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Latapiat V, Saez M, Pedroso I, Martin AJM. Unraveling patient heterogeneity in complex diseases through individualized co-expression networks: a perspective. Front Genet 2023; 14:1209416. [PMID: 37636264 PMCID: PMC10449456 DOI: 10.3389/fgene.2023.1209416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 07/24/2023] [Indexed: 08/29/2023] Open
Abstract
This perspective highlights the potential of individualized networks as a novel strategy for studying complex diseases through patient stratification, enabling advancements in precision medicine. We emphasize the impact of interpatient heterogeneity resulting from genetic and environmental factors and discuss how individualized networks improve our ability to develop treatments and enhance diagnostics. Integrating system biology, combining multimodal information such as genomic and clinical data has reached a tipping point, allowing the inference of biological networks at a single-individual resolution. This approach generates a specific biological network per sample, representing the individual from which the sample originated. The availability of individualized networks enables applications in personalized medicine, such as identifying malfunctions and selecting tailored treatments. In essence, reliable, individualized networks can expedite research progress in understanding drug response variability by modeling heterogeneity among individuals and enabling the personalized selection of pharmacological targets for treatment. Therefore, developing diverse and cost-effective approaches for generating these networks is crucial for widespread application in clinical services.
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Affiliation(s)
- Verónica Latapiat
- Programa de Doctorado en Genómica Integrativa, Vicerrectoría de Investigación, Universidad Mayor, Santiago, Chile
- Vicerrectoría de Investigación, Universidad Mayor, Santiago, Chile
- Laboratorio de Redes Biológicas, Centro Científico y Tecnológico de Excelencia Ciencia & Vida, Fundación Ciencia & Vida, Santiago, Chile
| | - Mauricio Saez
- Centro de Oncología de Precisión, Facultad de Medicina y Ciencias de la Salud, Universidad Mayor, Santiago, Chile
- Laboratorio de Investigación en Salud de Precisión, Departamento de Procesos Diagnósticos y Evaluación, Facultad de Ciencias de la Salud, Universidad Católica de Temuco, Temuco, Chile
| | - Inti Pedroso
- Vicerrectoría de Investigación, Universidad Mayor, Santiago, Chile
| | - Alberto J. M. Martin
- Laboratorio de Redes Biológicas, Centro Científico y Tecnológico de Excelencia Ciencia & Vida, Fundación Ciencia & Vida, Santiago, Chile
- Escuela de Ingeniería, Facultad de Ingeniería, Arquitectura y Diseño, Universidad San Sebastián, Santiago, Chile
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Vargas E, Nandhakumar P, Ding S, Saha T, Wang J. Insulin detection in diabetes mellitus: challenges and new prospects. Nat Rev Endocrinol 2023:10.1038/s41574-023-00842-3. [PMID: 37217746 DOI: 10.1038/s41574-023-00842-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/19/2023] [Indexed: 05/24/2023]
Abstract
Tremendous progress has been made towards achieving tight glycaemic control in individuals with diabetes mellitus through the use of frequent or continuous glucose measurements. However, in patients who require insulin, accurate dosing must consider multiple factors that affect insulin sensitivity and modulate insulin bolus needs. Accordingly, an urgent need exists for frequent and real-time insulin measurements to closely track the dynamic blood concentration of insulin during insulin therapy and guide optimal insulin dosing. Nevertheless, traditional centralized insulin testing cannot offer timely measurements, which are essential to achieving this goal. This Perspective discusses the advances and challenges in moving insulin assays from traditional laboratory-based assays to frequent and continuous measurements in decentralized (point-of-care and home) settings. Technologies that hold promise for insulin testing using disposable test strips, mobile systems and wearable real-time insulin-sensing devices are discussed. We also consider future prospects for continuous insulin monitoring and for fully integrated multisensor-guided closed-loop artificial pancreas systems.
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Affiliation(s)
- Eva Vargas
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Ponnusamy Nandhakumar
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Shichao Ding
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Tamoghna Saha
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA
| | - Joseph Wang
- Department of Nanoengineering, University of California San Diego, La Jolla, CA, USA.
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Hu T, Yang F, He K, Ying J, Cui H. Association of mental health with the risk of coronary artery disease in patients with diabetes: A mendelian randomization study. Nutr Metab Cardiovasc Dis 2022; 32:703-709. [PMID: 35144858 DOI: 10.1016/j.numecd.2022.01.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/30/2021] [Revised: 12/28/2021] [Accepted: 01/04/2022] [Indexed: 10/19/2022]
Abstract
BACKGROUND AND AIMS Observational studies have shown an association between mental health and coronary artery disease (CAD) in patients with diabetes. Nevertheless, whether these associations are causal is still unknown. In this two-sample Mendelian randomization (MR) study, we aimed to assess the causality between mental health and CAD in patients with diabetes. METHODS AND RESULTS Single-nucleotide polymorphisms (SNPs) associated with: depression (807,553 individuals), anxiety (83,556 individuals) and neuroticism (329,821 individuals) were identified from the largest genome-wide association studies (GWAS). Summary-level data for CAD were extracted from the recently published GWAS of 15,666 diabetic patients (3968 CAD cases and 11,696 controls). The inverse-variance weighted (IVW) method was used for the main analysis. Sensitivity analyses included weighted median, maximum likelihood, and the MR-Egger method. Genetic liability to depression was significantly associated with a higher risk of CAD in patients with diabetes (odds ratio [OR], 1.286; 95%CI,1.018-1.621;p = 0.035). For anxiety and neuroticism, no causal association with CAD in patients with diabetes was observed. Consistent results were obtained in most sensitivity analyses. CONCLUSIONS This MR study provides genetic evidence that depression is a potential risk factor for CAD in patients with diabetes. However, anxiety and neuroticism were not causally associated with CAD in patients with diabetes. Mental health treatments should be enhanced to prevent CAD in patients with diabetes.
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Affiliation(s)
- Teng Hu
- School of Medicine, Ningbo University, Ningbo, Zhejiang, 315211, China; Cardiology Center, Ningbo First Hospital, Ningbo, Zhejiang, 315010, China
| | - Fangkun Yang
- Cardiology Center, Ningbo First Hospital, Ningbo, Zhejiang, 315010, China; School of Medicine, Zhejiang University, Hangzhou, 310016, China
| | - Kewan He
- School of Medicine, Ningbo University, Ningbo, Zhejiang, 315211, China; Cardiology Center, Ningbo First Hospital, Ningbo, Zhejiang, 315010, China
| | - Jiajun Ying
- Cardiology Center, Ningbo First Hospital, Ningbo, Zhejiang, 315010, China; School of Medicine, Zhejiang University, Hangzhou, 310016, China
| | - Hanbin Cui
- School of Medicine, Ningbo University, Ningbo, Zhejiang, 315211, China; Cardiology Center, Ningbo First Hospital, Ningbo, Zhejiang, 315010, China.
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Chandler PD, Clark CR, Zhou G, Noel NL, Achilike C, Mendez L, Ramirez AH, Loperena-Cortes R, Mayo K, Cohn E, Ohno-Machado L, Boerwinkle E, Cicek M, Qian J, Schully S, Ratsimbazafy F, Mockrin S, Gebo K, Dedier JJ, Murphy SN, Smoller JW, Karlson EW. Hypertension prevalence in the All of Us Research Program among groups traditionally underrepresented in medical research. Sci Rep 2021; 11:12849. [PMID: 34158555 PMCID: PMC8219813 DOI: 10.1038/s41598-021-92143-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Accepted: 06/04/2021] [Indexed: 11/18/2022] Open
Abstract
The All of Us Research Program was designed to enable broad-based precision medicine research in a cohort of unprecedented scale and diversity. Hypertension (HTN) is a major public health concern. The validity of HTN data and definition of hypertension cases in the All of Us (AoU) Research Program for use in rule-based algorithms is unknown. In this cross-sectional, population-based study, we compare HTN prevalence in the AoU Research Program to HTN prevalence in the 2015-2016 National Health and Nutrition Examination Survey (NHANES). We used AoU baseline data from patient (age ≥ 18) measurements (PM), surveys, and electronic health record (EHR) blood pressure measurements. We retrospectively examined the prevalence of HTN in the EHR cohort using Systemized Nomenclature of Medicine (SNOMED) codes and blood pressure medications recorded in the EHR. We defined HTN as the participant having at least 2 HTN diagnosis/billing codes on separate dates in the EHR data AND at least one HTN medication. We calculated an age-standardized HTN prevalence according to the age distribution of the U.S. Census, using 3 groups (18-39, 40-59, and ≥ 60). Among the 185,770 participants enrolled in the AoU Cohort (mean age at enrollment = 51.2 years) available in a Researcher Workbench as of October 2019, EHR data was available for at least one SNOMED code from 112,805 participants, medications for 104,230 participants, and 103,490 participants had both medication and SNOMED data. The total number of persons with SNOMED codes on at least two distinct dates and at least one antihypertensive medication was 33,310 for a crude prevalence of HTN of 32.2%. AoU age-adjusted HTN prevalence was 27.9% using 3 groups compared to 29.6% in NHANES. The AoU cohort is a growing source of diverse longitudinal data to study hypertension nationwide and develop precision rule-based algorithms for use in hypertension treatment and prevention research. The prevalence of hypertension in this cohort is similar to that in prior population-based surveys.
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Affiliation(s)
- Paulette D Chandler
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA.
| | - Cheryl R Clark
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Guohai Zhou
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
| | - Nyia L Noel
- Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
| | - Confidence Achilike
- Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
| | - Lizette Mendez
- Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
| | | | | | - Kelsey Mayo
- Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | - Eric Boerwinkle
- University of Texas Health Science Center School of Public Health, Houston, TX, USA
| | | | - Jun Qian
- Vanderbilt University Medical Center, Nashville, TN, USA
| | | | | | | | - Kelly Gebo
- Johns Hopkins University, Baltimore, MD, USA
| | - Julien J Dedier
- Boston Medical Center, Boston University School of Medicine, Boston, MA, USA
| | - Shawn N Murphy
- Research Information Science and Computing, Mass General Brigham, Boston, MA, USA
| | - Jordan W Smoller
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Elizabeth W Karlson
- Brigham and Women's Hospital, Harvard Medical School, Boston, MA, 02115, USA
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Abstract
BACKGROUND Systems biology is a rapidly advancing field of science that allows us to look into disease mechanisms, patient diagnosis and stratification, and drug development in a completely new light. It is based on the utilization of unbiased computational systems free of the traditional experimental approaches based on personal choices of what is important and what select experiments should be performed to obtain the expected results. METHODS Systems biology can be applied to inflammatory bowel disease (IBD) by learning basic concepts of omes and omics and how omics-derived "big data" can be integrated to discover the biological networks underlying highly complex diseases like IBD. Once these biological networks (interactomes) are identified, then the molecules controlling the disease network can be singled out and specific blockers developed. RESULTS The field of systems biology in IBD is just emerging, and there is still limited information on how to best utilize its power to advance our understanding of Crohn disease and ulcerative colitis to develop novel therapeutic strategies. Few centers have embraced systems biology in IBD, but the creation of international consortia and large biobanks will make biosamples available to basic and clinical IBD investigators for further research studies. CONCLUSIONS The implementation of systems biology is indispensable and unavoidable, and the patient and medical communities will both benefit immensely from what it will offer in the near future.
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Affiliation(s)
- Claudio Fiocchi
- Department of Inflammation & Immunity, Lerner Research Institute, Cleveland Clinic, Cleveland, Ohio, USA.,Department of Gastroenterology, Hepatology and Nutrition, Digestive Disease and Surgery Institute, Cleveland Clinic, Cleveland, Ohio, USA
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Denyer AL, Catchpole B, Davison LJ. Genetics of canine diabetes mellitus part 2: Current understanding and future directions. Vet J 2021; 270:105612. [PMID: 33641811 DOI: 10.1016/j.tvjl.2021.105612] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2020] [Revised: 01/05/2021] [Accepted: 01/12/2021] [Indexed: 02/08/2023]
Abstract
Part 1 of this 2-part review outlined the importance of disease classification in diabetes genetic studies, as well as the ways in which genetic variants may contribute to risk of a complex disease within an individual, or within a particular group of individuals. Part 2, presented here, describes in more detail our current understanding of the genetics of canine diabetes mellitus compared to our knowledge of the human disease. Ongoing work to improve our knowledge, using new technologies, is also introduced.
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Affiliation(s)
- Alice L Denyer
- Department of Pathology and Pathogen Biology, Royal Veterinary College, Hatfield, UK
| | - Brian Catchpole
- Department of Pathology and Pathogen Biology, Royal Veterinary College, Hatfield, UK
| | - Lucy J Davison
- Department of Clinical Sciences and Services, Royal Veterinary College, Hatfield, UK; Wellcome Centre for Human Genetics, University of Oxford, Oxford, UK.
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Firneisz G, Rosta K, Rigó J, Nádasdi Á, Harreiter J, Kautzky-Willer A, Somogyi A. Identification and Potential Clinical Utility of the MTNR1B rs10830963 Core Gene Variant Associated to Endophenotypes in Gestational Diabetes Mellitus. Front Genet 2020; 11:332. [PMID: 32373162 PMCID: PMC7186410 DOI: 10.3389/fgene.2020.00332] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2019] [Accepted: 03/20/2020] [Indexed: 01/28/2023] Open
Affiliation(s)
- Gábor Firneisz
- 2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary
- MTA-SE Molecular Medicine Research Group, Hungarian Academy of Sciences - Semmelweis University, Budapest, Hungary
| | - Klara Rosta
- Department of Obstetrics and Gynecology, Medical University of Vienna, Vienna, Austria
- 1st Department of Obstetrics and Gynecology, Semmelweis University, Budapest, Hungary
| | - János Rigó
- 1st Department of Obstetrics and Gynecology, Semmelweis University, Budapest, Hungary
| | - Ákos Nádasdi
- 2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary
| | - Jürgen Harreiter
- Gender Medicine Unit, Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Alexandra Kautzky-Willer
- Gender Medicine Unit, Division of Endocrinology and Metabolism, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria
| | - Anikó Somogyi
- 2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary
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