Precision medicine: Molecular mechanisms will lead future optimizations with PBM therapy (Conference Presentation)

During this decade, breakthrough conceptual shifts have commenced to emerge in the field of Alzheimer’s disease (AD) recognizing risk factors and the non-linear dynamic continuum of complex pathophysiologies amongst a wide dimensional spectrum of multi-factorial brain proteinopathies/neurodegenerative diseases. As is the case in most fields of medicine, substantial advancements in detecting, treating and preventing AD will likely evolve from the generation and implementation of a systematic precision medicine strategy. This approach will likely be based on the success found from more advanced research fields, such as oncology. Precision medicine will require integration and transfertilization across fragmented specialities of medicine and direct reintegration of Neuroscience, Neurology and Psychiatry into a continuum of medical sciences away from the silo approach. Precision medicine is biomarker-guided medicine on systems-levels that takes into account methodological advancements and discoveries of the comprehensive pathophysiological profiles of complex multi-factorial neurodegenerative diseases, such as late-onset sporadic AD. This will allow identifying and characterizing the disease processes at the asymptomatic preclinical stage, where pathophysiological and topographical abnormalities precede overt clinical symptoms by many years to decades. In this respect, the uncharted territory of the AD preclinical stage has become a major research challenge as the field postulates that early biomarker guided customized interventions may offer the best chance of therapeutic success. Clarification and practical operationalization is needed for comprehensive dissection and classification of interacting and converging disease mechanisms, description of genomic and epigenetic drivers, natural history trajectories through space and time, surrogate biomarkers and indicators of risk and progression, as well as considerations about the regulatory, ethical, political and societal consequences of early detection at asymptomatic stages. In this scenario, the integrated roles of genome sequencing, investigations of comprehensive fluid-based biomarkers and multimodal neuroimaging will be of key importance for the identification of distinct molecular mechanisms and signaling pathways in subsets of asymptomatic people at greatest risk for progression to clinical milestones due to those specific pathways. The precision medicine strategy facilitates a paradigm shift in Neuroscience and AD research and development away from the classical “one-size-fits-all” approach in drug discovery towards biomarker guided “molecularly” tailored therapy for truly effective treatment and prevention options. After the long and winding decade of failed therapy trials progress towards the holistic systems-based strategy of precision medicine may finally turn into the new age of scientific and medical success curbing the global AD epidemic.

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Recent advances in understanding the phenotypes of osteoarthritis

F1000Research ◽

10.12688/f1000research.20575.1 ◽

2019 ◽

Vol 8 ◽

pp. 2091 ◽

Cited By ~ 7

Author(s):

Ali Mobasheri ◽

Simo Saarakkala ◽

Mikko Finnilä ◽

Morten A. Karsdal ◽

Anne-Christine Bay-Jensen ◽

...

Keyword(s):

Clinical Trials ◽

Precision Medicine ◽

Biochemical Markers ◽

Molecular Mechanisms ◽

Review Article ◽

Clinical Phenotypes ◽

Recent Advances ◽

The People ◽

Molecular Phenotypes

Recent research in the field of osteoarthritis (OA) has focused on understanding the underlying molecular and clinical phenotypes of the disease. This narrative review article focuses on recent advances in our understanding of the phenotypes of OA and proposes that the disease represents a diversity of clinical phenotypes that are underpinned by a number of molecular mechanisms, which may be shared by several phenotypes and targeted more specifically for therapeutic purposes. The clinical phenotypes of OA supposedly have different underlying etiologies and pathogenic pathways and they progress at different rates. Large OA population cohorts consist of a majority of patients whose disease progresses slowly and a minority of individuals whose disease may progress faster. The ability to identify the people with relatively rapidly progressing OA can transform clinical trials and enhance their efficiency. The identification, characterization, and classification of molecular phenotypes of rapidly progressing OA, which represent patients who may benefit most from intervention, could potentially serve as the basis for precision medicine for this disabling condition. Imaging and biochemical markers (biomarkers) are important diagnostic and research tools that can assist with this challenge.

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En route to precision medicine through the integration of biological sex into pharmacogenomics

Clinical Science ◽

10.1042/cs20160379 ◽

2017 ◽

Vol 131 (4) ◽

pp. 329-342 ◽

Cited By ~ 20

Author(s):

Lea Gaignebet ◽

Georgios Kararigas

Keyword(s):

Precision Medicine ◽

Molecular Mechanisms ◽

Genetic Determinants ◽

Biological Sex ◽

Genome Wide ◽

Cardiovascular Therapy ◽

Pharmacokinetic Properties ◽

Candidate Gene Studies ◽

Pharmacogenomic Studies

Frequently, pharmacomechanisms are not fully elucidated. Therefore, drug use is linked to an elevated interindividual diversity of effects, whether therapeutic or adverse, and the role of biological sex has as yet unrecognized and underestimated consequences. A pharmacogenomic approach could contribute towards the development of an adapted therapy for each male and female patient, considering also other fundamental features, such as age and ethnicity. This would represent a crucial step towards precision medicine and could be translated into clinical routine. In the present review, we consider recent results from pharmacogenomics and the role of sex in studies that are relevant to cardiovascular therapy. We focus on genome-wide analyses, because they have obvious advantages compared with targeted single-candidate gene studies. For instance, genome-wide approaches do not necessarily depend on prior knowledge of precise molecular mechanisms of drug action. Such studies can lead to findings that can be classified into three categories: first, effects occurring in the pharmacokinetic properties of the drug, e.g. through metabolic and transporter differences; second, a pharmacodynamic or drug target-related effect; and last diverse adverse effects. We conclude that the interaction of sex with genetic determinants of drug response has barely been tested in large, unbiased, pharmacogenomic studies. We put forward the theory that, to contribute towards the realization of precision medicine, it will be necessary to incorporate sex into pharmacogenomics.

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Baseline cell proliferation rates and response to UV differ in Lymphoblastoid Cell Lines derived from healthy individuals of extreme constitution types

10.1101/2021.01.26.428133 ◽

2021 ◽

Author(s):

Sumita Chakraborty ◽

Sunanda Singhmar ◽

Dayanidhi Singh ◽

Mahua Maulik ◽

Rutuja Patil ◽

...

Keyword(s):

Cell Proliferation ◽

Precision Medicine ◽

Molecular Mechanisms ◽

Early Interventions ◽

Healthy Individuals ◽

Functional Studies ◽

Dna Damaging Agents ◽

Environmental Interactions ◽

Cellular Phenotypes ◽

Stress Variability

AbstractDifferences in human phenotypes and susceptibility to complex diseases are an outcome of genetic and environmental interactions. This is evident in diseases that progress through a common set of intermediate patho-endophenotypes. Precision medicine aims to delineate the molecular players for individualized and early interventions. Functional studies in Lymphoblastoid Cell Line (LCL) model of phenotypically well characterized healthy individuals can help deconvolute and validate these molecular mechanisms. We developed LCLs from eight healthy individuals belonging to three extreme constitution types, deep phenotyped on the basis of Ayurveda. LCLs were characterized by karyotyping and immunophenotyping. Growth characteristics and response to UV was studied in these LCLs. We observed significant differences in cell proliferation rates between the contrasting groups such that one type (Kapha) proliferates significantly slower than the other two (Vata, Pitta). In response to UV, one fast growing group (Vata) shows higher cell death but recovers its numbers due to inherent higher rates of proliferation. The baseline differences in cell proliferation are key to understanding the survival of cells in UV stress. Variability in baseline cellular phenotypes not only explains the cellular basis of different constitutions types but can also help set priors during designing an individualized therapy with DNA damaging agents. This is the first study of its kind that shows variability of intermediate patho-phenotypes amongst healthy individuals that have implications in precision medicine.

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Inching towards precision medicine for multiple myeloma with causal network models.

Journal of Clinical Oncology ◽

10.1200/jco.2019.37.15_suppl.e19526 ◽

2019 ◽

Vol 37 (15_suppl) ◽

pp. e19526-e19526

Author(s):

Jun Zhu ◽

Yu Liu ◽

Li Wang ◽

Haocheng Yu ◽

Seungyeul Yoo ◽

...

Keyword(s):

Multiple Myeloma ◽

Precision Medicine ◽

Drug Response ◽

Molecular Mechanisms ◽

Molecular Subtype ◽

Surface Protein ◽

Network Models ◽

Causal Models ◽

Data Matching ◽

Drug Response Biomarkers

e19526 Background: Multiple myeloma (MM) is the 2nd most prevalent blood cancer. For each molecular subtype of MM defined by molecular profiles, mechanisms underlying prognosis and drug response are largely unknown. Elucidating the mechanisms underlying differences in prognosis and drug response will enable a more personalized, precision medicine (PM) approach to treating patients. Methods: Big multiomics data are now widely available and contain the ingredients necessary to build causal models to uncover mechanisms of prognosis and drug response. However, data from resources like the MM Research Consortium (MMRC) dataset may contain errors (eg, sample mislabeling) that diminish modeling accuracy. We developed a probabilistic data matching method ( proMODMatcher) to correct such errors and applied it to the MMRC data. We identified labeling errors in 10 patients, including swaps in RNA and CNV profiles. Given the corrected MMRC data, we characterized recurrent genomic aberrations in MM. We found > 8000 genes significantly associated (FDR < 0.01) with CNVs spanning the gene locations. To distinguish expression correlations driven by causal biological relationships from those driven by coincident CNV influence, we constructed a causal MM network based on the MMRC dataset. Results: Overlaps among multiomic prognostic or drug response biomarkers are sparse. To identify common mechanisms of different biomarkers, we projected them onto our MM network to define the causal context in which they occur. Prognostic biomarkers were enriched in subnetworks associated with mitotic regulation and lipid metabolism, and predicted by our network to be regulated by ZWINT, BUB1B, DTL, TPX2 and NOP16. Proteasome inhibitor and immunomodulating drug responses were mediated by amino acid biosynthesis and cell surface protein complex subnetworks, respectively, with MTHFD2 and TMC8 inferred as the master regulators of these subnetworks, respectively. Regulators include genes (eg, BUB1B and MTHFD2) known to associate with tumor growth and drug response and novel therapeutic control points. Conclusions: Causal models can elucidate the molecular mechanisms underlying prognosis and drug response, enabling the design of more personalized MM treatments.

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Personalized Medicine: The Future of Health Care

The Indonesian Biomedical Journal ◽

10.18585/inabj.v8i3.271 ◽

2016 ◽

Vol 8 (3) ◽

pp. 127

Author(s):

Anna Meiliana ◽

Nurrani Mustika Dewi ◽

Andi Wijaya

Keyword(s):

Health Care ◽

Personalized Medicine ◽

Precision Medicine ◽

Molecular Mechanisms ◽

Care Needs ◽

Medical Treatments ◽

Treatment And Prevention ◽

Human Illness ◽

Make Health Care ◽

Innovation Approach

BACKGROUND: Most medical treatments have been designed for the “average patients”. As a result of this “one-size-fits-all-approach”, treatments can be very successful for some patients but not for others. The issue is shifting by the new innovation approach in diseases treatment and prevention, precision medicine, which takes into account individual differences in people’s genes, environments, and lifestyles. This review was aimed to describe a new approach of healthcare performance strategy based on individual genetic variants.CONTENT: Researchers have discovered hundreds of genes that harbor variations contributing to human illness, identified genetic variability in patients’ responses to different of treatments, and from there begun to target the genes as molecular causes of diseases. In addition, scientists are developing and using diagnostic tests based on genetics or other molecular mechanisms to better predict patients’ responses to targeted therapy.SUMMARY: Personalized medicine seeks to use advances in knowledge about genetic factors and biological mechanisms of disease coupled with unique considerations of an individual’s patient care needs to make health care more safe and effective. As a result of these contributions to improvement in the quality of care, personalized medicine represents a key strategy of healthcare reform.KEYWORDS: precision medicine, genomic, proteomic, metabolomic

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Precision medicine for heart failure based on molecular mechanisms: The Research Achievement Award Lecture

Journal of Molecular and Cellular Cardiology ◽

10.1016/j.yjmcc.2020.11.010 ◽

2021 ◽

Vol 152 ◽

pp. 29-39

Author(s):

Seitaro Nomura ◽

Issei Komuro

Keyword(s):

Heart Failure ◽

Precision Medicine ◽

Molecular Mechanisms ◽

Achievement Award ◽

Research Achievement

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Towards a personalized risk assessment for exposure of humans to toxic substances

Cadernos Saúde Coletiva ◽

10.1590/1414-462x201600020135 ◽

2016 ◽

Vol 24 (2) ◽

pp. 262-273

Author(s):

Thaís de Almeida Pedrete ◽

Caroline de Lima Mota ◽

Eline Simões Gonçalves ◽

Josino Costa Moreira

Keyword(s):

Risk Assessment ◽

Precision Medicine ◽

Molecular Mechanisms ◽

Toxic Substances ◽

Predictive Toxicology ◽

President Obama ◽

Specific Chemical ◽

The Usa ◽

Personalized Risk Assessment ◽

Personalized Risk

Abstract Great response variability caused by genetic and/or environmental factors has been observed among organisms exposed to hazardous chemicals. This subject has been a topic of intense discussion in the USA since President Obama announced support for an “era of precision medicine”, which consists in the inclusion of genetic data of patients in the treatment design, imposing a new approach to risk assessment. Personalized evaluation must consider the phenotypic factors of an individual. Among the markers that have been developed to evaluate any alteration in the structure or function of organisms, biomarkers of susceptibility are of great importance because they indicate the natural characteristics of a given organism which make it more sensitive to a specific adverse effect or disease, or more responsive to exposure to a specific chemical/drug. The ‘-omics’ technologies provide an insight into the relationship between chemical effects and molecular mechanisms of action. These technologies are the pillars for a personalized toxicology and precision medicine. Predictive toxicology requires a more comprehensive knowledge on specific individual factors or susceptibilities predisposing to diseases, enabling personalized risk assessment and adequate medical treatment.

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Precision Medicine for Continuing Phenotype Expansion of Human Genetic Diseases

BioMed Research International ◽

10.1155/2015/745043 ◽

2015 ◽

Vol 2015 ◽

pp. 1-4 ◽

Cited By ~ 5

Author(s):

Hui Yu ◽

Victor Wei Zhang

Keyword(s):

Patient Care ◽

Precision Medicine ◽

Molecular Mechanisms ◽

Current Knowledge ◽

Genetic Diseases ◽

Diagnostic Purpose ◽

Disease Spectrum ◽

Phenotypic Spectrum ◽

Core Elements ◽

Common Understanding

Determining the exact genetic causes for a patient and providing definite molecular diagnoses are core elements of precision medicine. Individualized patient care is often limited by our current knowledge of disease etiologies and commonly used phenotypic-based diagnostic approach. The broad and incompletely understood phenotypic spectrum of a disease and various underlying genetic heterogeneity also present extra challenges to our clinical practice. With the rapid adaptation of new sequence technology in clinical setting for diagnostic purpose, phenotypic expansions of disease spectrum are becoming increasingly common. Understanding the underlying molecular mechanisms will help us to integrate genomic information into the workup of individualized patient care and make better clinical decisions.

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Precision Medicine in Childhood Asthma

10.32545/encyclopedia202005.0007.v3 ◽

2020 ◽

Author(s):

Javier Perez-Garcia ◽

Esther Herrera-Luis ◽

Fabian Lorenzo-Diaz ◽

Mario A. Gonzalez Carracedo ◽

Olaia Sardon Prado ◽

...

Keyword(s):

Precision Medicine ◽

Treatment Response ◽

Childhood Asthma ◽

Molecular Mechanisms ◽

Inhaled Corticosteroids ◽

Pediatric Population ◽

Beta Agonists ◽

High Prevalence ◽

Appropriate Therapy ◽

Definition Of

Asthma is a complex and multifactorial respiratory disease with a high prevalence in the pediatric population. Variation in treatment response to asthma therapies has been described among patients, and difficult-to-treat asthma carries both high healthcare and socioeconomic burden to the patients and society. Omic studies can be used to discover the molecular mechanisms underlying asthma susceptibility and treatment response, contributing to a better knowledge and definition of asthma pathogenesis and therefore, to the development of precision medicine. This entry aims to summarize the recent findings of omic studies of treatment response in childhood asthma. Between 2018-2019 a total of 13 omic studies has been performed involving genomics, epigenomics, transcriptomics, metabolomics, and the microbiome. These have been focused on the response to three common asthma medications: short-acting beta agonists, inhaled corticosteroids, and leukotriene receptor antagonists. Novel associations of different biomarkers with asthma treatment response have been described. However, stronger evidence and more consistent results are required to implement these molecular biomarkers into clinical practice by establishing the most appropriate therapy for each patient.

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