Evidence map›Paper›PMID 35022429›Full record

ArticleScientific reports2022

Contributions of common genetic variants to specific languages and to when a language is learned.

Patrick C M Wong, Xin Kang, Hon-Cheong So, Kwong Wai Choy

Abstract read
In one paragraph

Article in Scientific reports, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

3 citing papers in PubMed.

  1. Article
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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.

Patrick C M WongDepartment of Linguistics and Modern Languages, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China. p.wong@cuhk.edu.hk.ORCID http://orcid.org/0000-0002-6105-5027
Xin KangDepartment of Linguistics and Modern Languages, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China. xin.kang@cqu.edu.cn.ORCID http://orcid.org/0000-0002-1126-5771
Hon-Cheong SoBrain and Mind Institute, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.
Kwong Wai ChoyDepartment of Obsterics and Gynecology, The Chinese University of Hong Kong, Shatin, Hong Kong SAR, China.

Funding

Research Grants Council, University Grants Committee HSSPF #34000118
6 · The paper itself

Abstract

Research over the past two decades has identified a group of common genetic variants explaining a portion of variance in native language ability. The present study investigates whether the same group of genetic variants are associated with different languages and languages learned at different times in life. We recruited 940 young adults who spoke from childhood Chinese and English as their first (native) (L1) and second (L2) language, respectively, who were learners of a new, third (L3) language. For the variants examined, we found a general decrease of contribution of genes to language functions from native to foreign (L2 and L3) languages, with variance in foreign languages explained largely by non-genetic factors such as musical training and motivation. Furthermore, genetic variants that were found to contribute to traits specific to Chinese and English respectively exerted the strongest effects on L1 and L2. These results seem to speak against the hypothesis of a language- and time-universal genetic core of linguistic functions. Instead, they provide preliminary evidence that genetic contribution to language may depend at least partly on the intricate language-specific features. Future research including a larger sample size, more languages and more genetic variants is required to further explore these hypotheses.

Indexed as

LanguagePolymorphism, Single NucleotideVerbal LearningFemaleHumansLatent Class AnalysisMaleYoung Adult

Identifiers

PMID35022429
PMCPMC8755716

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Registered trials

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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.