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Shakiba M, Yasaei M, Saneifard H, Mosallanejad A, Alaei MR, Kobarfard F, Esfahanizadeh M, Anousheh N. Expanded inherited metabolic diseases screening by tandem mass spectrophotometry: The first report from Iran. Mol Genet Metab Rep 2024; 40:101103. [PMID: 39006123 PMCID: PMC11245937 DOI: 10.1016/j.ymgmr.2024.101103] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/17/2024] [Revised: 05/30/2024] [Accepted: 06/04/2024] [Indexed: 07/16/2024] Open
Abstract
Inherited metabolic diseases (IMD) are a group of rare genetic disorders that can present with a variety of symptoms. Since these disorders are hard to treat once the symptoms occur, neonatal screening may be a logical strategy. Here we evaluate the first results of national expanded IMD screening in Iran. A total of 46 IMDs were screened in this national program. Between April 2018 and March 2022, all infants who underwent national IMD screening at Shahid Beheshti University of Medical Sciences were included in this study. History and Physical examinations of infants, screening results, recall rate, response rate, and prevalence of IMDs were evaluated. A total of 125,819 infants were screened during this period. The recall rate of the test was 0.81%. 124 cases were diagnosed with a definite IMD and the raw overall prevalence of IMDs was estimated to be 1:1015. Aminoacidopathies were the most commonly detected disorders and Hyperphenylalaninemia/PKU was the most prevalent disorder among all groups. Since IMDs vary from region even in a single country, screening for IMDs is crucial in societies with a high rate of consanguineous marriages. More studies are essential for figuring out the most efficient combination of diseases to be screened based on countries' facilities.
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Affiliation(s)
- Marjan Shakiba
- Department of Pediatric Endocrinology & Metabolism, Mofid Children's Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mehrdad Yasaei
- Department of Pediatric Endocrinology & Metabolism, Mofid Children's Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Hedyeh Saneifard
- Department of Pediatric Endocrinology & Metabolism, Mofid Children's Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Asieh Mosallanejad
- Department of Pediatric Endocrinology & Metabolism, Mofid Children's Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Mohammad Reza Alaei
- Department of Pediatric Endocrinology & Metabolism, Mofid Children's Hospital, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Farzad Kobarfard
- Department of Medicinal Chemistry, School of Pharmacy, Phytochemistry Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Marjan Esfahanizadeh
- Central Research Laboratory, Phytochemistry Research Center, Shahid Beheshti University of Medical Sciences, Tehran, Iran
| | - Narges Anousheh
- School of Medicine, Shahid Beheshti University of Medical Sciences, Tehran, Iran
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Liu J. Editorial: Emerging roles of the gut microbiota in the pathogenesis of metabolic disorders, volume II. Front Endocrinol (Lausanne) 2024; 15:1415705. [PMID: 38859904 PMCID: PMC11163127 DOI: 10.3389/fendo.2024.1415705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2024] [Accepted: 05/16/2024] [Indexed: 06/12/2024] Open
Affiliation(s)
- Jieying Liu
- Center for Biomarker Discovery and Validation, National Infrastructures for Translational Medicine (PUMCH), Institute of Clinical Medicine, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China
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Yu J, Ren J, Ren Y, Wu Y, Zeng Y, Zhang Q, Xiao X. Using metabolomics and proteomics to identify the potential urine biomarkers for prediction and diagnosis of gestational diabetes. EBioMedicine 2024; 101:105008. [PMID: 38368766 PMCID: PMC10882130 DOI: 10.1016/j.ebiom.2024.105008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 01/22/2024] [Accepted: 01/30/2024] [Indexed: 02/20/2024] Open
Abstract
Gestational diabetes mellitus (GDM) is one of the most common metabolic complications during pregnancy, threatening both maternal and fetal health. Prediction and diagnosis of GDM is not unified. Finding effective biomarkers for GDM is particularly important for achieving early prediction, accurate diagnosis and timely intervention. Urine, due to its accessibility in large quantities, noninvasive collection and easy preparation, has become a good sample for biomarker identification. In recent years, a number of studies using metabolomics and proteomics approaches have identified differential expressed urine metabolites and proteins in GDM patients. In this review, we summarized these potential urine biomarkers for GDM prediction and diagnosis and elucidated their role in development of GDM.
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Affiliation(s)
- Jie Yu
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Jing Ren
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yaolin Ren
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yifan Wu
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Yuan Zeng
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China
| | - Qian Zhang
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China.
| | - Xinhua Xiao
- Key Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, 100730, China.
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Luo H, Wang J, Chen J, Yi H, Yang X, Peng Y, Ni L, Yang YQ, Zhang XM, Huang H. Prevalence of inherited metabolic disorders among newborns in Zhuzhou, a southern city in China. Front Genet 2024; 15:1197151. [PMID: 38380423 PMCID: PMC10877023 DOI: 10.3389/fgene.2024.1197151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Accepted: 01/19/2024] [Indexed: 02/22/2024] Open
Abstract
Background and aims: Defective enzymes, cofactors, or transporters of metabolic pathways cause inherited metabolic disorders (IMDs), a group of genetic disorders. Several IMDs have serious consequences for the affected neonates. Newborn screening for IMDs is conducted by measuring specific metabolites between 3 and 7 days of life. Herein, we analyzed the incidence, spectrum, and genetic characteristics of IMDs in newborns in the Zhuzhou area. Methods: Tandem mass spectrometry was conducted on 90,829 newborns who were admitted to the Women and Children Healthcare Hospital of Zhuzhou and requested for screening for IMDs. These newborns were subsequently subjected to next-generation sequencing and further validated using Sanger sequencing. Results: 30 IMDs cases were found in 90,829 cases of newborns screened for IMDs, and the overall incidence was 1/3,027. The incidence of amino acid, organic acid, fatty acid oxidation and urea cycle disorders were 1/8,257, 1/18,165, 1/7,569, and 1/45,414, respectively. Additionally, 9 cases of maternal IMDs were found in our study, and unreported gene mutations of 3 cases IMDs were identified. Conclusion: Our data indicated that IMDs are never uncommon in zhuzhou, meanwhile, we also found that primary carnitine deficiency was the only disorder of fatty acid oxidation in Zhuzhou, and the incidence (1/7,569) was higher than the national level, organic acid metabolic diseases are mostly inherited. Therefore, our study has clarified the disease spectrum and genetic backgrounds, contributing to the treatment and prenatal genetic counseling of these disorders in this region.
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Affiliation(s)
- Hunjin Luo
- Women and Children Healthcare Hospital of Zhuzhou, Zhuzhou, Hunan, China
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Abdulridha JS, Mashkani B, Alaei A, Boskabadi M, Varasteh A, Keyfi F. Determination of Normal Range of Acylcarnitine in Neonatal Dried Blood Spots using LC-MS/MS. Rep Biochem Mol Biol 2024; 12:522-529. [PMID: 39086584 PMCID: PMC11288244 DOI: 10.61186/rbmb.12.4.522] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Accepted: 02/20/2022] [Indexed: 08/02/2024]
Abstract
Background Acylcarnitine is one of the crucial markers of fatty acid metabolism, and examination of their level in infants can reveal several Inherited Metabolic Disorders (IDM) or Inborn errors of Metabolism (IEM). Because of the great importance of hereditary, metabolic, and other inherited disorders early diagnosis before the appearance of clinical symptoms, this study was carried out to establish a reference range for carnitine analytes and to identify acylcarnitine profiles in normal weight neonatal dried blood spots (DBS) specimens. Methods By using liquid chromatography tandem mass spectrometry (LC-MS/MS) for neonatal screening and eventually the examination and analysis of LC-MS/MS results, 34 acylcarnitine derivatives were identified. Results The normal range for acylcarnitine analytes with carbon numbers ranging from zero to 18, both main and the branched ones, were ultimately measured. Afterward, they were compared with the results of some other diagnostic laboratories to be verified. Conclusions This study differed from the other findings, which could be due to diversity in population and work methods. However, the reference range of most acylcarnitine derivatives in Tehran closely aligned with this study's findings.
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Affiliation(s)
| | - Baratali Mashkani
- Department of Clinical Biochemistry, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Amin Alaei
- Department of Medical Laboratory Science, Varastegan Institute for Medical Sciences, Mashhad, Iran.
- Division of Metabolic Disorder, Pardis Clinical and Genetic Laboratory, Mashhad, Iran.
- Research Committee, Department of Medical Laboratory Science, Varastegan Institute for Medical Sciences, Mashhad, Iran.
| | - Mostafa Boskabadi
- School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Abdolreza Varasteh
- Department of Medical Laboratory Science, Varastegan Institute for Medical Sciences, Mashhad, Iran.
- Division of Metabolic Disorder, Pardis Clinical and Genetic Laboratory, Mashhad, Iran.
| | - Fatemeh Keyfi
- Department of Medical Laboratory Science, Varastegan Institute for Medical Sciences, Mashhad, Iran.
- Division of Metabolic Disorder, Pardis Clinical and Genetic Laboratory, Mashhad, Iran.
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Piombarolo A, Ialongo C, Bizzarri M, Angeloni A. Systems Biology and Inborn Error of Metabolism: Analytical Strategy in Investigating Different Biochemical/Genetic Parameters. Methods Mol Biol 2024; 2745:191-210. [PMID: 38060187 DOI: 10.1007/978-1-0716-3577-3_12] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/08/2023]
Abstract
Inborn errors of metabolism (IEM) are a group of about 500 rare genetic diseases with large diversity and complexity due to number of metabolic pathways involved in. Establishing a correct diagnosis and identifying the specific clinical phenotype is consequently a difficult task. However, an inclusive diagnosis able in capturing the different clinical phenotypes is mandatory for successful treatment. However, in contrast with Garrod's basic assumption "one-gene one-disease," no "simple" correlation between genotype-phenotype can be vindicated in IEMs. An illustrative example of IEM is Phenylketonuria (PKU), an autosomal recessive inborn error of L-phenylalanine (Phe) metabolism, ascribed to variants of the phenylalanine hydroxylase (PAH) gene encoding for the enzyme complex phenylalanine-hydroxylase. Blood values of Phe allow classifying PKU into different clinical phenotypes, albeit the participation of other genetic/biochemical pathways in the pathogenetic mechanisms remains elusive. Indeed, it has been shown that the most serious complications, such as cognitive impairment, are not only related to the gene dysfunction but also to the patient's background and the participation of several nongenetic factors.Therefore, a Systems Biology-based strategy is required in addressing IEM complexity, and in identifying the interplay between different pathways in shaping the clinical phenotype. Such an approach should entail the concerted investigation of genomic, transcriptomics, proteomics, metabolomics profiles altogether with phenylalanine and amino acids metabolism. Noticeably, this "omic" perspective could be instrumental in planning personalized treatment, tailored accordingly to the disease profile and prognosis.
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Affiliation(s)
- Aurora Piombarolo
- Department of Experimental Medicine, Sapienza University, Rome, Italy
| | - Cristiano Ialongo
- Department of Experimental Medicine, Sapienza University, Rome, Italy
| | - Mariano Bizzarri
- Department of Experimental Medicine, Sapienza University, Rome, Italy
| | - Antonio Angeloni
- Department of Experimental Medicine, Sapienza University, Rome, Italy.
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Singh S, Sarma DK, Verma V, Nagpal R, Kumar M. Unveiling the future of metabolic medicine: omics technologies driving personalized solutions for precision treatment of metabolic disorders. Biochem Biophys Res Commun 2023; 682:1-20. [PMID: 37788525 DOI: 10.1016/j.bbrc.2023.09.064] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2023] [Revised: 09/13/2023] [Accepted: 09/21/2023] [Indexed: 10/05/2023]
Abstract
Metabolic disorders are increasingly prevalent worldwide, leading to high rates of morbidity and mortality. The variety of metabolic illnesses can be addressed through personalized medicine. The goal of personalized medicine is to give doctors the ability to anticipate the best course of treatment for patients with metabolic problems. By analyzing a patient's metabolomic, proteomic, genetic profile, and clinical data, physicians can identify relevant diagnostic, and predictive biomarkers and develop treatment plans and therapy for acute and chronic metabolic diseases. To achieve this goal, real-time modeling of clinical data and multiple omics is essential to pinpoint underlying biological mechanisms, risk factors, and possibly useful data to promote early diagnosis and prevention of complex diseases. Incorporating cutting-edge technologies like artificial intelligence and machine learning is crucial for consolidating diverse forms of data, examining multiple variables, establishing databases of clinical indicators to aid decision-making, and formulating ethical protocols to address concerns. This review article aims to explore the potential of personalized medicine utilizing omics approaches for the treatment of metabolic disorders. It focuses on the recent advancements in genomics, epigenomics, proteomics, metabolomics, and nutrigenomics, emphasizing their role in revolutionizing personalized medicine.
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Affiliation(s)
- Samradhi Singh
- ICMR- National Institute for Research in Environmental Health, Bhopal Bypass Road, Bhouri, Bhopal, 462030, Madhya Pradesh, India
| | - Devojit Kumar Sarma
- ICMR- National Institute for Research in Environmental Health, Bhopal Bypass Road, Bhouri, Bhopal, 462030, Madhya Pradesh, India
| | - Vinod Verma
- Stem Cell Research Centre, Department of Hematology, Sanjay Gandhi Post-Graduate Institute of Medical Sciences, Lucknow, 226014, Uttar Pradesh, India
| | - Ravinder Nagpal
- Department of Nutrition and Integrative Physiology, College of Health and Human Sciences, Florida State University, Tallahassee, FL, 32306, USA
| | - Manoj Kumar
- ICMR- National Institute for Research in Environmental Health, Bhopal Bypass Road, Bhouri, Bhopal, 462030, Madhya Pradesh, India.
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Birhanu AG. Mass spectrometry-based proteomics as an emerging tool in clinical laboratories. Clin Proteomics 2023; 20:32. [PMID: 37633929 PMCID: PMC10464495 DOI: 10.1186/s12014-023-09424-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Accepted: 08/03/2023] [Indexed: 08/28/2023] Open
Abstract
Mass spectrometry (MS)-based proteomics have been increasingly implemented in various disciplines of laboratory medicine to identify and quantify biomolecules in a variety of biological specimens. MS-based proteomics is continuously expanding and widely applied in biomarker discovery for early detection, prognosis and markers for treatment response prediction and monitoring. Furthermore, making these advanced tests more accessible and affordable will have the greatest healthcare benefit.This review article highlights the new paradigms MS-based clinical proteomics has created in microbiology laboratories, cancer research and diagnosis of metabolic disorders. The technique is preferred over conventional methods in disease detection and therapy monitoring for its combined advantages in multiplexing capacity, remarkable analytical specificity and sensitivity and low turnaround time.Despite the achievements in the development and adoption of a number of MS-based clinical proteomics practices, more are expected to undergo transition from bench to bedside in the near future. The review provides insights from early trials and recent progresses (mainly covering literature from the NCBI database) in the application of proteomics in clinical laboratories.
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Martins AD, Ribeiro JC, Ferreira R, Alves MG, Oliveira PF. Understanding the age-related alterations in the testis-specific proteome. Expert Rev Proteomics 2023; 20:331-343. [PMID: 37878493 DOI: 10.1080/14789450.2023.2274857] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 10/12/2023] [Indexed: 10/27/2023]
Abstract
INTRODUCTION Fertility rates in developing countries have declined over the past decades, and the trend of delayed fatherhood is rising as societies develop. The reasons behind the decline in male fertility with advancing age remain mysterious, making it a compelling and crucial area for further research. However, the limited number of studies dedicated to unraveling this enigma poses a challenge. Thus, our objective is to illuminate some of the upregulated and downregulated mechanisms in the male testis during the aging process. AREAS COVERED Herein, we present a critical overview of the studies addressing the alterations of testicular proteome through the aging process, starting from sexually matured young males to end-of-life-expectancy aged males. The comparative studies of the proteomic testicular profile of men with and without spermatogenic impairment are also discussed and key proteins and pathways involved are highlighted. EXPERT OPINION The difficulty of making age-comparative studies, especially of advanced-age study subjects, makes this topic of study quite challenging. Another topic worth mentioning is the heterogeneous nature and vast cellular composition of testicular tissue, which makes proteome data interpretation tricky. The cell type sorting and comorbidities testing in the testicular tissue of the studied subjects would help mitigate these problems.
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Affiliation(s)
- Ana D Martins
- LAQV-REQUIMTE and Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - João C Ribeiro
- LAQV-REQUIMTE and Department of Chemistry, University of Aveiro, Aveiro, Portugal
- Unit for Multidisciplinary Research in Biomedicine (UMIB), Institute of Biomedical Sciences Abel Salazar (ICBAS), University of Porto, Porto, Portugal
- Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, Porto, Portugal
| | - Rita Ferreira
- LAQV-REQUIMTE and Department of Chemistry, University of Aveiro, Aveiro, Portugal
| | - Marco G Alves
- iBiMED-Institute of Biomedicine, Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Pedro F Oliveira
- LAQV-REQUIMTE and Department of Chemistry, University of Aveiro, Aveiro, Portugal
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