Aoife Doherty, BSc MSc PhD

The prevalence of prediabetes is rapidly increasing, and this can lead to an increased risk for individuals to develop type 2 diabetes and associated diseases. Therefore, it is necessary to develop nutritional strategies to maintain healthy glucose levels and prevent glucose metabolism dysregulation in the general population. Functional ingredients offer great potential for the prevention of various health conditions, including blood glucose regulation, in a cost-effective manner. Using an… Show more

The prevalence of prediabetes is rapidly increasing, and this can lead to an increased risk for individuals to develop type 2 diabetes and associated diseases. Therefore, it is necessary to develop nutritional strategies to maintain healthy glucose levels and prevent glucose metabolism dysregulation in the general population. Functional ingredients offer great potential for the prevention of various health conditions, including blood glucose regulation, in a cost-effective manner. Using an artificial intelligence (AI) approach, a functional ingredient, NRT_N0G5IJ, was predicted and produced from Pisum sativum (pea) protein by hydrolysis and then validated. Treatment of human skeletal muscle cells with NRT_N0G5IJ significantly increased glucose uptake, indicating efficacy of this ingredient in vitro. When db/db diabetic mice were treated with NRT_N0G5IJ, we observed a significant reduction in glycated haemoglobin (HbA1c) levels and a concomitant benefit on fasting glucose. A pilot double-blinded, placebo controlled human trial in a population of healthy individuals with elevated HbA1c (5.6% to 6.4%) showed that HbA1c percentage was significantly reduced when NRT_N0G5IJ was supplemented in the diet over a 12-week period. Here, we provide evidence of an AI approach to discovery and demonstrate that a functional ingredient identified using this technology could be used as a supplement to maintain healthy glucose regulation. Show less

In publication process.

With the proportion of older people among the global population now higher than at any point in human history and still expanding, maintaining health into old age (i.e. healthspan) has become a new and urgent frontier for modern medicine. Age is a major risk factor for most of the top 10 causes of death worldwide, such as ischaemic heart disease, Alzheimer’s disease, cancer and the largest known human pandemic, diabetes. Therefore, it is clear that while we are… Show more

In publication process.

With the proportion of older people among the global population now higher than at any point in human history and still expanding, maintaining health into old age (i.e. healthspan) has become a new and urgent frontier for modern medicine. Age is a major risk factor for most of the top 10 causes of death worldwide, such as ischaemic heart disease, Alzheimer’s disease, cancer and the largest known human pandemic, diabetes. Therefore, it is clear that while we are living longer, the ability to prevent the majority of age-related diseases and improve healthspan has not been successfully addressed. There are dramatic consequences of poor healthspan on public expenditure. In both the United States and Europe, 97% of public healthcare budgets are allocated to treatment, leaving only 3% to spend on prevention. While such a model may have been sustainable in the past, these issues must be urgently solved as the pace of the entire globe ageing is increasing dramatically around the world. Over 150 years, France slowly adapted to a change from 10% to 20% in the proportion of the population that was older than 60 years old. However, much larger countries such as Brazil, India and China have slightly more than 20 years to devise and implement the same adaptations. This viewpoint provides a short discussion on how nutritional interventions can positively impact global healthcare costs for some of the World's biggest killers today, in particular when analysed with the newest methods in the Artificial Intelligence sphere. Show less

Selective breeding of the domestic dog (Canis lupus familiaris) rigidly retains desirable features, and could inadvertently fix disease-causing variants within a breed. We combine phenotypic data from > 72,000 dogs with a large genotypic dataset to search for genes associated with cancer mortality and longevity in pedigree dog breeds. We validated previous findings that breeds with higher average body weight have higher cancer mortality rates and lower life expectancy. We identified a… Show more

Selective breeding of the domestic dog (Canis lupus familiaris) rigidly retains desirable features, and could inadvertently fix disease-causing variants within a breed. We combine phenotypic data from > 72,000 dogs with a large genotypic dataset to search for genes associated with cancer mortality and longevity in pedigree dog breeds. We validated previous findings that breeds with higher average body weight have higher cancer mortality rates and lower life expectancy. We identified a significant positive correlation between life span and cancer mortality residuals corrected for body weight, implying that long-lived breeds die more frequently from cancer compared to short-lived breeds. We replicated a number of known genetic associations with body weight (IGF1, GHR, CD36, SMAD2 and IGF2BP2). Subsequently, we identified five genetic variants in known cancer-related genes (located within SIPA1, ADCY7 and ARNT2) that could be associated with cancer mortality residuals corrected for confounding factors. One putative genetic variant was marginally significantly associated with longevity residuals that had been corrected for the effects of body weight; this genetic variant is located within PRDX1, a peroxiredoxin that belongs to an emerging class of pro-longevity associated genes. This research should be considered as an exploratory analysis to uncover associations between genes and longevity/cancer mortality. Show less

Understanding the expression changes that come with age is an important step in understanding the ageing process as a whole. By combining such transcriptomic data with other sources of information, for instance protein-protein interaction (PPI) data, it is possible to make inferences about the functional changes that occur with age. To address this, we conducted a meta-analysis on 127 publicly available microarray and RNA-Seq datasets from mice, rats and humans, to identify genes that are… Show more

Understanding the expression changes that come with age is an important step in understanding the ageing process as a whole. By combining such transcriptomic data with other sources of information, for instance protein-protein interaction (PPI) data, it is possible to make inferences about the functional changes that occur with age. To address this, we conducted a meta-analysis on 127 publicly available microarray and RNA-Seq datasets from mice, rats and humans, to identify genes that are commonly differentially expressed with age in mammals. We also conducted analyses on subsets of these datasets, to produce transcriptomic signatures for brain, heart and muscle tissues, all of which are important tissues in the pathophysiology of ageing. This approach identified the transcriptomic signatures of the ageing system, as well as brain, heart and muscle tissues. We then applied enrichment analysis and machine learning to functionally describe those signatures. This revealed a typical ageing signature including the overexpression of immune and stress response genes and the underexpression of metabolic and developmental genes. Further analysis of the ageing expression signatures revealed that genes differentially expressed with age tend to be broadly expressed across tissues, rather than be tissue-specific, and that the ageing expression signatures (particularly the overexpressed signatures) of the whole system, brain and muscle tend to include genes that are central in PPI networks. We also show that genes underexpressed in the brain are highly central in a co-expression map, suggesting that underexpression of these genes may play a part in cognitive ageing. In sum, we show numerous functional similarities between the ageing transcriptomes of these important tissues, a broad non-specific expression pattern in genes differentially expressed with age, along with altered network properties of these genes in both a PPI and co-expression network. Show less

Cancer is a disease of multicellularity; it originates when cells become dysregulated due to mutations and grow out of control, invading other tissues and provoking discomfort, disability, and eventually death. Human life expectancy has greatly increased in the last two centuries, and consequently so has the incidence of cancer. However, how cancer patterns in humans compare to those of other species remains largely unknown. In this review, we search for clues about cancer and its evolutionary… Show more

Cancer is a disease of multicellularity; it originates when cells become dysregulated due to mutations and grow out of control, invading other tissues and provoking discomfort, disability, and eventually death. Human life expectancy has greatly increased in the last two centuries, and consequently so has the incidence of cancer. However, how cancer patterns in humans compare to those of other species remains largely unknown. In this review, we search for clues about cancer and its evolutionary underpinnings across the tree of life. We discuss data from a wide range of species, drawing comparisons with humans when adequate, and interpret our findings from an evolutionary perspective. We conclude that certain cancers are uniquely common in humans, such as lung, prostate, and testicular cancer; while others are common across many species. Lymphomas appear in almost every animal analysed, including in young animals, which may be related to pathogens imposing selection on the immune system. Cancers unique to humans may be due to our modern environment or may be evolutionary accidents: random events in the evolution of our species. Finally, we find that cancer‐resistant animals such as whales and mole‐rats have evolved cellular mechanisms that help them avoid neoplasia, and we argue that there are multiple natural routes to cancer resistance. Show less

This work uses the Random Forest (RF) classification algorithm to predict if a gene is overexpressed, underexpressed or has no change in expression with age in the brain. RFs have high predictive power, and RF models can be interpreted using a feature (variable) importance measure. However, current feature importance measures evaluate a feature as a whole (all feature values). We show that, for a popular type of biological data (Gene Ontology-based), usually only one value of a feature is… Show more

This work uses the Random Forest (RF) classification algorithm to predict if a gene is overexpressed, underexpressed or has no change in expression with age in the brain. RFs have high predictive power, and RF models can be interpreted using a feature (variable) importance measure. However, current feature importance measures evaluate a feature as a whole (all feature values). We show that, for a popular type of biological data (Gene Ontology-based), usually only one value of a feature is particularly important for classification and the interpretation of the RF model. Hence, we propose a new algorithm for identifying the most important and most informative feature values in an RF model. The new feature importance measure identified highly relevant Gene Ontology terms for the aforementioned gene classification task, producing a feature ranking that is much more informative to biologists than an alternative, state-of-the-art feature importance measure. Show less

The World Health Organization predicts that the proportion of the world's population over 60 will almost double from 12% to 22% between 2015 and 2050. Ageing is the biggest risk factor for cancer, which is a leading cause of deaths worldwide. Unfortunately, research describing how genetic variants affect cancer progression commonly neglects to account for the ageing process. Herein is the first systematic analysis that combines a large longitudinal data set with a targeted candidate gene… Show more

The World Health Organization predicts that the proportion of the world's population over 60 will almost double from 12% to 22% between 2015 and 2050. Ageing is the biggest risk factor for cancer, which is a leading cause of deaths worldwide. Unfortunately, research describing how genetic variants affect cancer progression commonly neglects to account for the ageing process. Herein is the first systematic analysis that combines a large longitudinal data set with a targeted candidate gene approach to examine the effect of genetic variation on survival as a function of age in cancer patients. Survival was significantly decreased in individuals with heterozygote or rare homozygote (i.e. variant) genotypes compared to those with a common homozygote genotype (i.e. wild type) for two single nucleotide polymorphisms (rs11574358 and rs4147918), one gene (SIRT3) and one pathway (FoxO signalling) in an age-dependent manner. All identified genes and pathways have previously been associated with ageing and cancer. These observations demonstrate that there are ageing-related genetic elements that differentially affect mortality in cancer patients in an age-dependent manner. Understanding the genetic determinants affecting prognosis differently with age will be invaluable to develop age-specific prognostic biomarkers and personalized therapies that may improve clinical outcomes for older individuals. Show less

One of the greatest unresolved questions in aging biology is determining the genetic basis of inter-species longevity variation. Gene duplication is often the key to understanding the origin and evolution of important Eutherian phenotypes. We systematically identified longevity-associated genes in model organisms that duplicated throughout Eutherian evolution.

Longevity-associated gene families have a marginally significantly higher rate of duplication compared to non-longevity… Show more

One of the greatest unresolved questions in aging biology is determining the genetic basis of inter-species longevity variation. Gene duplication is often the key to understanding the origin and evolution of important Eutherian phenotypes. We systematically identified longevity-associated genes in model organisms that duplicated throughout Eutherian evolution.

Longevity-associated gene families have a marginally significantly higher rate of duplication compared to non-longevity associated gene families. Anti-longevity associated gene families have a significantly increased rate of duplication compared to pro-longevity gene families and are enriched in neurodegenerative disease categories. Conversely, pro-longevity associated gene families are enriched in cell cycle genes.

There is a cluster of longevity associated gene families that expanded solely in long-lived species that is significantly enriched in pathways relating to 3-UTR mediated translational regulation, metabolism of proteins and gene expression; pathways which have the potential to affect longevity. The identification of a gene cluster that duplicated solely in long-lived species involved in such fundamental processes provides a promising avenue for further exploration of Eutherian longevity evolution. Show less

Polar bears are uniquely adapted to life in the High Arctic and have undergone drastic physiological changes in response to Arctic climates and a hyperlipid diet of primarily marine mammal prey. We analyzed 89 complete genomes of polar bear and brown bear using population genomic modeling and show that the species diverged only 479–343 thousand years BP. We find that genes on the polar bear lineage have been under stronger positive selection than in brown bears; nine of the top 16 genes under… Show more

Polar bears are uniquely adapted to life in the High Arctic and have undergone drastic physiological changes in response to Arctic climates and a hyperlipid diet of primarily marine mammal prey. We analyzed 89 complete genomes of polar bear and brown bear using population genomic modeling and show that the species diverged only 479–343 thousand years BP. We find that genes on the polar bear lineage have been under stronger positive selection than in brown bears; nine of the top 16 genes under strong positive selection are associated with cardiomyopathy and vascular disease, implying important reorganization of the cardiovascular system. One of the genes showing the strongest evidence of selection, APOB, encodes the primary lipoprotein component of low-density lipoprotein (LDL); functional mutations in APOB may explain how polar bears are able to cope with life-long elevated LDL levels that are associated with high risk of heart disease in humans. Show less

Synonymous codon usage patterns are shaped by a balance between mutation, drift, and natural selection. To date, detection of translational selection in vertebrates has proven to be a challenging task, obscured by small long-term effective population sizes in larger animals and the existence of isochores in some species. The consensus is that, in such species, natural selection is either completely ineffective at overcoming mutational pressures and genetic drift or perhaps is effective but so… Show more

Synonymous codon usage patterns are shaped by a balance between mutation, drift, and natural selection. To date, detection of translational selection in vertebrates has proven to be a challenging task, obscured by small long-term effective population sizes in larger animals and the existence of isochores in some species. The consensus is that, in such species, natural selection is either completely ineffective at overcoming mutational pressures and genetic drift or perhaps is effective but so weak that it is not detectable. The aim of this research is to understand the interplay between mutation, selection, and genetic drift in vertebrates. We observe that although variation in mutational bias is undoubtedly the dominant force influencing codon usage, translational selection acts as a weak additional factor influencing synonymous codon usage. These observations indicate that translational selection is a widespread phenomenon in vertebrates and is not limited to a few species. Show less

Although gene duplications occur at a higher rate, only a small fraction of these are retained. The position of a gene’s encoded product in the protein–protein interaction network has recently emerged as a determining factor of gene duplicability. However, the direction of the relationship between network centrality and duplicability is not universal: In Escherichia coli, yeast, fly, and worm, duplicated genes more often act at the periphery of the network, whereas in humans, such genes tend to… Show more

Although gene duplications occur at a higher rate, only a small fraction of these are retained. The position of a gene’s encoded product in the protein–protein interaction network has recently emerged as a determining factor of gene duplicability. However, the direction of the relationship between network centrality and duplicability is not universal: In Escherichia coli, yeast, fly, and worm, duplicated genes more often act at the periphery of the network, whereas in humans, such genes tend to occupy the most central positions. Herein, we have inferred duplication events that took place in the different branches of the primate phylogeny. In agreement with previous observations, we found that duplications generally affected the most central network genes, which is presumably the process that has most influenced the trend in humans. However, the opposite trend—that is, duplication being more common in genes whose encoded products are peripheral in the network—is observed for three recent branches, including, quite counterintuitively, the external branch leading to humans. This indicates a shift in the relationship between centrality and duplicability during primate evolution. Furthermore, we found that genes encoding interacting proteins exhibit phylogenetic tree topologies that are more similar than expected for random pairs and that genes duplicated in a given branch of the phylogeny tend to interact with those that duplicated in the same lineage. These results indicate that duplication of a gene increases the likelihood of duplication of its interacting partners. Our observations indicate that the structure of the primate protein–protein interaction network affects gene duplicability in previously unrecognized ways. Show less

Scientific research consistently demonstrates that diseases may be delayed, treated, or even prevented and, thereby, health may be maintained with health-promoting functional food ingredients (FFIs). Consumers are increasingly demanding sound information about food, nutrition, nutrients, and their associated health benefits. Consequently, a nutrition industry is being formed around natural foods and FFIs, the economic growth of which is increasingly driven by consumer decisions. Information… Show more

Scientific research consistently demonstrates that diseases may be delayed, treated, or even prevented and, thereby, health may be maintained with health-promoting functional food ingredients (FFIs). Consumers are increasingly demanding sound information about food, nutrition, nutrients, and their associated health benefits. Consequently, a nutrition industry is being formed around natural foods and FFIs, the economic growth of which is increasingly driven by consumer decisions. Information technology, in particular artificial intelligence (AI), is primed to vastly expand the pool of characterised and annotated FFIs available to consumers, by systematically discovering and characterising natural, validated, and safe bioactive ingredients (bioactives) that address specific health needs. However, FFI-producing companies are lagging in adopting AI technology for their ingredient development pipelines for several reasons, resulting in a lack of efficient means for large-scale and high-throughput molecular and functional ingredient characterisation. The arrival of the AI-led technological revolution allows for the comprehensive characterisation and understanding of the universe of FFI molecules, enabling the mining of the food and natural product space in an unprecedented manner. In turn, this expansion of bioactives dramatically increases the repertoire of FFIs available to the consumer, ultimately resulting in bioactives being specifically developed to target unmet health needs. Show less