3.1 billion by 2100. Aging is a complex process that can result in reduced mobility, increased vulnerability to disease, cognitive impairment, decreased quality of life, and the onset of age-related diseases (ARDs). Not all aging individuals will suffer with ARDs, and many will age healthily, but little is understood about the underlying mechanisms of the transition from healthy aging to the development of ARDs.
Aging has been defined as low-grade sterile inflammation, with “inflammaging” being coined as the term referring to the inflammation related to aging. This inflammation is responsible for the changes seen in the body throughout what is considered healthy aging, such as accumulation of intracellular damage, decline in cellular proliferation and decline in regenerative capacity. However, at some point, the molecular switch of which is still unclear, these changes can lead to the development of ARDs such as cancer, cardiovascular diseases (CVDs), musculoskeletal degenerative diseases, and neurodegenerative diseases.
There are 9 accepted hallmarks of aging, clustered into 3 categories by Lopez-Otin et al., 2013. The first category is the primary hallmarks – genomic instability, telomere attrition, epigenetic alterations, and loss of proteostasis. These hallmarks cause the cellular damage that is characteristic of aging. The antagonistic hallmarks – deregulated nutrient sensing, mitochondrial dysfunction, and cellular senescence – are responses to the damage caused by the primary hallmarks. The third category includes the integrative hallmarks – stem cell exhaustion and altered intercellular communication – which are culprits of the aging phenotype.
Either one or a combination of many of these 9 hallmarks of aging has been linked to reduced mobility, rigid and painful joints, alterations in musculoskeletal systems, increased vulnerability to bone and joint disorders, and inflammation. In all of these disorders, the musculoskeletal system and the cells within it play a role, which is why study of the bone marrow in relation to aging is gaining traction.
The bone marrow is considered an organ with an intricate 3D structure which houses multiple cell types, growth factors, cytokines, and other soluble factors. Two stem cell populations exist within the bone marrow – hematopoietic stems cells (HSCs) and mesenchymal stem cells (MSCs). MSCs differentiate into chondrocytes, osteoblasts, and adipocytes, which are responsible for the formation of cartilage, bone, and fat, respectively. HSCs differentiate into common lymphoid progenitor cells and common myeloid progenitor cells. Common lymphoid progenitors differentiate to form the B cells, T cells and Natural Killer cells of the immune system, and common myeloid progenitors ultimately form the four blood cell types – monocytes, granulocytes, megakaryocytes, and erythrocytes.
Many of these cell types and their progenitors undergo significant changes within the bone marrow during the aging process. The bone marrow is a unique microenvironment, but many previous studies have focused only on individual cell types. The aim of this review was to assess the effects of aging on the bone marrow as a whole organ. Alterations in the cellularity of the bone marrow include changes in proliferative capacity and reduced functionalities and differentiation abilities. Most cell populations decrease but some increase to compensate for reduced functionality. MSCs are responsible for the bone-fat balance within the body as they produce osteocytes and adipocytes, and this balance is lost in older donors, with a skew towards adipose tissue synthesis. HSCs often skew towards the formation of myeloid progenitor cells and away from lymphoid progenitor cells, meaning a reduction in immune cell population and an increase in malignancies associated with cells of myeloid origin. All of these factors are caused by damage to the DNA and genomic instability, the latter being the first primary hallmark of aging. Damage to the DNA is reflected at an epigenetic level and at the RNA transcript level, both of which can be analysed by Next Generation Sequencing (NGS) techniques.
NGS emerged from initial Sanger sequencing methods. It involves random fragmentation of the DNA strands to be sequenced into 100-300bp fragments, the addition of adaptors and immobilisation for library prep, and the selection of libraries based on size. These libraries are then subjected to sequencing, with the sequences then assembled and mapped to the reference genome of the organism being studied. Bioinformatic analysis is utilised to provide information on the molecular networks active within the cell types and under the conditions that are being studied.
NGS has been used to study DNA damage to HSCs within the bone marrow, the cells responsible for lymphoid and myeloid progenitors. Mutations in stem cells can cause problems down the line of differentiation, potentially resulting in haematological malignancies. Not all such mutations will have a functional effect on the body, but some mutations can make cells independent of growth factors or result in the development of resistance to growth factors and other signalling molecules, as is the case with many haematological cancers. NGS has allowed scientists to study the genome, exome, and transcriptome of the cells residing in the BM in order to understand the underlying molecular mechanisms of these changes.
Targeted sequencing is a rapid form of sequencing used to identify known and novel variants within specific parts of the genome. The most common types are hybridisation capture and amplicon sequencing. An example of a targeted sequencing application is a study conducted by Pathak et al., 2019, which was an exploratory study of MYD88 L265P, rare NLRP3 variants, and clonal haematopoiesis prevalence in patients with Schnitzler Syndrome, an acquired/late onset auto-inflammatory disease with symptoms including joint and bone pain and abnormal bone imaging findings. The study analysed a panel of 28 genes within HSCs related to aging, including the development of clonal haematopoiesis and myelodysplastic syndrome. Only one patient was discovered to have a nonsense mutation in an age-related gene, resulting in the conclusion of no involvement of clonal haematopoiesis or age-related mutations in this bone marrow disorder.
Another study, which employed NGS to analyse mutations within bone marrow cells related to aging, used single-cell RNA and bulk RNA sequencing. This study took a wider approach, using SMART sequencing, a single-cell technique developed to provide full genome coverage, permitting the detection of alternative transcript isoforms and SNPs. The HSC population was divided into 6 sub-populations, and it was found that levels of mRNA transcripts of age-related glycolytic enzymes were markedly higher in myeloid-derived populations than lymphoid-derived populations. In conclusion, it was found that these changes reduce the pathway functions involved in human haematopoietic stem and progenitor cell homing.
Until this point, the use of NGS in the study of the aging bone marrow has been applied to samples from aging donors. Within their review, Dr Pathak and Dr Ganguly propose the need for study of samples from the wider age range of 18-90. This will assist with understanding the underlying molecular mechanisms of “healthy aging” and the switch that occurs when individuals transition from a healthy aging process to the development of ARDs. Skeletal aging is suggested to being within the fifth decade of life so studying samples from individuals of 40-60 years of age may help identify early markers of “inflammaging”. Comparative transcriptomic studies with reads from healthy aging adults and those with ARDs will help to pin down the genetic profile transition that occurs in the development of ARDs. These approaches may also assist in the early detection of ARDs and slowing the progression of debilitating diseases such as cancer, CVD, and painful joint disorders. Improving patients’ quality of life (QOL) through personalised therapies is the main long-term goal of such strategies.
However, many challenges remain within the NGS field, mostly related to data output and storage, and downstream analysis. Technical challenges mainly involve quality and quantity of the genetic material extracted for analysis. Certain cell populations, such as B and T cells, decline with age and extracting sufficient quantities from older donors can pose challenges during library preparation. Another challenge presented in the field is data storage. One alignment file accounting for 30x coverage of the human genome can generate between 90 and 95GB of data. Applying this to 10 samples will generate almost 1TB of data. One potential solution to this problem is the sharing and deposition of sequences in public domains. The National Centre for Biotechnology Information (NCBI) has an ever-growing bank of such data. These databases allow for filtering of different parameters, and you may find that the data of a control sample you require is already there.
The last couple of decades have increased our understanding of age-related changes within the bone marrow. However, novel techniques providing data at the genetic level are essential for discovering pathways responsible for the cellular changes within the aging bone marrow. Focussing on gene panels aimed at the proliferation, differentiation, migration, and homing of these cells with advancing age will also add to our knowledgebase of aging bone marrow. This will help us underpin the pathways involved in the transition from healthy aging to ARD, allowing for applications in early diagnosis and enhanced care and QOL of the elderly.
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