Systematic investigation of allelic regulatory activity of schizophrenia-associated common variants

Abstract

Genome-wide association studies (GWAS) have successfully identified 145 genomic regions that contribute to schizophrenia risk, but linkage disequilibrium (LD) makes it challenging to discern causal variants. Computational finemapping prioritized thousands of credible variants, ∼98% of which lie within poorly characterized non-coding regions. To functionally validate their regulatory effects, we performed a massively parallel reporter assay (MPRA) on 5,173 finemapped schizophrenia GWAS variants in primary human neural progenitors (HNPs). We identified 439 variants with allelic regulatory effects (MPRA-positive variants), with 71% of GWAS loci containing at least one MPRA-positive variant. Transcription factor binding had modest predictive power for predicting the allelic activity of MPRA-positive variants, while GWAS association, finemap posterior probability, enhancer overlap, and evolutionary conservation failed to predict MPRA-positive variants. Furthermore, 64% of MPRA-positive variants did not exhibit eQTL signature, suggesting that MPRA could identify yet unexplored variants with regulatory potentials. MPRA-positive variants differed from eQTLs, as they were more frequently located in distal neuronal enhancers. Therefore, we leveraged neuronal 3D chromatin architecture to identify 272 genes that physically interact with MPRA-positive variants. These genes annotated by chromatin interactome displayed higher mutational constraints and regulatory complexity than genes annotated by eQTLs, recapitulating a recent finding that eQTL- and GWAS-detected variants map to genes with different properties. Finally, we propose a model in which allelic activity of multiple variants within a GWAS locus can be aggregated to predict gene expression by taking chromatin contact frequency and accessibility into account. In conclusion, we demonstrate that MPRA can effectively identify functional regulatory variants and delineate previously unknown regulatory principles of schizophrenia.

Massively parallel characterization of psychiatric disorder-associated and cell-type-specific regulatory elements in the developing human cortex

“…We evaluated the regulatory effect of 17,069 brain QTLs and psychiatric disorder associated variants, identifying 164 differentially active variants. This small number is in line with other MPRAs that tested the effect of single-nucleotide variants ( 14 , 51 , 53 , 83 , 84 ) observing relatively small effects of single nucleotide substitutions, especially common alleles, on regulatory activity. Our deep learning model supports this conclusion; it predicts that many nucleotide changes in the open chromatin regions we tested, including alleles never or rarely seen in people, would show greater differential activity than the brain QTLs did.…”

Practical application of massively parallel reporter assay in biotechnology and medicine

“…Вместе с тем анализ eQTL и МПРА являются, скорее, взаимодополняющими, поскольку МПРА, по всей вероятности, позволяет идентифицировать редкие функциональные регуляторные полиморфизмы, определение которых в анализе eQTL зачас тую невозможно ввиду ограничений чувствительности метода [159]. В свою очередь МПРА также может давать несколько искаженную картину, поскольку экспериментальная проверка проводится in vitro в доступных клеточных культурах, далеко не всегда воспроизводящих физиологию клеток, задействованных в патогенезе заболевания, а также в основном сфокусирован на исследовании функции энхансеров [159].…”

“…Совпадение результатов МПРА и eQTL имеет место приблизительно в 1/3 случаев, что, однако, вселяет надежду на высокую прогностической ценность МПРА-позитивных eQTL локусов [159]. МПРА также дополняет исследования методом GWAS, поскольку, в отличие от него, позволяет сравнивать регуляторный эффект индивидуальных мутаций, давая возможность находить наиболее значимые полиморфизмы среди множества близкорасположенных сцепленных вариантов (рис.…”

The interaction between enhancer variants and environmental factors as an overlooked aetiological paradigm in human complex disease

“…[27][28][29][30][31] However, more global assays interrogating the overall functional and medical relevance of GWAS SNPs or the enhancers in which they are located suggest that only a minor fraction (<10%) of disease-associated variants might have an impact on gene expression. [16,32,33] Therefore, despite major efforts and technological advances, our understanding of the genetic basis of complex human diseases in general and of the aetiological significance of non-coding variants in particular remains incomplete. Furthermore, human complex disorders are not simply caused by particular combinations of genetic variants but also by environmental risk factors (e.g., diet, pollution, smoking, ageing, etc.).…”