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Total genetic contribution assessment across the human genome.

ABSTRACT: Quantifying the overall magnitude of every single locus' genetic effect on the widely measured human phenome is of great challenge. We introduce a unified modelling technique that can consistently provide a total genetic contribution assessment (TGCA) of a gene or genetic variant without thresholding genetic association signals. Genome-wide TGCA in five UK Biobank phenotype domains highlights loci such as the HLA locus for medical conditions, the bone mineral density locus WNT16 for physical measures, and the skin tanning locus MC1R and smoking behaviour locus CHRNA3 for lifestyle. Tissue-specificity investigation reveals several tissues associated with total genetic contributions, including the brain tissues for mental health. Such associations are driven by tissue-specific gene expressions, which share genetic basis with the total genetic contributions. TGCA can provide a genome-wide atlas for the overall genetic contributions in each particular domain of human complex traits.

SUBMITTER: Li T

PROVIDER: S-EPMC8121943 | biostudies-literature | 2021 May

REPOSITORIES: biostudies-literature

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Total genetic contribution assessment across the human genome.

Li Ting T Ning Zheng Z Yang Zhijian Z Zhai Ranran R Zheng Chenqing C Xu Wenzheng W Wang Yipeng Y Ying Kejun K Chen Yiwen Y Shen Xia X

Nature communications 20210514 1

Quantifying the overall magnitude of every single locus' genetic effect on the widely measured human phenome is of great challenge. We introduce a unified modelling technique that can consistently provide a total genetic contribution assessment (TGCA) of a gene or genetic variant without thresholding genetic association signals. Genome-wide TGCA in five UK Biobank phenotype domains highlights loci such as the HLA locus for medical conditions, the bone mineral density locus WNT16 for physical mea ...[more]

PMID: 33990588

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Project description:BackgroundGenome-wide association studies have identified statistical associations between various diseases, including cancers, and a large number of single-nucleotide polymorphisms (SNPs). However, they provide no direct explanation of the mechanisms underlying the association. Based on the recent discovery that changes in three-dimensional genome organization may have functional consequences on gene regulation favoring diseases, we investigated systematically the genome-wide distribution of disease-associated SNPs with respect to a specific feature of 3D genome organization: topologically associating domains (TADs) and their borders.ResultsFor each of 449 diseases, we tested whether the associated SNPs are present in TAD borders more often than observed by chance, where chance (i.e., the null model in statistical terms) corresponds to the same number of pointwise loci drawn at random either in the entire genome, or in the entire set of disease-associated SNPs listed in the GWAS catalog. Our analysis shows that a fraction of diseases displays such a preferential localization of their risk loci. Moreover, cancers are relatively more frequent among these diseases, and this predominance is generally enhanced when considering only intergenic SNPs. The structure of SNP-based diseasome networks confirms that localization of risk loci in TAD borders differs between cancers and non-cancer diseases. Furthermore, different TAD border enrichments are observed in embryonic stem cells and differentiated cells, consistent with changes in topological domains along embryogenesis and delineating their contribution to disease risk.ConclusionsOur results suggest that, for certain diseases, part of the genetic risk lies in a local genetic variation affecting the genome partitioning in topologically insulated domains. Investigating this possible contribution to genetic risk is particularly relevant in cancers. This study thus opens a way of interpreting genome-wide association studies, by distinguishing two types of disease-associated SNPs: one with an effect on an individual gene, the other acting in interplay with 3D genome organization.

Project description:Parkinson's disease is a complex neurodegenerative disorder with a strong genetic component, for which most known disease-associated variants are single nucleotide polymorphisms (SNPs) and small insertions and deletions (indels). DNA repetitive elements account for >50% of the human genome; however, little is known of their contribution to Parkinson's disease aetiology. While select short tandem repeats (STRs) within candidate genes have been studied in Parkinson's disease, their genome-wide contribution remains unknown. Here we present the first genome-wide association study of STRs in Parkinson's disease. Through a meta-analysis of 16 imputed genome-wide association study cohorts from the International Parkinson's Disease Genomic Consortium (IPDGC), totalling 39 087 individuals (16 642 cases and 22 445 controls of European ancestry), we identified 34 genome-wide significant STR loci (P < 5.34 × 10-6), with the strongest signal located in KANSL1 [chr17:44 205 351:[T]11, P = 3 × 10-39, odds ratio = 1.31 (95% confidence interval = 1.26-1.36)]. Conditional-joint analyses suggested that four significant STRs mapping nearby NDUFAF2, TRIML2, MIRNA-129-1 and NCOR1 were independent from known risk SNPs. Including STRs in heritability estimates increased the variance explained by SNPs alone. Gene expression analysis of STRs (eSTRs) in RNA sequencing data from 13 brain regions identified significant associations of STRs influencing the expression of multiple genes, including known Parkinson's disease genes. Further functional annotation of candidate STRs revealed that significant eSTRs within NUDFAF2 and ZSWIM7 overlap with regulatory features and are associated with change in the expression levels of nearby genes. Here, we show that STRs at known and novel candidate loci contribute to Parkinson's disease risk and have functional effects in disease-relevant tissues and pathways, supporting previously reported disease-associated genes and giving further evidence for their functional prioritization. These data represent a valuable resource for researchers currently dissecting Parkinson's disease risk loci.

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Total genetic contribution assessment across the human genome.

Publications

Total genetic contribution assessment across the human genome.

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