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A New Wave of Genomics for All

25 years ago, the Human Genome Project revolutionized life sciences research, diagnostics and treatment practices – much like landing on the moon!

The next wave of genomics will advance on this progress by providing insights that make vast amounts of medical device and electronic health records data actionable, such as detecting minimal residual disease after cancer treatment or providing more tailored healthcare.

Single-Cell Genomics

Single-cell genomic technologies are providing unprecedented clarity into tissue composition, identities and states. When combined with genotype data and additional phenotypic measurements, we may be able to link genetic variation with biological pathways governing biological trajectories; this has great implication for disease diagnosis, risk prediction and therapeutic development; however integrating large-scale single-cell genomics analyses will require new computational approaches which enable multimodal data analyses that scale.

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Single-cell genomics is currently at an inflection point. With emerging technologies becoming more cost-effective and requiring less specialized equipment157, and being amenable to high-throughput applications158, we anticipate these advancements will accelerate sc-eQTL discovery rates while opening up opportunities for novel types of association analysis (such as finding variants that change with cell context or influence certain cellular pathways).

Single-cell genomics provides new insight into the molecular mechanisms underlying complex diseases, while also opening up opportunities to increase diagnosis rates of severe monogenic conditions by providing more in-depth understanding of variants that influence their biology. Furthermore, single-cell genomics has made possible the creation of polygenic risk scores (PRSs) for common diseases by aggregating thousands of association signals into individual scores that quantify an individual’s risk for disorder49.

Genome-wide association studies (GWASs) have identified over 400,000 genetic associations for human traits and diseases.1 However, one key challenge remains: no clear evidence showing the functional impact of these variants on biological systems.

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One promising approach for overcoming this barrier is using single-cell expression quantitative trait loci (sc-eQTL) analyses as a population level approach to link genetics with cell measurements and phenotypes using single-cell genome sequencing technology. Sc-eQTL analyzes use this single cell genome sequencing technology to measure gene expression within genotyped cohorts, cluster similar cells phenotypically similar cells together and associate aggregated gene expression levels with associated genotypes – this approach is similar to bulk RNA-seq approaches used in genome wide association studies (GWAS). Sc-eQTL methods can also be applied across samples comprising multiple cell types to identify subset of genes associated with particular diseases or phenotypes.

Personalized Medicine

Personalized Medicine (PM) refers to tailoring preventive, diagnostic and therapeutic strategies specifically for an individual patient’s phenotype or genotype. The field includes various clinical activities and research projects including genetic testing, personalized biomarker development and the identification of causal gene mutations as well as genome editing technologies such as CRISPR/Cas9. Incorporation of new knowledge gained through these advances into health care practices and systems are also part of personalized medicine’s mandate.

PM is an expanding field of research and health care that holds immense promise. It has led to the creation of various medical interventions such as personalized disease treatments and early detection protocols; identified disease risk factors; and tailored screening strategies for uncommon illnesses like colorectal cancer.

Genetic screening for BRCA1 and BRCA2 has enabled women who may be at an increased risk for breast cancer to be identified; this was one of the earliest examples of personalized medicine (PM). More recently, however, a large-scale study discovered that certain variants of G6PD gene can increase an individual’s risk for type 1 diabetes; such variants could then be treated individually through drug therapy to decrease its prevalence among its carriers.

These developments represent just the start of personalized medicine’s potential future impact, which may range from treatments to prevention and screening. The challenge will be in finding tools and technologies suitable for use within health care systems as well as ways of evaluating their potential benefits to public health.

As important as genomics and personalized medicine are, many obstacles remain to fully realizing their full promise. One significant barrier is medical professionals being trained only in specific disease areas with limited awareness of other disciplines – this may make utilizing all available tools and technology difficult; hopefully this will change as this field advances further.

Personalized Prevention

Personalized prevention refers to an approach that integrates sociodemographic, clinical and anthropometrical factors, biomarkers and genomic (genomics, transcriptomics, proteomics and metabolomics) data to predict an individual’s risk for diseases (Figure 1). Genomic data may also be utilized for targeted and cost-effective preventive interventions resulting in improved care delivery and cost management.

Notable among the new government’s many achievements is its recognition that personalised prevention approaches could have an enormous impact on NHS demand and should not divert focus away from areas that already demonstrate improvement in outcomes and reduce inequality.

If your DNA indicates that you are more predisposed to certain diseases such as breast cancer or Type II diabetes, for instance, screening with 92 commonly tested SNPs would provide valuable diagnostic data as well as reduce costs by screening before treating. This would not only save time waiting to see your GP but it would be far cheaper for the health service as screening would likely save more lives than treating after they develop these conditions.

As genomic sequencing technology becomes less expensive, it will become possible to sequence your entire genome and discover exactly which genes contribute to your unique biological makeup and their interactions with your environment. This information can help develop preventive strategies such as diet advice, exercise programs, quitting smoking cessation efforts, weight management techniques and cognitive enhancement as well as other lifestyle factors.

At this stage, mapping activities and the PROPHET assessment framework will be further refined, refined and integrated into a Strategic Research and Innovation Agenda (SRIA), to guide the Building phase and provide useful information to decision-makers about how best to implement personalized prevention in healthcare. In particular, PROPHET seeks to collaborate with existing and forthcoming initiatives at EU level while maximising potential impact of its work – through such an inclusive approach we can ensure genomics fulfills its full promise in helping prevent avoidable diseases in future and enable people to lead healthier lives.

Personalized Care

Personalized care strives to provide individuals with the optimal treatment for their conditions by tailoring medications and interventions to each person’s unique genetic profile. In order for this strategy to succeed, however, a holistic approach that includes genomic mapping as part of comprehensive care models must also be utilized; providing access to genetic testing must go hand in hand with overcoming healthcare barriers that prevent people from receiving the care they require.

Personalizing healthcare to meet individual genomes could offer many patients improved results and an optimistic outlook, but its full potential has yet to be realized; according to a McKinsey survey of US consumers only 4% believe their healthcare was tailored specifically for them.

Realizing personalized healthcare will require a paradigm shift in how we view what constitutes quality healthcare services, from organizing and financing services, as well as our interactions with patients, to empowering patients to become active partners with their doctors and providing them with tools necessary for making informed decisions regarding their own treatment.

Personalized care will inevitably require new technologies that enable physicians to quickly identify and interpret an individual’s unique gene sequence. Thanks to advances like next-generation sequencing technology, this goal has become possible more quickly than ever at an affordable price point. By reading an entire genome in hours instead of years or thousands more expensive methods used before.

As we gain more knowledge of the human genome, we will be able to detect changes in individual genes which increase their risk for certain illnesses and take preemptive steps to either prevent illness or delay its onset. An emerging field called polygenic risk scores uses data on an individual’s genes as an assessment of overall risk for diseases.

The NHS is currently rolling out a comprehensive model of personalized care to 2.5 million people and hopes to double it within a decade. By employing behavior change frameworks, WASP Service Evaluation Tool enables health and social care systems to better understand whether personalized care is working.

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