Mohammad Mehdi Banoei

Beta-Thalassemia in Iran: New Insight into the Role of Genetic Admixture and Migration

Iran with an area of 1.648 million km2 is located between the Caspian Sea and the Persian Gulf. The Iranian population consists of multiethnic groups that have been influenced by various invasions and migration throughout history. Studies have revealed the presence of more than 47 different β-globin gene mutations responsible for β-Thalassemia in Iran. This paper is an attempt to study the origin of β-Thalassemia mutations in different parts of Iran. Distribution of β-Thalassemia mutations in Iran shows different patterns in different areas. β-Thalassemia mutations have been a reflection of people and area in correlation with migration and origin of ancestors. We compared the frequencies of β-globin mutations in different regions of Iran with those derived from neighboring countries. The analysis provided evidence of complementary information about the genetic admixture and migration of some mutations, as well as the remarkable genetic classification of the Iranian people and ethnic groups.

Mitochondrial tRNALeu/Lys and ATPase 6/8 Gene Variations in Spinocerebellar Ataxias

Background: The spinocerebellar ataxias (SCA) comprise a heterogeneous group of severe late-onset neurodegenerative diseases that are promoted by the expansion of a tandem-arrayed DNA sequence that modifies the primary structure of the protein. Methods: Genomic DNA of 20 patients affected with SCAs was extracted from peripheral blood and screened for deletions in mitochondrial DNA (mtDNA). Sequencing of tRNALeu,tRNALys, cytochrome oxidase II, ATPase 6/8 and NADH dehydrogenase I (NDI) genes belonging to mtDNA from patients with SCAs was also carried out to detect the presence of variations. Results: We identified cytosine-adenine-guanine (CAG) trinucleotide repeat expansions in 20 patients. Seven of these patients had at least one nucleotide change in mtDNA. In such cases, 5 nucleotide variations resulted in amino acid changes with two novel variations T8256G and G9010A. Conclusion: SCA patients showed high levels of mtDNA variations in lymphocytes. It can be proposed that the SCA gene proteins (Ataxins) are involved in the complicated intracellular mechanisms that affect cellular organelles and their components, such as the mitochondrial genome. The instability of CAG repeats in polyglutamine diseases such as SCAs and Huntington’s disease might be a causative factor in mtDNA variation or possible damage.

Metabolomics: Applications and Promise in Mycobacterial Disease

Until recently, the study of mycobacterial diseases was trapped in culture-based technology that is more than a century old. The use of nucleic acid amplification is changing this, and powerful new technologies are on the horizon. Metabolomics, which is the study of sets of metabolites of both the bacteria and host, is being used to clarify mechanisms of disease, and can identify changes leading to better diagnosis, treatment, and prognostication of mycobacterial diseases. Metabolomic profiles are arrays of biochemical products of genes in their environment. These complex patterns are biomarkers that can allow a more complete understanding of cell function, dysfunction, and perturbation than genomics or proteomics. Metabolomics could herald sweeping advances in personalized medicine and clinical trial design, but the challenges in metabolomics are also great. Measured metabolite concentrations vary with the timing within a condition, the intrinsic biology, the instruments, and the sample preparation. Metabolism profoundly changes with age, sex, variations in gut microbial flora, and lifestyle. Validation of biomarkers is complicated by measurement accuracy, selectivity, linearity, reproducibility, robustness, and limits of detection. The statistical challenges include analysis, interpretation, and description of the vast amount of data generated. Despite these drawbacks, metabolomics provides great opportunity and the potential to understand and manage mycobacterial diseases.

Investigation of tRNALeu/Lys and ATPase 6 Genes Mutations in Huntington’s Disease

Huntington disease (HD) is a genetically dominant condition caused by expanded CAG repeats which code for glutamine in the HD gene product, huntingtin. Huntingtin is expressed in almost all tissues, so abnormalities outside the brain can also be expected. Involvement of nuclei and mitochondria in HD pathophysiology has been suggested. In fact mitochondrial dysfunction is reported in brains of patients suffering from HD. The tRNA gene mutations are one of hot spots that can cause mitochondrial disorders. In this study, possible mitochondrial DNA (mtDNA) damage was evaluated by screening for mutations in the tRNAleu/lys and ATPase 6 genes of 20 patients with HD, using PCR and automated DNA sequencing. Mutations including an A8656G mutation in one patient were observed, which may be causal to the disease. Understanding the role of mitochondria in the pathogenesis of neurodegenerative diseases could potentially be important for the development of therapeutic strategies in HD.

Plasma metabolomics for the diagnosis and prognosis of H1N1 influenza pneumonia

BackgroundMetabolomics is a tool that has been used for the diagnosis and prognosis of specific diseases. The purpose of this study was to examine if metabolomics could be used as a potential diagnostic and prognostic tool for H1N1 pneumonia. Our hypothesis was that metabolomics can potentially be used early for the diagnosis and prognosis of H1N1 influenza pneumonia.Methods1H nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry were used to profile the metabolome in 42 patients with H1N1 pneumonia, 31 ventilated control subjects in the intensive care unit (ICU), and 30 culture-positive plasma samples from patients with bacterial community-acquired pneumonia drawn within the first 24 h of hospital admission for diagnosis and prognosis of disease.ResultsWe found that plasma-based metabolomics from samples taken within 24 h of hospital admission can be used to discriminate H1N1 pneumonia from bacterial pneumonia and nonsurvivors from survivors of H1N1 pneumonia. Moreover, metabolomics is a highly sensitive and specific tool for the 90-day prognosis of mortality in H1N1 pneumonia.ConclusionsThis study demonstrates that H1N1 pneumonia can create a quite different plasma metabolic profile from bacterial culture-positive pneumonia and ventilated control subjects in the ICU on the basis of plasma samples taken within 24 h of hospital/ICU admission, early in the course of disease.

Do mitochondrial DNA haplogroups play a role in susceptibility to tuberculosis

Background and objectives:  Mitochondrial DNA has a unique role in ATP production and subsequent mitochondrial reactive oxygen species (ROS) production in eukaryotic cells and there is a potential role for ROS and oxygen burst against Mycobacterium tuberculosis, an intracellular pathogen. This study aimed to determine whether the frequency of different mitochondrial haplogroups was significantly different in patients with tuberculosis (TB) compared with a normal population.

Metabolomics and Biomarker Discovery in Traumatic Brain Injury

Traumatic brain injury (TBI) is one of the leading causes of disability and mortality worldwide. The TBI pathogenesis can induce broad pathophysiological consequences and clinical outcomes attributed to the complexity of the brain. Thus, the diagnosis and prognosis are important issues for the management of mild, moderate, and severe forms of TBI. Metabolomics of readily accessible biofluids is a promising tool for establishing more useful and reliable biomarkers of TBI than using clinical findings alone. Metabolites are an integral part of all biochemical and pathophysiological pathways. Metabolomic processes respond to the internal and external stimuli resulting in an alteration of metabolite concentrations. Current high-throughput and highly sensitive analytical tools are capable of detecting and quantifying small concentrations of metabolites, allowing one to measure metabolite alterations after a pathological event when compared to a normal state or a different pathological process. Further, these metabolic biomarkers could be used for the assessment of injury severity, discovery of mechanisms of injury, and defining structural damage in the brain in TBI. Metabolic biomarkers can also be used for the prediction of outcome, monitoring treatment response, in the assessment of or prognosis of post-injury recovery, and potentially in the use of neuroplasticity procedures. Metabolomics can also enhance our understanding of the pathophysiological mechanisms of TBI, both in primary and secondary injury. Thus, this review presents the promising application of metabolomics for the assessment of TBI as a stand-alone platform or in association with proteomics in the clinical setting.

Evolution of ARDS Biomarkers, Will Metabolomics Be the Answer?

To date, there is no clinically agreed-upon diagnostic test for acute respiratory distress syndrome (ARDS): the condition is still diagnosed on the basis of a constellation of clinical findings, laboratory tests, and radiological images. Development of ARDS biomarkers has been in a state of continuous flux during the past four decades. To address ARDS heterogeneity, several studies have recently focused on subphenotyping the disease on the basis of observable clinical characteristics and associated blood biomarkers. However, the strong correlation between identified biomarkers and ARDS subphenotypes has yet to establish etiology; hence, there is a need for the adoption of other methodologies for studying ARDS. In this review, we will shed light on ARDS metabolomics research in the literature and discuss advances and major obstacles encountered in ARDS metabolomics research. Generally, the ARDS metabolomics studies focused on identification of differentiating metabolites for diagnosing ARDS, but they were performed to different standards in terms of sample size, selection of control cohort, type of specimens collected, and measuring technique utilized. Virtually none of these studies have been properly validated to identify true metabolomics biomarkers of ARDS. Though in their infancy, metabolomics studies exhibit promise to unfold the biological processes underlying ARDS and, in our opinion, have great potential for pushing forward our present understanding of ARDS.

Reply: Metabolomics and Mycobacterial Disease: Don’t Forget the Bioinformatics

to the development of high-resolution metabolomics (2, 3), which significantly improves the limit of detection of small molecules and may be crucial for the detection of low-abundance ions such as those derived from the mycobacterial cell envelope. Traditional methods in metabolomics identify several hundred to a few thousand metabolites in biologic samples, with high reproducibility. However, low-abundance metabolites can be missed by these methods. High-resolution metabolomics offers the ability to detect more than 20,000 metabolites (.100,000 ions) in biologic samples (4). This capability is obtained by use of ultrahigh-resolution, accurate mass instruments, analysis in triplicate with rigorous standard operating procedures, and advanced data extraction methods (2–4); the approach supports measurement of metabolites differing by more than seven orders of magnitude in absolute concentration (4). Coupled with new bioinformatics and pathway and network methods to characterize both known and unidentified metabolites (3, 5), high-resolution metabolomics allows the study of the complex mixture of metabolites derived from the diet and endogenous nutrient metabolism, the gut microbiota, infective microorganisms and host–pathogen interactions, drugs, and the environment. Our group recently used these methods to obtain a more comprehensive description of the plasma metabolome from patients with pulmonary tuberculosis (6). Important differences in both mycobacterial cell wall and host immune metabolites were identified, allowing for patients with active tuberculosis to be successfully differentiated from household contacts without active tuberculosis. Because Mycobacterium tuberculosis-derived metabolites with the potential for biomarker development are in relatively low abundance in biologic samples, high-sensitivity methods are an important tool for the development of metabolic signatures specific to this pathogen. Thus, although the authors effectively describe the great promise of the emerging field of metabolomics for the identification of novel biomarkers and host–pathogen interactions in mycobacterial diseases, we feel that additional recognition is warranted concerning the advanced computational methods needed to effectively use the complex information-rich mass spectrometry analyses. Metabolomics experts agree that the human metabolome contains hundreds of thousands of chemicals. Ongoing advances in data sciences are critical to transform this broad spectrum of metabolic information into knowledge. With improved computational pipelines, metabolomics is certain to advance understanding of host susceptibility and host–pathogen interactions, decrease disease burden, and address critical issues of multidrug resistance.

Association of genetic variations in the mitochondrial D-loop with β-thalassemia

Abstract Beta-thalassemia, one of the most common single-gene disorders, is the result of reduced or absent production of β-globin chains. Patients with β-thalassemia show weak genotype–phenotype correlations. Mitochondrial DNA polymorphisms are a potential source for different physiological and pathological characteristics and have been found to be associated as genetic modifiers with various pathophysiologies, including cancers and neurodegenerative diseases. A group of 35 patients with β-thalassemia was investigated for the presence of mtDNA D-loop polymorphisms in comparison with 504 normal controls. We found four mtDNA D-loop polymorphisms at nucleotides 16,069C > T, 16,189T > C, 16,319G > A, and 16,519T > C that showed significant differences between patients and normal subjects. There is no strong proof for the association of these polymorphisms with β-thalassemia. It is hypothesized that iron overload or its effects on sequestration of calcium or zinc can lead to oxidative stress and ROS production inside the mitochondria. Therefore, possible accompanying of mtDNA polymorphisms with β-thalassemia disease may complicate the genotype–phenotype correlation and could affect the clinical outcomes in the patients.