Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 477

The DOI matches its Crossref record.

Germline mutations of the MEN1 gene in familial multiple endocrine neoplasia type 1 and related states

Agarwal, S.·1997·Human Molecular Genetics

Abstract

Familial multiple endocrine neoplasia type 1 (FMEN1) is an autosomal dominant trait characterized by tumors of the parathyroids, gastro-intestinal endocrine tissue, anterior pituitary and other tissues. We recently cloned the MEN1 gene and confirmed its identity by finding mutations in FMEN1. We have now extended our mutation analysis to 34 more unrelated FMEN1 probands and to two related states, sporadic MEN1 and familial hyperparathyroidism. There was a high prevalence of heterozygous germline MEN1 mutations in sporadic MEN1 (8/11 cases) and in FMEN1 (47/50 probands). One case of sporadic MEN1 was proven to be a new MEN1 mutation. Eight different mutations were observed more than once in FMEN1. Forty different mutations (32 FMEN1 and eight sporadic MEN1) were distributed across the MEN1 gene. Most predicted loss of function of the encoded menin protein, supporting the prediction that MEN1 is a tumor suppressor gene. No MEN1 germline mutation was found in five probands with familial hyperparathyroidism, suggesting that familial hyperparathyroidism often is caused by mutation in another gene or gene(s).

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1093/hmg/6.7.1169

Cites

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cited by

See all 477

Metadata

Authors
Agarwal, S.
Venue
Human Molecular Genetics
Published
1997-07-01
Volume
6
Issue
7
Pages
1169-1175
ISSN
  • 0964-6906 (ISSN-L)
  • 1460-2083
OpenAlex
W2162942974
Cited by
477
References
0
FWCI
40.70
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Germline mutations of the MEN1 gene in familial multiple endocrine neoplasia type 1 and related states. https://app.cochat.ai/papers/10.1093/hmg/6.7.1169
The paper
Agarwal, S. (1997). Germline mutations of the MEN1 gene in familial multiple endocrine neoplasia type 1 and related states. Human Molecular Genetics. https://doi.org/10.1093/hmg/6.7.1169

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.