40 research outputs found

    Reduction of Mitoferrin Results in Abnormal Development and Extended Lifespan in Caenorhabditis elegans

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    Iron is essential for organisms. It is mainly utilized in mitochondria for biosynthesis of iron-sulfur clusters, hemes and other cofactors. Mitoferrin 1 and mitoferrin 2, two homologues proteins belonging to the mitochondrial solute carrier family, are required for iron delivery into mitochondria. Mitoferrin 1 is highly expressed in developing erythrocytes which consume a large amount of iron during hemoglobinization. Mitoferrin 2 is ubiquitously expressed, whose functions are less known. Zebrafish with mitoferrin 1 mutation show profound hypochromic anaemia and erythroid maturation arrests, and yeast with defects in MRS3/4, the counterparts of mitoferrin 1/2, has low mitochondrial iron levels and grows poorly by iron depletion. Mitoferrin 1 expression is up-regulated in yeast and mouse models of Fiedreich's ataxia disease and in human cell culture models of Parkinson disease, suggesting its involvement in the pathogenesis of diseases with mitochondrial iron accumulation. In this study we found that reduced mitoferrin levels in C. elegans by RNAi treatment causes pleiotropic phenotypes such as small body size, reduced fecundity, slow movement and increased sensitivity to paraquat. Despite these abnormities, lifespan was increased by 50% to 80% in N2 wild type strain, and in further studies using the RNAi sensitive strain eri-1, more than doubled lifespan was observed. The pathways or mechanisms responsible for the lifespan extension and other phenotypes of mitoferrin RNAi worms are worth further study, which may contribute to our understanding of aging mechanisms and the pathogenesis of iron disorder related diseases

    The rice mitochondrial iron transporter is essential for plant growth

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    In plants, iron (Fe) is essential for mitochondrial electron transport, heme, and Fe-Sulphur (Fe-S) cluster synthesis; however, plant mitochondrial Fe transporters have not been identified. Here we show, identify and characterize the rice mitochondrial Fe transporter (MIT). Based on a transfer DNA library screen, we identified a rice line showing symptoms of Fe deficiency while accumulating high shoot levels of Fe. Homozygous knockout of MIT in this line resulted in a lethal phenotype. MIT localized to the mitochondria and complemented the growth of Δmrs3Δmrs4 yeast defective in mitochondrial Fe transport. The growth of MIT-knockdown (mit-2) plants was also significantly impaired despite abundant Fe accumulation. Further, the decrease in the activity of the mitochondrial and cytosolic Fe-S enzyme, aconitase, indicated that Fe-S cluster synthesis is affected in mit-2 plants. These results indicate that MIT is a mitochondrial Fe transporter essential for rice growth and development

    Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention

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    Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.publishedVersionPeer reviewe

    Genome-wide association analyses of physical activity and sedentary behavior provide insights into underlying mechanisms and roles in disease prevention

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    Although physical activity and sedentary behavior are moderately heritable, little is known about the mechanisms that influence these traits. Combining data for up to 703,901 individuals from 51 studies in a multi-ancestry meta-analysis of genome-wide association studies yields 99 loci that associate with self-reported moderate-to-vigorous intensity physical activity during leisure time (MVPA), leisure screen time (LST) and/or sedentary behavior at work. Loci associated with LST are enriched for genes whose expression in skeletal muscle is altered by resistance training. A missense variant in ACTN3 makes the alpha-actinin-3 filaments more flexible, resulting in lower maximal force in isolated type IIA muscle fibers, and possibly protection from exercise-induced muscle damage. Finally, Mendelian randomization analyses show that beneficial effects of lower LST and higher MVPA on several risk factors and diseases are mediated or confounded by body mass index (BMI). Our results provide insights into physical activity mechanisms and its role in disease prevention.Multi-ancestry meta-analyses of genome-wide association studies for self-reported physical activity during leisure time, leisure screen time, sedentary commuting and sedentary behavior at work identify 99 loci associated with at least one of these traits

    Metformin for prevention or delay of type 2 diabetes mellitus and its associated complications in persons at increased risk for the development of type 2 diabetes mellitus

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    BACKGROUND: The projected rise in the incidence of type 2 diabetes mellitus (T2DM) could develop into a substantial health problem worldwide. Whether metformin can prevent or delay T2DM and its complications in people with increased risk of developing T2DM is unknown. OBJECTIVES: To assess the effects of metformin for the prevention or delay of T2DM and its associated complications in persons at increased risk for the T2DM. SEARCH METHODS: We searched the Cochrane Central Register of Controlled Trials, MEDLINE, Scopus, ClinicalTrials.gov, the World Health Organization (WHO) International Clinical Trials Registry Platform and the reference lists of systematic reviews, articles and health technology assessment reports. We asked investigators of the included trials for information about additional trials. The date of the last search of all databases was March 2019. SELECTION CRITERIA: We included randomised controlled trials (RCTs) with a duration of one year or more comparing metformin with any pharmacological glucose-lowering intervention, behaviour-changing intervention, placebo or standard care in people with impaired glucose tolerance, impaired fasting glucose, moderately elevated glycosylated haemoglobin A1c (HbA1c) or combinations of these. DATA COLLECTION AND ANALYSIS: Two review authors read all abstracts and full-text articles and records, assessed risk of bias and extracted outcome data independently. We used a random-effects model to perform meta-analysis and calculated risk ratios (RRs) for dichotomous outcomes and mean differences (MDs) for continuous outcomes, using 95% confidence intervals (CIs) for effect estimates. We assessed the certainty of the evidence using GRADE. MAIN RESULTS: We included 20 RCTs randomising 6774 participants. One trial contributed 48% of all participants. The duration of intervention in the trials varied from one to five years. We judged none of the trials to be at low risk of bias in all 'Risk of bias' domains. Our main outcome measures were all-cause mortality, incidence of T2DM, serious adverse events (SAEs), cardiovascular mortality, non-fatal myocardial infarction or stroke, health-related quality of life and socioeconomic effects.The following comparisons mostly reported only a fraction of our main outcome set. Fifteen RCTs compared metformin with diet and exercise with or without placebo: all-cause mortality was 7/1353 versus 7/1480 (RR 1.11, 95% CI 0.41 to 3.01; P = 0.83; 2833 participants, 5 trials; very low-quality evidence); incidence of T2DM was 324/1751 versus 529/1881 participants (RR 0.50, 95% CI 0.38 to 0.65; P < 0.001; 3632 participants, 12 trials; moderate-quality evidence); the reporting of SAEs was insufficient and diverse and meta-analysis could not be performed (reported numbers were 4/118 versus 2/191; 309 participants; 4 trials; very low-quality evidence); cardiovascular mortality was 1/1073 versus 4/1082 (2416 participants; 2 trials; very low-quality evidence). One trial reported no clear difference in health-related quality of life after 3.2 years of follow-up (very low-quality evidence). Two trials estimated the direct medical costs (DMC) per participant for metformin varying from 220to220 to 1177 versus 61to61 to 184 in the comparator group (2416 participants; 2 trials; low-quality evidence). Eight RCTs compared metformin with intensive diet and exercise: all-cause mortality was 7/1278 versus 4/1272 (RR 1.61, 95% CI 0.50 to 5.23; P = 0.43; 2550 participants, 4 trials; very low-quality evidence); incidence of T2DM was 304/1455 versus 251/1505 (RR 0.80, 95% CI 0.47 to 1.37; P = 0.42; 2960 participants, 7 trials; moderate-quality evidence); the reporting of SAEs was sparse and meta-analysis could not be performed (one trial reported 1/44 in the metformin group versus 0/36 in the intensive exercise and diet group with SAEs). One trial reported that 1/1073 participants in the metformin group compared with 2/1079 participants in the comparator group died from cardiovascular causes. One trial reported that no participant died due to cardiovascular causes (very low-quality evidence). Two trials estimated the DMC per participant for metformin varying from 220to220 to 1177 versus 225to225 to 3628 in the comparator group (2400 participants; 2 trials; very low-quality evidence). Three RCTs compared metformin with acarbose: all-cause mortality was 1/44 versus 0/45 (89 participants; 1 trial; very low-quality evidence); incidence of T2DM was 12/147 versus 7/148 (RR 1.72, 95% CI 0.72 to 4.14; P = 0.22; 295 participants; 3 trials; low-quality evidence); SAEs were 1/51 versus 2/50 (101 participants; 1 trial; very low-quality evidence). Three RCTs compared metformin with thiazolidinediones: incidence of T2DM was 9/161 versus 9/159 (RR 0.99, 95% CI 0.41 to 2.40; P = 0.98; 320 participants; 3 trials; low-quality evidence). SAEs were 3/45 versus 0/41 (86 participants; 1 trial; very low-quality evidence). Three RCTs compared metformin plus intensive diet and exercise with identical intensive diet and exercise: all-cause mortality was 1/121 versus 1/120 participants (450 participants; 2 trials; very low-quality evidence); incidence of T2DM was 48/166 versus 53/166 (RR 0.55, 95% CI 0.10 to 2.92; P = 0.49; 332 participants; 2 trials; very low-quality evidence). One trial estimated the DMC of metformin plus intensive diet and exercise to be 270perparticipantcomparedwith270 per participant compared with 225 in the comparator group (94 participants; 1 trial; very-low quality evidence). One trial in 45 participants compared metformin with a sulphonylurea. The trial reported no patient-important outcomes. For all comparisons there were no data on non-fatal myocardial infarction, non-fatal stroke or microvascular complications. We identified 11 ongoing trials which potentially could provide data of interest for this review. These trials will add a total of 17,853 participants in future updates of this review. AUTHORS' CONCLUSIONS: Metformin compared with placebo or diet and exercise reduced or delayed the risk of T2DM in people at increased risk for the development of T2DM (moderate-quality evidence). However, metformin compared to intensive diet and exercise did not reduce or delay the risk of T2DM (moderate-quality evidence). Likewise, the combination of metformin and intensive diet and exercise compared to intensive diet and exercise only neither showed an advantage or disadvantage regarding the development of T2DM (very low-quality evidence). Data on patient-important outcomes such as mortality, macrovascular and microvascular diabetic complications and health-related quality of life were sparse or missing

    Was nĂĽtzt uns die Automatisierung bei der Erstellung von Evidenzsynthesen?

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