Crosstalk of Genetic Variants, Allele-Specific DNA Methylation, and Environmental Factors for Complex Disease Risk

AbstractBackgroundEpigenetic processes, including DNA methylation (DNAm), are among the mechanisms allowing integration of genetic and environmental factors to shape cellular function. While many studies have investigated either environmental or genetic contributions to DNAm, few have assessed their integrated effects. We examined the relative contributions of prenatal environmental factors and genotype on DNA methylation in neonatal blood at variably methylated regions (VMRs), defined as consecutive CpGs showing the highest variability of DNAm in 4 independent cohorts (PREDO, DCHS, UCI, MoBa, N=2,934).ResultsWe used Akaike’s information criterion to test which factors best explained variability of methylation in the cohort-specific VMRs: several prenatal environmental factors (E) including maternal demographic, psychosocial and metabolism related phenotypes, genotypes in cis (G), or their additive (G+E) or interaction (GxE) effects. G+E and GxE models consistently best explained variability in DNAm of VMRs across the cohorts, with G explaining the remaining sites best. VMRs best explained by G, GxE or G+E, as well as their associated functional genetic variants (predicted using deep learning algorithms), were located in distinct genomic regions, with different enrichments for transcription and enhancer marks. Genetic variants of not only G and G+E models, but also of variants in GxE models were significantly enriched in genome wide association studies (GWAS) for complex disorders.ConclusionGenetic and environmental factors in combination best explain DNAm at VMRs. The CpGs best explained by G, G+E or GxE are functionally distinct. The enrichment of GxE variants in GWAS for complex disorders supports their importance for disease risk.

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Allele-Specific Methylation Occurs at Genetic Variants Associated with Complex Disease

PLoS ONE ◽

10.1371/journal.pone.0098464 ◽

2014 ◽

Vol 9 (6) ◽

pp. e98464 ◽

Cited By ~ 27

Author(s):

John N. Hutchinson ◽

Towfique Raj ◽

Jes Fagerness ◽

Eli Stahl ◽

Fernando T. Viloria ◽

...

Keyword(s):

Genetic Variants ◽

Complex Disease ◽

Allele Specific ◽

Allele Specific Methylation

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Systematic Mendelian randomization framework elucidates hundreds of genetic loci which may influence disease through changes in DNA methylation levels

10.1101/189076 ◽

2017 ◽

Cited By ~ 3

Author(s):

Tom G. Richardson ◽

Philip C. Haycock ◽

Jie Zheng ◽

Nicholas J. Timpson ◽

Tom R. Gaunt ◽

...

Keyword(s):

Dna Methylation ◽

Quantitative Trait Loci ◽

Genetic Variants ◽

Quantitative Trait ◽

Complex Traits ◽

Complex Disease ◽

Mendelian Randomization ◽

High Rate ◽

Trait Variation ◽

Trait Loci

AbstractWe have undertaken an extensive Mendelian randomization (MR) study using methylation quantitative trait loci (mQTL) as genetic instruments to assess the potential causal relationship between genetic variation, DNA methylation and 139 complex traits. Using two-sample MR, we observed 1,191 effects across 62 traits where genetic variants were associated with both proximal DNA methylation (i.e. cis-mQTL) and complex trait variation (P<1.39x10−08). Joint likelihood mapping provided evidence that the causal mQTL for 364 of these effects across 58 traits was also likely the causal variant for trait variation. These effects showed a high rate of replication in the UK Biobank dataset for 14 selected traits, as 121 of the attempted 129 effects replicated. Integrating expression quantitative trait loci (eQTL) data suggested that genetic variants responsible for 319 of the 364 mQTL effects also influence gene expression, which indicates a coordinated system of effects that are consistent with causality. CpG sites were enriched for histone mark peaks in tissue types relevant to their associated trait and implicated genes were enriched across relevant biological pathways. Though we are unable to distinguish mediation from horizontal pleiotropy in these analyses, our findings should prove valuable in identifying candidate loci for further evaluation and help develop mechanistic insight into the aetiology of complex disease.

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Allele-specific open chromatin in human iPSC neurons elucidates functional disease variants

Science ◽

10.1126/science.aay3983 ◽

2020 ◽

Vol 369 (6503) ◽

pp. 561-565 ◽

Cited By ~ 6

Author(s):

Siwei Zhang ◽

Hanwen Zhang ◽

Yifan Zhou ◽

Min Qiao ◽

Siming Zhao ◽

...

Keyword(s):

Genetic Variants ◽

Target Genes ◽

Disease Risk ◽

Induced Pluripotent Stem Cell ◽

Open Chromatin ◽

Regulatory Sequences ◽

Functional Interpretation ◽

Neuropsychiatric Disease ◽

Risk Variants ◽

Allele Specific

Most neuropsychiatric disease risk variants are in noncoding sequences and lack functional interpretation. Because regulatory sequences often reside in open chromatin, we reasoned that neuropsychiatric disease risk variants may affect chromatin accessibility during neurodevelopment. Using human induced pluripotent stem cell (iPSC)–derived neurons that model developing brains, we identified thousands of genetic variants exhibiting allele-specific open chromatin (ASoC). These neuronal ASoCs were partially driven by altered transcription factor binding, overrepresented in brain gene enhancers and expression quantitative trait loci, and frequently associated with distal genes through chromatin contacts. ASoCs were enriched for genetic variants associated with brain disorders, enabling identification of functional schizophrenia risk variants and their cis-target genes. This study highlights ASoC as a functional mechanism of noncoding neuropsychiatric risk variants, providing a powerful framework for identifying disease causal variants and genes.

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Determination of chemical-disease risk values to prioritize connections between environmental factors, genetic variants, and human diseases

Toxicology and Applied Pharmacology ◽

10.1016/j.taap.2019.114674 ◽

2019 ◽

Vol 379 ◽

pp. 114674

Author(s):

Marissa B. Kosnik ◽

David M. Reif

Keyword(s):

Environmental Factors ◽

Genetic Variants ◽

Disease Risk ◽

Human Diseases

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In Search of Complex Disease Risk through Genome Wide Association Studies

Mathematics ◽

10.3390/math9233083 ◽

2021 ◽

Vol 9 (23) ◽

pp. 3083

Author(s):

Lorena Alonso ◽

Ignasi Morán ◽

Cecilia Salvoro ◽

David Torrents

Keyword(s):

Genetic Variants ◽

Complex Disease ◽

Disease Risk ◽

Association Studies ◽

Personalised Medicine ◽

Genome Wide Association ◽

Phenotypic Traits ◽

Genome Wide Association Studies ◽

Treatment Protocols ◽

Genome Wide

The identification and characterisation of genomic changes (variants) that can lead to human diseases is one of the central aims of biomedical research. The generation of catalogues of genetic variants that have an impact on specific diseases is the basis of Personalised Medicine, where diagnoses and treatment protocols are selected according to each patient’s profile. In this context, the study of complex diseases, such as Type 2 diabetes or cardiovascular alterations, is fundamental. However, these diseases result from the combination of multiple genetic and environmental factors, which makes the discovery of causal variants particularly challenging at a statistical and computational level. Genome-Wide Association Studies (GWAS), which are based on the statistical analysis of genetic variant frequencies across non-diseased and diseased individuals, have been successful in finding genetic variants that are associated to specific diseases or phenotypic traits. But GWAS methodology is limited when considering important genetic aspects of the disease and has not yet resulted in meaningful translation to clinical practice. This review presents an outlook on the study of the link between genetics and complex phenotypes. We first present an overview of the past and current statistical methods used in the field. Next, we discuss current practices and their main limitations. Finally, we describe the open challenges that remain and that might benefit greatly from further mathematical developments.

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Genetic Epidemiology in Latin America: Identifying Strong Genetic Proxies for Complex Disease Risk Factors

Genes ◽

10.3390/genes11050507 ◽

2020 ◽

Vol 11 (5) ◽

pp. 507

Author(s):

Carolina Bonilla ◽

Lara Novaes Baccarini

Keyword(s):

Latin America ◽

Genetic Variants ◽

Complex Disease ◽

Disease Risk ◽

Association Studies ◽

Strong Association ◽

Genome Wide Association Studies ◽

Reverse Causation ◽

Health And Wellbeing ◽

Genome Wide

Epidemiology seeks to determine the causal effects of exposures on outcomes related to the health and wellbeing of populations. Observational studies, one of the most commonly used designs in epidemiology, can be biased due to confounding and reverse causation, which makes it difficult to establish causal relationships. In recent times, genetically informed methods, like Mendelian randomization (MR), have been developed in an attempt to overcome these disadvantages. MR relies on the association of genetic variants with outcomes of interest, where the genetic variants are proxies or instruments for modifiable exposures. Because genotypes are sorted independently and at random at the time of conception, they are less prone to confounding and reverse causation. Implementation of MR depends on, among other things, a strong association of the genetic variants with the exposure, which has usually been defined via genome-wide association studies (GWAS). Because GWAS have been most often carried out in European populations, the limited identification of strong instruments in other populations poses a major problem for the application of MR in Latin America. We suggest potential solutions that can be realized with the resources at hand and others that will have to wait for increased funding and access to technology.

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Genetic and Risk factors in Dry-Form (Non-Neovascular) Age-Related Macular Degeneration

Güncel Retina Dergisi (Current Retina Journal) ◽

10.37783/crj-0017 ◽

2017 ◽

pp. 100-104

Keyword(s):

Risk Factors ◽

Environmental Factors ◽

Macular Degeneration ◽

Genetic Variants ◽

Genetic Risk ◽

Older Persons ◽

Complex Disease ◽

Age Related Macular Degeneration ◽

Genetic Studies ◽

Age Related

Age-related macular degeneration (AMD) is the leading cause of severe visual impairment in older persons. AMD is a multifactorial complex disease that both genetic and many environmental factors play roles in its etiopathogenesis. In recent years, advances in genetic studies have led to the detection of many genetic variants that play a role in the pathogenesis of AMD. This review summarized the environmental and genetic risk factors of AMD.

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Schizophrenia-associated differential DNA methylation in the superior temporal gyrus is distributed to many sites across the genome and annotated by the risk gene MAD1L1

10.1101/2020.08.02.20166777 ◽

2020 ◽

Author(s):

Brandon C McKinney ◽

Christopher M Hensler ◽

Yue Wei ◽

David A Lewis ◽

Jiebiao Wang ◽

...

Keyword(s):

Dna Methylation ◽

Environmental Factors ◽

Genetic Variants ◽

Association Studies ◽

Superior Temporal Gyrus ◽

Differential Methylation ◽

Composition Analysis ◽

Genome Wide Association Studies ◽

Genome Wide ◽

The Individual

Background: Many genetic variants and multiple environmental factors increase risk for schizophrenia (SZ). SZ-associated genetic variants and environmental risk factors have been associated with altered DNA methylation (DNAm), the addition of a methyl group to a cytosine in DNA. DNAm changes, acting through effects on gene expression, represent one potential mechanism by which genetic and environmental factors confer risk for SZ and alter neurobiology. Methods: We investigated the hypothesis that DNAm in superior temporal gyrus (STG) is altered in SZ. We measured genome-wide DNAm in postmortem STG from 44 SZ subjects and 44 non-psychiatric comparison (NPC) subjects using Illumina Infinium MethylationEPIC BeadChip microarrays. We applied tensor composition analysis to extract cell type-specific DNAm signals. Results: We found that DNAm levels differed between SZ and NPC subjects at 242 sites, and 44 regions comprised of two or more sites, with a false discovery rate cutoff of q=0.1. We determined differential methylation at nine of the individual sites were driven by neuron-specific DNAm alterations. Glia-specific DNAm alterations drove the differences at two sites. Notably, we identied SZ-associated differential methylation within within mitotic arrest deficient 1-like 1 (MAD1L1), a gene strongly associated with SZ through genome-wide association studies. Conclusions: This study adds to a growing number of studies that implicate DNAm, and epigenetic pathways more generally, in SZ. Our findings suggest differential methylation may contribute to STG dysfunction in SZ. Future studies to identify the mechanisms by which altered DNAm, especially within MAD1L1, contributes to SZ neurobiology are warranted.

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