Evidence map›Paper›PMID 36438765›Full record

ReviewFrontiers in nutrition2022

Non-coding RNAs: The link between maternal malnutrition and offspring metabolism.

Yuan Zeng, Yifan Wu, Qian Zhang, Xinhua Xiao

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in nutrition, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
1.0field-weighted citation impact, top 25% 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

8 citing papers in PubMed, 11 citations in OpenAlex.

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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

4 authors at 2 institutions in 1 country.

Yuan ZengKey Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Yifan WuKey Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Qian ZhangKey Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Xinhua XiaoKey Laboratory of Endocrinology, Ministry of Health, Department of Endocrinology, Peking Union Medical College Hospital, Peking Union Medical College, Chinese Academy of Medical Sciences, Beijing, China.
Peking Union Medical College Hospital · CNChinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Early life nutrition is associated with the development and metabolism in later life, which is known as the Developmental Origin of Health and Diseases (DOHaD). Epigenetics have been proposed as an important explanation for this link between early life malnutrition and long-term diseases. Non-coding RNAs (ncRNAs) may play a role in this epigenetic programming. The expression of ncRNAs (such as long non-coding RNA H19, microRNA-122, and circular RNA-SETD2) was significantly altered in specific tissues of offspring exposed to maternal malnutrition. Changes in these downstream targets of ncRNAs lead to abnormal development and metabolism. This review aims to summarize the existing knowledge on ncRNAs linking the maternal nutrition condition and offspring metabolic diseases, such as obesity, type 2 diabetes (T2D) and non-alcoholic fatty liver disease (NAFLD).

Indexed as

DOHaDgestational diabetes mellitusmetabolic syndromenon-coding RNAobesity

Identifiers

PMID36438765
PMCPMC9684648
OpenAlexW4308878102

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

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 Socratic graph.