Ask about this productRelated genes to: MTMR14 antibody
- Gene:
- MTMR14 NIH gene
- Name:
- myotubularin related protein 14
- Previous symbol:
- C3orf29
- Synonyms:
- FLJ22405, FLJ90311, hJumpy, hEDTP
- Chromosome:
- 3p25.3
- Locus Type:
- gene with protein product
- Date approved:
- 2005-12-22
- Date modifiied:
- 2016-10-05
Related products to: MTMR14 antibody
Related articles to: MTMR14 antibody
- Frailty and cognitive impairments frequently co-occur in older adults. It remains unclear whether this overlap reflects shared underlying biological mechanisms or parallel but distinct disease pathways. We hypothesize that physical weakness and cognitive impairment share circulating markers already in an early disease stage. We therefore recruited and analyzed a relatively healthy population with partially overlapping pre-frailty and mild cognitive impairment (MCI), and applied a multi-omics approach to identify shared and distinct molecular signatures in plasma. Community-dwelling older adults were recruited, and frailty status was determined using the Fried frailty criteria. Cognitive function was assessed in all subjects using the Montreal Cognitive Assessment (MoCA) and MemTrax tests. Blood samples were collected in the fasted state, and plasma was used for multi-omics analyses, including proteomic profiling using the SomaLogic 11 k platform, Nightingale metabolomics, and liquid chromatography-tandem mass spectrometry (LC-MS/MS). A total of 50 community-dwelling older adults (79.9 ± 0.5 years) were recruited, comprising 29 fit individuals (14 females, 15 males) and 21 pre-frail individuals (9 females, 12 males). Pre-frail individuals scored significantly lower on the MoCA test (- 12%, P = 0.006) and MemTrax accuracy (- 4%, P = 0.03), indicating worse cognitive performance. Proteomics analysis identified 21 biomarkers associated with MCI, including APP, ACHE, and ADGRB1, and 24 biomarkers associated with pre-frailty, including FABP2, KNG1, and MTMR14. Contrary to our hypothesis, no biomarkers were shared between the pre-frailty and MCI proteomic signatures. Metabolomics analyses identified two biomarkers associated with pre-frailty and ten associated with MCI, again with no overlap between the two conditions. LC-MS/MS identified C18:0 acylcarnitine as a biomarker for pre-frailty, but not MCI. Despite consistent differences in cognitive performance between fit and pre-frail individuals, pre-frailty and MCI were characterized by distinct proteomic and metabolomic signatures, with no detectable molecular overlap. These findings suggest that the frequently observed clinical co-occurrence of frailty and cognitive impairment arises from parallel but biologically distinct disease processes, at least in early disease stages. If confirmed in a larger cohort, this suggests that both conditions will benefit from disease-specific treatments.Trial registration: The FITAAL study was registered in the Dutch Trial Register, with registration code NTR6124. - Source: PubMed
Publication date: 2026/08/21
de Jong Jelle C B Cvan der Hoek Marjanne DKoopman Koen W Wvan den Hoek Anita MVeeger Nic J G MKuda Ondřejvan der Leij Feike RVerschuren LarsKeijer JaapNieuwenhuizen Arie G - Autophagy is a lysosome-mediated self-degradation process of eukaryotic cells which is critical for the elimination of cellular damage. Its capacity progressively declines with age, and this change can lead to the development of various neurodegenerative pathologies including Spinocerebellar ataxia type 1 (SCA1). SCA1 is mainly caused by mutations in the polyglutamine region of Ataxin 1 protein. In patients affected by the disease, Purkinje neurons of the cerebellum frequently undergo demise and eventually become lost. Here we tested whether two well-characterized autophagy-enhancing small molecules, AUTEN-67 and -99, which antagonize the autophagy complex Vps34 through blocking the myotubularin-related lipid phosphatase MTMR14/EDTP, have the capacity to ameliorate SCA1 symptoms. We found that in a model of SCA1, only AUTEN-67 exerts positive effects including improvement in climbing ability and extending life span. Based on these results, we hypothesized that the two compounds influence autophagy in the brain in a neuron-specific manner. Indeed, according to data we obtained, AUTEN-67 and -99 exhibit shared and unique functional domains in the brain. AUTENs enhance autophagy in GABAergic and dopaminergic neurons. In addition, AUTEN-67 also affect autophagy in cholinergic neurons, while AUTEN-99 trigger the process in glutaminergic neurons and motoneurons. We also observed varying efficiencies between the two AUTENs among different subtypes of cultured hippocampal neurons of mice. These data suggest that the two compounds display neuron-specific differences in exerting autophagy-enhancing effects, and may lead to a better understanding of which types of neurons autophagy could potentially be activated to treat SCA1 in human patients. - Source: PubMed
Publication date: 2025/10/27
Burján TímeaAslam MaryamKeresztes FanniSigmond TímeaBilles Viktor ABencsik NorbertSchlett KatalinVellai TiborKovács Tibor - Chronic obstructive pulmonary disease (COPD) is typically characterized by chronic airway inflammation and emphysema. Macrophage polarization plays an important role in COPD, while the precise molecules and mechanisms underpinning it have yet to be fully elucidated. Pulmonary decrease of myotubularin-related protein 14 (MTMR14) expression conduces to the progression of COPD in our prior publication, while the further analysis reveals the differential expression of MTMR14 in alveolar macrophages, whose function and related mechanisms are worth further research. Our study aims to investigate the role and mechanism of MTMR14 in macrophages of COPD. - Source: PubMed
Publication date: 2025/07/10
Zhang JiahengZhan YuanDeng ZhesongChen ShanshanYang RuonanZhang YatingFu HaoHuang QianWu JixingGu YiyaXie Jungang - Existing observational studies examining the effect of body fat on the risk of Parkinson disease (PD) have yielded inconsistent results. We aimed to investigate this causal relationship at the genetic level. - Source: PubMed
Zhao QianLiu DongmingBaranova AnchaCao HongbaoZhang Fuquan - The meat production traits of pigs are influenced by the expression regulation of multiple gene types, including mRNAs, miRNAs, and lncRNAs. To study the differences in meat production traits at the transcriptional level among individuals with different growth rates, the samples from eight Duroc × Bama Xiang F2 crossbred pigs with a fast growth rate (high gTroup) or a slow growth rate (low group) were selected to perform whole transcriptome sequencing and ceRNA regulatory network construction. This study first analyzed the differences in physiological and biochemical indicators, muscle histological characteristics, and muscle fiber types. A total of 248 mRNAs, 25 miRNAs, and 432 lncRNAs were identified as differentially expressed by whole transcriptome sequencing. Key genes that may influence meat production traits include , , , , , and . The ceRNA regulatory network map showed that ENSSSCG00000042061-ssc-mir-208b-, ENSSSCG00000042223-ssc-mir-146a-, ENSSSCG00000045539-ssc-mir-9-3-, and ENSSSCG00000047852-ssc-mir-103-1- may be the key factors affecting meat production traits through their regulatory relationships. This study provides valuable insights into the molecular mechanisms underlying porcine muscle development and can aid in improving meat production traits. - Source: PubMed
Publication date: 2024/08/14
Xu YupeiWang HuiCheng FengChen KuirongLei GuofengDeng ZhongrongWu XiaoxiaoLiu CongSi JingleiLiang Jing