There is a great deal of hype surrounding the concept of personalized medicine. Personalized medicine is rooted in the belief that since individuals possess nuanced and unique characteristics at the ...molecular, physiological, environmental exposure, and behavioral levels, they may need to have interventions provided to them for diseases they possess that are tailored to these nuanced and unique characteristics. This belief has been verified to some degree through the application of emerging technologies such as DNA sequencing, proteomics, imaging protocols, and wireless health monitoring devices, which have revealed great inter-individual variation in disease processes. In this review, we consider the motivation for personalized medicine, its historical precedents, the emerging technologies that are enabling it, some recent experiences including successes and setbacks, ways of vetting and deploying personalized medicines, and future directions, including potential ways of treating individuals with fertility and sterility issues. We also consider current limitations of personalized medicine. We ultimately argue that since aspects of personalized medicine are rooted in biological realities, personalized medicine practices in certain contexts are likely to be inevitable, especially as relevant assays and deployment strategies become more efficient and cost-effective.
There is a great deal of interest in personalized, individualized, or precision interventions for disease and health-risk mitigation. This is as true of nutrition-based intervention and prevention ...strategies as it is for pharmacotherapies and pharmaceutical-oriented prevention strategies. Essentially, technological breakthroughs have enabled researchers to probe an individual's unique genetic, biochemical, physiological, behavioral, and exposure profile, allowing them to identify very specific and often nuanced factors that an individual might possess, which may make it more or less likely that he or she responds favorably to a particular intervention (e.g., nutrient supplementation) or disease prevention strategy (e.g., specific diet). However, as compelling and intuitive as personalized nutrition might be in the current era in which data-intensive biomedical characterization of individuals is possible, appropriately and objectively vetting personalized nutrition strategies is not trivial and requires novel study designs and data analytical methods. These designs and methods must consider a very integrated use of the multiple contemporary biomedical assays and technologies that motivate them, which adds to their complexity. Single-subject or N-of-1 trials can be used to assess the utility of personalized interventions and, in addition, can be crafted in such a way as to accommodate the necessarily integrated use of many emerging biomedical technologies and assays. In this review, we consider the motivation, design, and implementation of N-of-1 trials in translational nutrition research that are meant to assess the utility of personalized nutritional strategies. We provide a number of example studies, discuss
appropriate analytical methods given the complex data they generate and require, and consider how such studies could leverage integration of various biomarker assays and clinical end points. Importantly, we also consider the development of strategies and algorithms for matching nutritional needs to individual biomedical profiles and the issues surrounding them. Finally, we discuss the limitations of personalized nutrition studies, possible extensions of N-of-1 nutritional intervention studies, and areas of future research.
Circulating tumor DNA holds substantial promise as an early detection biomarker, particularly for cancers that do not have currently accepted screening methodologies, such as ovarian, pancreatic, and ...gastric cancers. Many features intrinsic to ctDNA analysis may be leveraged to enhance its use as an early cancer detection biomarker: including ctDNA fragment lengths, DNA copy number variations, and associated patient phenotypic information. Furthermore, ctDNA testing may be synergistically used with other multi-omic biomarkers to enhance early detection. For instance, assays may incorporate early detection proteins (i.e., CA-125), epigenetic markers, circulating tumor RNA, nucleosomes, exosomes, and associated immune markers. Many companies are currently competing to develop a marketable early cancer detection test that leverages ctDNA. Although some hurdles (like early stage disease assay accuracy, high implementation costs, confounding from clonal hematopoiesis, and lack of clinical utility studies) need to be addressed before integration into healthcare, ctDNA assays hold substantial potential as an early cancer screening test.
Personalized medicine, or the tailoring of health interventions to an individual's nuanced and often unique genetic, biochemical, physiological, behavioral, and/or exposure profile, is seen by many ...as a biological necessity given the great heterogeneity of pathogenic processes underlying most diseases. However, testing and ultimately proving the benefit of strategies or algorithms connecting the mechanisms of action of specific interventions to patient pathophysiological profiles (referred to here as “intervention matching schemes” (IMS)) is complex for many reasons. We argue that IMS are likely to be pervasive, if not ubiquitous, in future health care, but raise important questions about their broad deployment and the contexts within which their utility can be proven. For example, one could question the need to, the efficiency associated with, and the reliability of, strategies for comparing competing or perhaps complementary IMS. We briefly summarize some of the more salient issues surrounding the vetting of IMS in cancer contexts and argue that IMS are at the foundation of many modern clinical trials and intervention strategies, such as basket, umbrella, and adaptive trials. In addition, IMS are at the heart of proposed “rapid learning systems” in hospitals, and implicit in cell replacement strategies, such as cytotoxic T‐cell therapies targeting patient‐specific neo‐antigen profiles. We also consider the need for sensitivity to issues surrounding the deployment of IMS and comment on directions for future research.
In recent years, the development of sensor and wearable technologies have led to their increased adoption in clinical and health monitoring settings. One area that is in early, but promising, stages ...of development is the use of biosensors for therapeutic drug monitoring (TDM). Traditionally, TDM could only be performed in certified laboratories and was used in specific scenarios to optimize drug dosage based on measurement of plasma/blood drug concentrations. Although TDM has been typically pursued in settings involving medications that are challenging to manage, the basic approach is useful for characterizing drug activity. TDM is based on the idea that there is likely a clear relationship between plasma/blood drug concentration (or concentration in other matrices) and clinical efficacy. However, these relationships may vary across individuals and may be affected by genetic factors, comorbidities, lifestyle, and diet. TDM technologies will be valuable for enabling precision medicine strategies to determine the clinical efficacy of drugs in individuals, as well as optimizing personalized dosing, especially since therapeutic windows may vary inter-individually. In this mini-review, we discuss emerging TDM technologies and their applications, and factors that influence TDM including drug interactions, polypharmacy, and supplement use. We also discuss how using TDM within single subject (N-of-1) and aggregated N-of-1 clinical trial designs provides opportunities to better capture drug response and activity at the individual level. Individualized TDM solutions have the potential to help optimize treatment selection and dosing regimens so that the right drug and right dose may be matched to the right person and in the right context.
Endometriosis is an estrogen dependent, inflammatory disorder occurring in 5-10% of reproductive-aged women. Women with endometriosis have a lower body mass index (BMI) and decreased body fat ...compared to those without the disease, yet few studies have focused on the metabolic abnormalities in adipose tissue in women with endometriosis. Previously, we identified microRNAs that are differentially expressed in endometriosis and altered in the serum of women with the disease. Here we explore the effect of endometriosis on fat tissue and identified a role for endometriosis-related microRNAs in fat metabolism and a reduction in adipocyte stem cell number.
Primary adipocyte cells cultured from 20 patients with and without endometriosis were transfected with mimics and inhibitors of microRNAs 342-3p or Let 7b-5p to model the status of these microRNAs in endometriosis. RNA was extracted for gene expression analysis by qRT-PCR. PCNA expression was used as a marker of adipocyte proliferation. Endometriosis was induced experimentally in 9-week old female C57BL/6 mice and after 10 months fat tissue was harvested from both the subcutaneous (inguinal) and visceral (mesenteric) tissue. Adipose-derived mesenchymal stem cells in fat tissue were characterized in both endometriosis and non-endometriosis mice by FACS analysis.
Gene expression analysis showed that endometriosis altered the expression of Cebpa, Cebpb, Ppar-γ, leptin, adiponectin, IL-6, and HSL, which are involved in driving brown adipocyte differentiation, appetite, insulin sensitivity and fat metabolism. Each gene was regulated by an alteration in microRNA expression known to occur in endometriosis. Analysis of the stem cell content of adipose tissue in a mouse model of endometriosis demonstrated a reduced number of adipocyte stem cells.
We demonstrate that microRNAs Let-7b and miR-342-3p affected metabolic gene expression significantly in adipocytes of women with endometriosis. Similarly, there is a reduction in the adipose stem cell population in a mouse model of endometriosis. Taken together these data suggest that endometriosis alters BMI in part through an effect on adipocytes and fat metabolism.
The development of effective treatments to prevent and slow Alzheimer's disease (AD) pathogenesis is needed in order to tackle the steady increase in the global prevalence of AD. This challenge is ...complicated by the need to identify key health shifts that precede the onset of AD and cognitive decline as these represent windows of opportunity for intervening and preventing disease. Such shifts may be captured through the measurement of biomarkers that reflect the health of the individual, in particular those that reflect brain age and biological age. Brain age biomarkers provide a composite view of the health of the brain based on neuroanatomical analyses, while biological age biomarkers, which encompass the epigenetic clock, provide a measurement of the overall health state of an individual based on DNA methylation analysis. Acceleration of brain and biological ages is associated with changes in cognitive function, as well as neuropathological markers of AD. In this mini-review, we discuss brain age and biological age research in the context of cognitive decline and AD. While more research is needed, studies show that brain and biological aging trajectories are variable across individuals and that such trajectories are non-linear at older ages. Longitudinal monitoring of these biomarkers may be valuable for enabling earlier identification of divergent pathological trajectories toward AD and providing insight into points for intervention.
Populations composed of individuals descended from multiple distinct genetic lineages often feature significant differences in phenotypic frequencies. We considered hatchery production of steelhead, ...the migratory anadromous form of the salmonid species Oncorhynchus mykiss, and investigated how differences among genetic lineages and environmental variation impacted life history traits. We genotyped 23,670 steelhead returning to the four California Central Valley hatcheries over 9 years from 2011 to 2019, confidently assigning parentage to 13,576 individuals to determine age and date of spawning and rates of iteroparity and repeat spawning within each year. We found steelhead from different genetic lineages showed significant differences in adult life history traits despite inhabiting similar environments. Differences between coastal and Central Valley steelhead lineages contributed to significant differences in age at return, timing of spawning, and rates of iteroparity among programs. In addition, adaptive genomic variation associated with life history development in this species varied among hatchery programs and was associated with the age of steelhead spawners only in the coastal lineage population. Environmental variation likely contributed to variations in phenotypic patterns observed over time, as our study period spanned both a marine heatwave and a serious drought in California. Our results highlight evidence of a strong genetic component underlying known phenotypic differences in life history traits between two steelhead lineages.
Cross-sex hormone therapy (XHT) is widely used by transgender people to alter secondary sex characteristics to match their desired gender presentation. Here, we investigate the long-term effects of ...XHT on bone health using a murine model. Female mice underwent ovariectomy at either 6 or 10 wk and began weekly testosterone or vehicle injections. Dual-energy X-ray absorptiometry (DXA) was performed (20 wk) to measure bone mineral density (BMD), and microcomputed tomography was performed to compare femoral cortical and trabecular bone architecture. The 6-wk testosterone group had comparable BMD with controls by DXA but reduced bone volume fraction, trabecular number, and cortical area fraction and increased trabecular separation by microcomputed tomography. Ten-week ovariectomy/XHT maintained microarchitecture, suggesting that estrogen is critical for bone acquisition during adolescence and that late, but not early, estrogen loss can be sufficiently replaced by testosterone alone. Given these findings, we then compared effects of testosterone with effects of weekly estrogen or combined testosterone/low-dose estrogen treatment after a 6-wk ovariectomy. Estrogen treatment increased spine BMD and microarchitecture, including bone volume fraction, trabecular number, trabecular thickness, and connectivity density, and decreased trabecular separation. Combined testosterone-estrogen therapy caused similar increases in femur and spine BMD and improved architecture (increased bone volume fraction, trabecular number, trabecular thickness, and connectivity density) to estrogen therapy and were superior compared with mice treated with testosterone only. These results demonstrate estradiol is critical for bone acquisition and suggest a new cross-sex hormone therapy adding estrogens to testosterone treatments with potential future clinical implications for treating transgender youth or men with estrogen deficiency.
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