Evidence map›Paper›PMID 30684245›Full record

ArticleJournal of endocrinological investigation2019

Next-generation sequencing identifies novel mitochondrial variants in pituitary adenomas.

K Németh, O Darvasi, I Likó, N Szücs, S Czirják, L Reiniger, B Szabó, P A Kurucz, L Krokker, P Igaz and 2 more

Open access · hybridAbstract read
In one paragraph

Article in Journal of endocrinological investigation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 19 citations in OpenAlex.

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  10. Authors' response.The Indian journal of medical research · 2020
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 2 institutions in 1 country.

K Németh2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary.
O Darvasi"Lendulet" Hereditary Endocrine Tumours Research Group, Hungarian Academy of Sciences and Semmelweis University, 46 Szentkiralyi Street, Budapest, H-1088, Hungary.
I Likó"Lendulet" Hereditary Endocrine Tumours Research Group, Hungarian Academy of Sciences and Semmelweis University, 46 Szentkiralyi Street, Budapest, H-1088, Hungary.
N Szücs2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary.
S CzirjákNational Institute of Clinical Neurosciences, Budapest, Hungary.
L Reiniger1st Department of Pathology and Experimental Cancer Research, Semmelweis University, Budapest, Hungary.
B SzabóDepartment of Laboratory Medicine, Semmelweis University, Budapest, Hungary.
P A Kurucz2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary.
L Krokker2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary.
P Igaz2nd Department of Internal Medicine, Semmelweis University, Budapest, Hungary.
A Patócs"Lendulet" Hereditary Endocrine Tumours Research Group, Hungarian Academy of Sciences and Semmelweis University, 46 Szentkiralyi Street, Budapest, H-1088, Hungary.
H Butz"Lendulet" Hereditary Endocrine Tumours Research Group, Hungarian Academy of Sciences and Semmelweis University, 46 Szentkiralyi Street, Budapest, H-1088, Hungary. butz.henriett@med.semmelweis-univ.hu.ORCID http://orcid.org/0000-0003-1664-409X
Semmelweis University · HUOrszágos Idegsebészeti Tudományos Intézet · HU

Funding

Magyar Tudományos Akadémia Bolyai Research FellowshipMinistry of Human Capacities NTP-EFÖ-P-15Országos Tudományos Kutatási Alapprogramok OTKA PD116093Semmelweis Egyetem EFOP-3.6.3-VEKOP-16-2017-00009Semmelweis Research Innovation Found STIA-KF-17
6 · The paper itself

Abstract

purposeDisrupted mitochondrial functions and genetic variants of mitochondrial DNA (mtDNA) have been observed in different human neoplasms. Next-generation sequencing (NGS) can be used to detect even low heteroplasmy-level mtDNA variants. We aimed to investigate the mitochondrial genome in pituitary adenomas by NGS.

methodsWe analysed 11 growth hormone producing and 33 non-functioning [22 gonadotroph and 11 hormone immunonegative] pituitary adenomas using VariantPro™ Mitochondrion Panel on Illumina MiSeq instrument. Revised Cambridge Reference Sequence (rCRS) of the mtDNA was used as reference. Heteroplasmy was determined using a 3% cutoff.

results496 variants were identified in pituitary adenomas with overall low level of heteroplasmy (7.22%). On average, 35 variants were detected per sample. Samples harbouring the highest number of variants had the highest Ki-67 indices independently of histological subtypes. We identified eight variants (A11251G, T4216C, T16126C, C15452A, T14798C, A188G, G185A, and T16093C) with different prevalences among different histological groups. T16189C was found in 40% of non-recurrent adenomas, while it was not present in the recurrent ones. T14798C and T4216C were confirmed by Sanger sequencing in all 44 samples. 100% concordance was found between NGS and Sanger method.

conclusionsNGS is a reliable method for investigating mitochondrial genome and heteroplasmy in pituitary adenomas. Out of the 496 detected variants, 414 have not been previously reported in pituitary adenoma. The high number of mtDNA variants may contribute to adenoma genesis, and some variants (i.e., T16189C) might associate with benign behaviour.

Indexed as

Genetic VariationGenome, MitochondrialAdenomaAdultAgedAged, 80 and overBiomarkersDNA, MitochondrialFemaleFollow-Up StudiesHigh-Throughput Nucleotide SequencingHumansMaleMiddle AgedPituitary NeoplasmsPrognosisBiomarkersDNA, MitochondrialGenetic variationsGenomeMitochondriaNext-generation sequencingPathogenesisPituitary adenoma

Identifiers

PMID30684245
PMCPMC6647476
OpenAlexW2911901451

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.