Evidence map›Paper›PMID 32329556›Full record

ArticleHuman brain mapping2020

Partitioning heritability analyses unveil the genetic architecture of human brain multidimensional functional connectivity patterns.

Junjiao Feng, Chunhui Chen, Ying Cai, Zhifang Ye, Kanyin Feng, Jing Liu, Liang Zhang, Qinghao Yang, Anqi Li, Jintao Sheng and 5 more

Abstract read
In one paragraph

Article in Human brain mapping, 2020. 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
–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

10 citing papers in PubMed.

  1. Observational
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Twin studies to GWAS: there and back again.Trends in cognitive sciences · 2021
    Review
  9. Article
  10. Article
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

15 authors.

Junjiao FengState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.ORCID 0000-0003-3015-357X
Chunhui ChenState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Ying CaiDepartment of Psychology and Behavioral Sciences, Zhejiang University, Hangzhou, China.
Zhifang YeState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Kanyin FengState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Jing LiuState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Liang ZhangState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Qinghao YangState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Anqi LiState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Jintao ShengState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Bi ZhuState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Zhaoxia YuDepartment of Statistics, University of California, Irvine, California, USA.
Chuansheng ChenDepartment of Psychological Science, University of California, Irvine, California, USA.
Qi DongState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.
Gui XueState Key Laboratory of Cognitive Neuroscience and Learning & IDG/McGovern Institute for Brain Research, Beijing Normal University, Beijing, China.

Funding

Guangdong Pearl River Talents Plan Innovative and Entrepreneurial team grant 2016ZT06S220National Natural Science Foundation of China 31730038The NSFC and the German Research Foundation (DFG) joint project NSFC 61621136008 / DFG TRR-169
6 · The paper itself

Abstract

Resting-state functional connectivity profiles have been increasingly shown to be important endophenotypes that are tightly linked to human cognitive functions and psychiatric diseases, yet the genetic architecture of this multidimensional trait is barely understood. Using a unique sample of 1,704 unrelated, young and healthy Chinese Han individuals, we revealed a significant heritability of functional connectivity patterns in the whole brain and several subnetworks. We further proposed a partitioned heritability analysis for multidimensional functional connectivity patterns, which revealed the common and unique enrichment patterns of the genetic contributions to brain connectivity patterns for several gene sets linked to brain functions, including the genes expressed preferentially in the central nervous system and those associated with intelligence, educational attainment, attention-deficit/hyperactivity disorder, and schizophrenia. These results for the first time reveal the genetic architecture of multidimensional brain connectivity patterns across different networks and advance our understanding of the complex relationship between gene sets, neural networks, and behaviors.

Indexed as

Academic SuccessBrainConnectomeNerve NetSchizophreniaAdolescentAdultAttention Deficit Disorder with HyperactivityFemaleHumansIntelligenceMagnetic Resonance ImagingMaleMultifactorial InheritanceYoung Adultcognitive functionsmultidimensional functional connectivity patternspartitioned heritabilitypsychiatric diseasesSNP-based heritability

Identifiers

PMID32329556
PMCPMC7375050

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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.