Functional Analysis of Promoter Variants in Genes Involved in Sex Steroid Action, DNA Repair and Cell Cycle Control

The landscape of GWAS validation; systematic review identifying 309 validated non-coding variants across 130 human diseases

Background

The remarkable growth of genome-wide association studies (GWAS) has created a critical need to experimentally validate the disease-associated variants, 90% of which involve non-coding variants.

Methods

To determine how the field is addressing this urgent need, we performed a comprehensive literature review identifying 36,676 articles. These were reduced to 1454 articles through a set of filters using natural language processing and ontology-based text-mining. This was followed by manual curation and cross-referencing against the GWAS catalog, yielding a final set of 286 articles.

Results

We identified 309 experimentally validated non-coding GWAS variants, regulating 252 genes across 130 human disease traits. These variants covered a variety of regulatory mechanisms. Interestingly, 70% (215/309) acted through cis-regulatory elements, with the remaining through promoters (22%, 70/309) or non-coding RNAs (8%, 24/309). Several validation approaches were utilized in these studies, including gene expression (n = 272), transcription factor binding (n = 175), reporter assays (n = 171), in vivo models (n = 104), genome editing (n = 96) and chromatin interaction (n = 33).

Conclusions

This review of the literature is the first to systematically evaluate the status and the landscape of experimentation being used to validate non-coding GWAS-identified variants. Our results clearly underscore the multifaceted approach needed for experimental validation, have practical implications on variant prioritization and considerations of target gene nomination. While the field has a long way to go to validate the thousands of GWAS associations, we show that progress is being made and provide exemplars of validation studies covering a wide variety of mechanisms, target genes, and disease areas.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12920-022-01216-w.

Significance of the lncRNAs MALAT1 and ANRIL in occurrence and development of glaucoma

Background

Primary open‐angle glaucoma (POAG) is the commonest form of glaucoma which is estimated to cause bilaterally blind within 11.1 million people by 2020. Therefore, the primary objectives of this study were to investigate the clinical significance of single‐nucleotide polymorphisms (SNPs) in the lncRNAs MALAT1 and ANRIL in a Chinese Han POAG cohort.

Methods

Three hundred and forty‐six glaucoma patients and 263 healthy controls were recruited, and totally 14 SNPs in MALAT1 and ANRIL were genotyped between the two populations.

Results

The MALAT1 SNPs rs619586 (A>G), rs3200401 (C>T), and rs664589 (C>G) were associated with POAG risk, and the ANRIL SNPs rs2383207 (A>G), rs564398 (A>G), rs2157719 (A>G), rs7865618 (G>A), and rs4977574 (A>G) were associated with POAG (p < 0.05). The MALAT1 haplotypes ACG and ATC, comprised rs619586, rs3200401, and rs664589, increased POAG risk, and the ANRIL haplotype AAGAA, made up of rs2383207, rs7865618, rs4977574, rs564398, and rs2157719, show a significantly increased risk of POAG. In addition, rs619586 (A>G) of MALAT1 and rs564398/rs2157719 of ANRIL were associated with a smaller vertical cup‐to‐disc ratio, while rs619586 of MALAT1 and rs2383207/rs4977574 of ANRIL were associated with higher intraocular pressure in the POAG population.

Conclusion

Single‐nucleotide polymorphisms and haplotypes in ANRIL and MALAT1 were associated with POAG onset in our study population, which provide more possibilities to POAG diagnosis and treatment.

Residential PM2.5 exposure and the nasal methylome in children

RATIONALE

PM_2.5-induced adverse effects on respiratory health may be driven by epigenetic modifications in airway cells. The potential impact of exposure duration on epigenetic alterations in the airways is not yet known.

OBJECTIVES

We aimed to study associations of fine particulate matter PM_2.5 exposure with DNA methylation in nasal cells.

METHODS

We conducted nasal epigenome-wide association analyses within 503 children from Project Viva (mean age 12.9 y), and examined various exposure durations (1-day, 1-week, 1-month, 3-months and 1-year) prior to nasal sampling. We used residential addresses to estimate average daily PM_2.5 at 1 km resolution. We collected nasal swabs from the anterior nares and measured DNA methylation (DNAm) using the Illumina MethylationEPIC BeadChip. We tested 719,075 high quality autosomal CpGs using CpG-by-CpG and regional DNAm analyses controlling for multiple comparisons, and adjusted for maternal education, household smokers, child sex, race/ethnicity, BMI z-score, age, season at sample collection and cell-type heterogeneity. We further corrected for bias and genomic inflation. We tested for replication in a cohort from the Netherlands (PIAMA).

RESULTS

In adjusted analyses, we found 362 CpGs associated with 1-year PM_2.5 (FDR < 0.05), 20 CpGs passing Bonferroni correction (P < 7.0x10^-8) and 10 Differentially Methylated Regions (DMRs). In 445 PIAMA participants (mean age 16.3 years) 11 of 203 available CpGs replicated at P < 0.05. We observed differential DNAm at/near genes implicated in cell cycle, immune and inflammatory responses. There were no CpGs or regions associated with PM_2.5 levels at 1-day, 1-week, or 1-month prior to sample collection, although 2 CpGs were associated with past 3-month PM_2.5.

CONCLUSION

We observed wide-spread DNAm variability associated with average past year PM_2.5 exposure but we did not detect associations with shorter-term exposure. Our results suggest that nasal DNAm marks reflect chronic air pollution exposure.

DICER1-associated embryonal rhabdomyosarcoma and adenosarcoma of the gynecologic tract: Pathology, molecular genetics, and indications for molecular testing

Gynecologic sarcomas are uncommon neoplasms, the majority occurring in the uterus. Due to the diverse nature of these, the description of "new" morphological types and the rarity of some of them, pathological diagnosis and treatment is often challenging. Finding genetic alterations specific to, and frequently occurring, in a certain type can aid in the diagnosis. DICER1 is a highly conserved ribonuclease crucial in the biogenesis of microRNAs and mutations in DICER1 (either somatic or germline) have been detected in a wide range of sarcomas including genitourinary embryonal rhabdomyosarcomas (ERMS) and adenosarcomas. Importantly, DICER1-associated sarcomas share morphological features irrespective of the site of origin such that the pathologist can strongly suspect a DICER1 association. A review of the literature shows that almost all gynecologic ERMS reported (outside of the vagina) harbor DICER1 alterations, while approximately 20% of adenosarcomas also do so. These two tumor types exhibit significant morphological overlap and DICER1 tumor testing may be helpful in distinguishing between them, because a negative result makes ERMS unlikely. Given that germline pathogenic DICER1 variants are frequent in uterine (corpus and cervix) ERMS and pathogenic germline variants in this gene cause a hereditary cancer predisposition syndrome (DICER1 syndrome), patients diagnosed with these neoplasms should be referred to medical genetic services. Cooperation between pathologists and geneticists is crucial and will help in improving the diagnosis and management of these uncommon sarcomas.

Genome Dashboards: Framework and Examples

Genomics is a sequence-based informatics science and a three-dimensional-structure-based material science. However, in practice, most genomics researchers utilize sequence-based informatics approaches or three-dimensional-structure-based material science techniques, not both. This division is, at least in part, the result of historical developments rather than a fundamental necessity. The underlying computational tools, experimental techniques, and theoretical models were developed independently. The primary result presented here is a framework for the unification of informatics- and physics-based data associated with DNA, nucleosomes, and chromatin. The framework is based on the mathematical representation of geometrically exact rods and the generalization of DNA basepair step parameters. Data unification enables researchers to integrate computational, experimental, and theoretical approaches for the study of chromatin biology. The framework can be implemented using model-view-controller design principles, existing genome browsers, and existing molecular visualization tools. We developed a minimal, web-based genome dashboard, G-Dash-min, and applied it to two simple examples to demonstrate the usefulness of data unification and proof of concept. Genome dashboards developed using the framework and design principles presented here are extensible and customizable and are therefore more broadly applicable than the examples presented. We expect a number of purpose-specific genome dashboards to emerge as a novel means of investigating structure-function relationships for genomes that range from basepairs to entire chromosomes and for generating, validating, and testing mechanistic hypotheses.