PITPNA

Last update 08 May 2025

Basic Info

Synonyms

phosphatidylinositol transfer protein alpha, Phosphatidylinositol transfer protein alpha isoform, PI-TP-alpha

+ [5]

Introduction

Catalyzes the transfer of phosphatidylinositol (PI) and phosphatidylcholine (PC) between membranes (PubMed:10531358, PubMed:14962392, PubMed:15522822, PubMed:18636990, PubMed:22822086). Shows a preference for PI and PC containing shorter saturated or monosaturated acyl chains at the sn-1 and sn-2 positions (PubMed:15522822, PubMed:22822086). Preference order for PC is C16:1 > C16:0 > C18:1 > C18:0 > C20:4 and for PI is C16:1 > C16:0 > C18:1 > C18:0 > C20:4 > C20:3 (PubMed:22822086).

100 Clinical Results associated with PITPNA

100 Translational Medicine associated with PITPNA

0 Patents (Medical) associated with PITPNA

Literatures (Medical) associated with PITPNA

07 Nov 2023·BMC genomics

Broodstock nutritional programming differentially affects the hepatic transcriptome and genome-wide DNA methylome of farmed gilthead sea bream (Sparus aurata) depending on genetic background

Article

Author: Izquierdo, M ; Llorens, C ; Zamorano, M J ; Calduch-Giner, J ; Pérez-Sánchez, J ; Fontanillas, R ; Soriano, B ; Sarih, S ; Montero, D ; Naya-Català, F ; Torrecillas, S ; Belenguer, A

AbstractBackgroundBroodstock nutritional programming improves the offspring utilization of plant-based diets in gilthead sea bream through changes in hepatic metabolism. Attention was initially focused on fatty acid desaturases, but it can involve a wide range of processes that remain largely unexplored. How all this can be driven by a different genetic background is hardly underlined, and the present study aimed to assess how broodstock nutrition affects differentially the transcriptome and genome-wide DNA methylome of reference and genetically selected fish within the PROGENSA® selection program.ResultsAfter the stimulus phase with a low fish oil diet, two offspring subsets of each genetic background received a control or a FUTURE-based diet. This highlighted a different hepatic transcriptome (RNA-seq) and genome-wide DNA methylation (MBD-seq) pattern depending on the genetic background. The number of differentially expressed transcripts following the challenge phase varied from 323 in reference fish to 2,009 in genetically selected fish. The number of discriminant transcripts, and associated enriched functions, were also markedly higher in selected fish. Moreover, correlation analysis depicted a hyper-methylated and down-regulated gene expression state in selected fish with the FUTURE diet, whereas the opposite pattern appeared in reference fish. After filtering for highly represented functions in selected fish, 115 epigenetic markers were retrieved in this group. Among them, lipid metabolism genes (23) were the most reactive following ordering by fold-change in expression, rendering a final list of 10 top markers with a key role on hepatic lipogenesis and fatty acid metabolism (cd36, pitpna, cidea, fasn, g6pd, lipt1, scd1a, acsbg2, acsl14, acsbg2).ConclusionsGene expression profiles and methylation signatures were dependent on genetic background in our experimental model. Such assumption affected the magnitude, but also the type and direction of change. Thus, the resulting epigenetic clock of reference fish might depict an older phenotype with a lower methylation for the epigenetically responsive genes with a negative methylation-expression pattern. Therefore, epigenetic markers will be specific of each genetic lineage, serving the broodstock programming in our selected fish to prevent and mitigate later in life the risk of hepatic steatosis through changes in hepatic lipogenesis and fatty acid metabolism.

25 Jul 2023·Science Signaling

Rescuing β cells

Article

Author: Baek, Amy E

Loss of phosphatidylinositol transfer protein alpha underlies pancreatic β cell failure.

02 Mar 2023·Aging

lncRNA PITPNA-AS1 promotes cell proliferation and metastasis in hepatocellular carcinoma by upregulating PDGFD.

Article

Author: Yao, Jianguo ; Liu, Xiaojian

Hepatocellular carcinoma (HCC) ranks high in morbidity and mortality among notorious malignancies because of the lack of effective biomarkers and treatments. LncRNA PITPNA antisense RNA 1 (PITPNA-AS1) plays an oncogenic role in HCC, yet the mechanistic basis remains unprobed. Here using Bioinformatics and PCR analyses, we validated that PITPNA-AS1 expression was significantly increased in HCC. The levels of PITPNA-AS1 in tumors were reversely correlated with the prognosis in HCC patients. Downregulation of PITPNA-AS1 inhibited malignant activities of HCC cells. Next, we elucidated that PITPNA-AS1 acts as a competing endogenous RNA (ceRNA) to sponge miR-363-5p, thereby regulating the expression of platelet-derived growth factor-D (PDGFD). Moreover, the suppression of HCC cell activities by PITPNA-AS1 downregulation can be removed by PDGFD overexpression or miR-363-5p inhibition. Collectively, our work reveals the involvement of the PITPNA-AS1/miR-363-5p/PDGFD regulatory axis in HCC progression.

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PITPNA

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