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Nature Genetics Jun 2024Genotype × environment interactions (GxE) have long been recognized as a key mechanism underlying human phenotypic variation. Technological developments over the... (Review)
Review
Genotype × environment interactions (GxE) have long been recognized as a key mechanism underlying human phenotypic variation. Technological developments over the past 15 years have dramatically expanded our appreciation of the role of GxE in both gene regulation and complex traits. The richness and complexity of these datasets also required parallel efforts to develop robust and sensitive statistical and computational approaches. Although our understanding of the genetic architecture of molecular and complex traits has been maturing, a large proportion of complex trait heritability remains unexplained. Furthermore, there are increasing efforts to characterize the effect of environmental exposure on human health. We therefore review GxE in human gene regulation and complex traits, advocating for a comprehensive approach that jointly considers genetic and environmental factors in human health and disease.
Topics: Humans; Gene-Environment Interaction; Genotype; Gene Expression Regulation; Multifactorial Inheritance; Phenotype; Quantitative Trait Loci
PubMed: 38858456
DOI: 10.1038/s41588-024-01776-w -
Psychiatry Research Aug 2024Given that anxiety disorders (AD) are associated with reduced vagally-mediated heart rate variability (HRV), genetic variants related to HRV may provide insight into...
Given that anxiety disorders (AD) are associated with reduced vagally-mediated heart rate variability (HRV), genetic variants related to HRV may provide insight into anxiety etiology. This study used polygenic risk scores (PRS) to explore the genetic overlap between AD and HRV, and investigated whether HRV-related polymorphisms influence anxiety risk. Resting vagally-mediated HRV was measured using a wearable device in 188 European individuals (AD=101, healthy controls=87). AD PRS was tested for association with resting HRV, and HRV PRS for association with AD. We also investigated 15 significant hits from an HRV genome-wide association study (GWAS) for association with resting HRV and AD and if this association is mediated through resting HRV. The AD PRS and HRV PRS showed nominally significant associations with resting HRV and anxiety disorders, respectively. HRV GWAS variants associated with resting HRV were rs12980262 (NDUFA11), rs2680344 (HCN4), rs4262 and rs180238 (GNG11), and rs10842383 (LINC00477). Mediation analyses revealed that NDUFA11 rs12980262 A-carriers and GNG11 rs180238 and rs4262 C-carriers had higher anxiety risk through lower HRV. This study supports an anxiety-HRV genetic relationship, with HRV-related genetic variants translating to AD. This study encourages exploration of HRV genetics to understand mechanisms and identify novel treatment targets for anxiety.
Topics: Humans; Male; Female; Adult; Anxiety Disorders; Heart Rate; Multifactorial Inheritance; Genome-Wide Association Study; Polymorphism, Single Nucleotide; Middle Aged; Young Adult; Biomarkers; Genetic Predisposition to Disease
PubMed: 38850888
DOI: 10.1016/j.psychres.2024.115982 -
BMC Oral Health Jun 2024Individuals born with cleft lip and/or palate who receive corrective surgery regularly have abnormal growth in the midface region such that they exhibit premaxillary...
BACKGROUND
Individuals born with cleft lip and/or palate who receive corrective surgery regularly have abnormal growth in the midface region such that they exhibit premaxillary hypoplasia. However, there are also genetic contributions to craniofacial morphology in the midface region, so although these individuals appear to have Class III skeletal discrepancy, their molar relationship may be Class I. Past genome-wide association studies (GWASs) on skeletal Class II and III malocclusion suggested that multiple genetic markers contribute to these phenotypes via a multifactorial inheritance model, but research has yet to examine the genetic markers associated with dental Class I malocclusion. Thus, our goal was to conduct a family based GWAS to identify genes across the genome that are associated with Class I malocclusion, as defined by molar relations, in humans with and without clefts.
METHODS
Our cohort consisted of 739 individuals from 47 Filipino families originally recruited in 2006 to investigate the genetic basis of orofacial clefts. All individuals supplied blood samples for DNA extraction and genotyping, and a 5,766 single nucleotide polymorphism (SNP) custom panel was used for the analyses. We performed a transmission disequilibrium test for participants with and without clefts to identify genetic contributors potentially involved with Class I malocclusion.
RESULTS
In the total cohort, 13 SNPs had associations that reached the genomic control threshold (p < 0.005), while five SNPs were associated with Class I in the cohort of participants without clefts, including four associations that were identified in the total cohort. The associations for the SNPs ABCA4 rs952499, SOX1-OT rs726455, and RORA rs877228 are of particular interest, as past research found associations between these genes and various craniofacial phenotypes, including cleft lip and/or palate.
CONCLUSIONS
These findings support the multifactorial inheritance model for dental Class I malocclusion and suggest a common genetic basis for different aspects of craniofacial development.
Topics: Humans; Cleft Lip; Cleft Palate; Genome-Wide Association Study; Polymorphism, Single Nucleotide; Female; Male; Malocclusion, Angle Class I; Cohort Studies; Linkage Disequilibrium; Child; Genotype; Adolescent; Genetic Markers; Adult; Phenotype; Multifactorial Inheritance; Young Adult
PubMed: 38849772
DOI: 10.1186/s12903-024-04444-x -
Nature Communications Jun 2024Coronary artery disease (CAD) is the leading cause of death among adults worldwide. Accurate risk stratification can support optimal lifetime prevention. Current methods...
Coronary artery disease (CAD) is the leading cause of death among adults worldwide. Accurate risk stratification can support optimal lifetime prevention. Current methods lack the ability to incorporate new information throughout the life course or to combine innate genetic risk factors with acquired lifetime risk. We designed a general multistate model (MSGene) to estimate age-specific transitions across 10 cardiometabolic states, dependent on clinical covariates and a CAD polygenic risk score. This model is designed to handle longitudinal data over the lifetime to address this unmet need and support clinical decision-making. We analyze longitudinal data from 480,638 UK Biobank participants and compared predicted lifetime risk with the 30-year Framingham risk score. MSGene improves discrimination (C-index 0.71 vs 0.66), age of high-risk detection (C-index 0.73 vs 0.52), and overall prediction (RMSE 1.1% vs 10.9%), in held-out data. We also use MSGene to refine estimates of lifetime absolute risk reduction from statin initiation. Our findings underscore our multistate model's potential public health value for accurate lifetime CAD risk estimation using clinical factors and increasingly available genetics toward earlier more effective prevention.
Topics: Humans; Coronary Artery Disease; Male; Female; Middle Aged; Electronic Health Records; Aged; Risk Assessment; Risk Factors; Adult; Genetic Predisposition to Disease; Hydroxymethylglutaryl-CoA Reductase Inhibitors; United Kingdom; Longitudinal Studies; Multifactorial Inheritance
PubMed: 38849421
DOI: 10.1038/s41467-024-49296-9 -
Scientific Reports Jun 2024Speech-in-noise (SIN) perception is a primary complaint of individuals with audiometric hearing loss. SIN performance varies drastically, even among individuals with...
Speech-in-noise (SIN) perception is a primary complaint of individuals with audiometric hearing loss. SIN performance varies drastically, even among individuals with normal hearing. The present genome-wide association study (GWAS) investigated the genetic basis of SIN deficits in individuals with self-reported normal hearing in quiet situations. GWAS was performed on 279,911 individuals from the UB Biobank cohort, with 58,847 reporting SIN deficits despite reporting normal hearing in quiet. GWAS identified 996 single nucleotide polymorphisms (SNPs), achieving significance (p < 5*10) across four genomic loci. 720 SNPs across 21 loci achieved suggestive significance (p < 10). GWAS signals were enriched in brain tissues, such as the anterior cingulate cortex, dorsolateral prefrontal cortex, entorhinal cortex, frontal cortex, hippocampus, and inferior temporal cortex. Cochlear cell types revealed no significant association with SIN deficits. SIN deficits were associated with various health traits, including neuropsychiatric, sensory, cognitive, metabolic, cardiovascular, and inflammatory conditions. A replication analysis was conducted on 242 healthy young adults. Self-reported speech perception, hearing thresholds (0.25-16 kHz), and distortion product otoacoustic emissions (1-16 kHz) were utilized for the replication analysis. 73 SNPs were replicated with a self-reported speech perception measure. 211 SNPs were replicated with at least one and 66 with at least two audiological measures. 12 SNPs near or within MAPT, GRM3, and HLA-DQA1 were replicated for all audiological measures. The present study highlighted a polygenic architecture underlying SIN deficits in individuals with self-reported normal hearing.
Topics: Humans; Genome-Wide Association Study; Polymorphism, Single Nucleotide; Male; Female; Speech Perception; Multifactorial Inheritance; Adult; Noise; Middle Aged; Self Report; Aged; Hearing; Young Adult
PubMed: 38849415
DOI: 10.1038/s41598-024-63972-2 -
Nature Communications Jun 2024Evidence for adaptation of human skin color to regional ultraviolet radiation suggests shared and distinct genetic variants across populations. However, skin color...
Evidence for adaptation of human skin color to regional ultraviolet radiation suggests shared and distinct genetic variants across populations. However, skin color evolution and genetics in East Asians are understudied. We quantified skin color in 48,433 East Asians using image analysis and identified associated genetic variants and potential causal genes for skin color as well as their polygenic interplay with sun exposure. This genome-wide association study (GWAS) identified 12 known and 11 previously unreported loci and SNP-based heritability was 23-24%. Potential causal genes were determined through the identification of nonsynonymous variants, colocalization with gene expression in skin tissues, and expression levels in melanocytes. Genomic loci associated with pigmentation in East Asians substantially diverged from European populations, and we detected signatures of polygenic adaptation. This large GWAS for objectively quantified skin color in an East Asian population improves understanding of the genetic architecture and polygenic adaptation of skin color and prioritizes potential causal genes.
Topics: Adult; Female; Humans; Male; Middle Aged; Adaptation, Physiological; Chromosome Mapping; Genome-Wide Association Study; Multifactorial Inheritance; Polymorphism, Single Nucleotide; Quantitative Trait Loci; Skin Pigmentation; Ultraviolet Rays; East Asian People
PubMed: 38849341
DOI: 10.1038/s41467-024-49031-4 -
Scientific Reports Jun 2024The risk of developing age-related macular degeneration (AMD) is influenced by genetic background. In 2016, the International AMD Genomics Consortium (IAMDGC)...
The risk of developing age-related macular degeneration (AMD) is influenced by genetic background. In 2016, the International AMD Genomics Consortium (IAMDGC) identified 52 risk variants in 34 loci, and a polygenic risk score (PRS) from these variants was associated with AMD. The Israeli population has a unique genetic composition: Ashkenazi Jewish (AJ), Jewish non-Ashkenazi, and Arab sub-populations. We aimed to perform a genome-wide association study (GWAS) for AMD in Israel, and to evaluate PRSs for AMD. Our discovery set recruited 403 AMD patients and 256 controls at Hadassah Medical Center. We genotyped individuals via custom exome chip. We imputed non-typed variants using cosmopolitan and AJ reference panels. We recruited additional 155 cases and 69 controls for validation. To evaluate predictive power of PRSs for AMD, we used IAMDGC summary-statistics excluding our study and developed PRSs via clumping/thresholding or LDpred2. In our discovery set, 31/34 loci reported by IAMDGC were AMD-associated (P < 0.05). Of those, all effects were directionally consistent with IAMDGC and 11 loci had a P-value under Bonferroni-corrected threshold (0.05/34 = 0.0015). At a 5 × 10 threshold, we discovered four suggestive associations in FAM189A1, IGDCC4, C7orf50, and CNTNAP4. Only the FAM189A1 variant was AMD-associated in the replication cohort after Bonferroni-correction. A prediction model including LDpred2-based PRS + covariates had an AUC of 0.82 (95% CI 0.79-0.85) and performed better than covariates-only model (P = 5.1 × 10). Therefore, previously reported AMD-associated loci were nominally associated with AMD in Israel. A PRS developed based on a large international study is predictive in Israeli populations.
Topics: Humans; Macular Degeneration; Israel; Genome-Wide Association Study; Female; Male; Genetic Predisposition to Disease; Aged; Polymorphism, Single Nucleotide; Risk Factors; Middle Aged; Case-Control Studies; Aged, 80 and over; Multifactorial Inheritance; Jews; Genotype
PubMed: 38844476
DOI: 10.1038/s41598-024-63065-0 -
Neurology Jun 2024The World Health Organization recently released a novel metric for healthy aging: intrinsic capacity (IC). The relationship between IC and the incidence of dementia, and...
BACKGROUND AND OBJECTIVES
The World Health Organization recently released a novel metric for healthy aging: intrinsic capacity (IC). The relationship between IC and the incidence of dementia, and its subtypes, is unknown. We aimed to analyze the relationship between IC and the incidence of dementia and its subtypes. Moreover, we tested whether genetic susceptibility to dementia could be modified by IC.
METHODS
This cohort study involved 366,406 participants from the UK Biobank between 2006 and 2010. We analyzed 7 factors that reflected functional status across 4 IC domains to compute a comprehensive IC deficit score. Cox models were used to elucidate the relationship between the IC deficit score and the incidence of dementia.
RESULTS
Among the 366,406 participants, 5,207 cases of dementia were documented, encompassing 2,186 and 1,175 cases of Alzheimer disease (AD) and vascular dementia (VD), respectively. Compared with participants with an IC score of 0, individuals with an IC score of 4+ had a markedly elevated risk of dementia (hazard ratio [HR] 2.17, 95% CI 1.92-2.45). In the joint analysis, for participants with a high polygenic risk score (PRS) and an IC score of 4 or more, the HR of all-cause dementia was 8.11 (95% CI 6.28-10.47) compared with individuals with a low PRS and an IC score of 0. Similar results were seen in the AD and VD groups.
DISCUSSION
In summary, IC is associated with a higher risk of dementia, particularly in those combined with genetically predisposed to dementia.
Topics: Humans; Female; Male; United Kingdom; Aged; Apolipoproteins E; Biological Specimen Banks; Multifactorial Inheritance; Middle Aged; Dementia; Prospective Studies; Genotype; Genetic Predisposition to Disease; Alzheimer Disease; Cohort Studies; Incidence; Risk Factors; Healthy Aging; Dementia, Vascular; Genetic Risk Score; UK Biobank
PubMed: 38843484
DOI: 10.1212/WNL.0000000000209452 -
Briefings in Bioinformatics May 2024In precision medicine, both predicting the disease susceptibility of an individual and forecasting its disease-free survival are areas of key research. Besides the...
In precision medicine, both predicting the disease susceptibility of an individual and forecasting its disease-free survival are areas of key research. Besides the classical epidemiological predictor variables, data from multiple (omic) platforms are increasingly available. To integrate this wealth of information, we propose new methodology to combine both cooperative learning, a recent approach to leverage the predictive power of several datasets, and polygenic hazard score models. Polygenic hazard score models provide a practitioner with a more differentiated view of the predicted disease-free survival than the one given by merely a point estimate, for instance computed with a polygenic risk score. Our aim is to leverage the advantages of cooperative learning for the computation of polygenic hazard score models via Cox's proportional hazard model, thereby improving the prediction of the disease-free survival. In our experimental study, we apply our methodology to forecast the disease-free survival for Alzheimer's disease (AD) using three layers of data. One layer contains epidemiological variables such as sex, APOE (apolipoprotein E, a genetic risk factor for AD) status and 10 leading principal components. Another layer contains selected genomic loci, and the last layer contains methylation data for selected CpG sites. We demonstrate that the survival curves computed via cooperative learning yield an AUC of around $0.7$, above the state-of-the-art performance of its competitors. Importantly, the proposed methodology returns (1) a linear score that can be easily interpreted (in contrast to machine learning approaches), and (2) a weighting of the predictive power of the involved data layers, allowing for an assessment of the importance of each omic (or other) platform. Similarly to polygenic hazard score models, our methodology also allows one to compute individual survival curves for each patient.
Topics: Humans; Precision Medicine; Alzheimer Disease; Disease-Free Survival; Machine Learning; Proportional Hazards Models; Multifactorial Inheritance; Male; Female; Multiomics
PubMed: 38836403
DOI: 10.1093/bib/bbae267 -
Nature Genetics Jun 2024While genome-wide association studies are increasingly successful in discovering genomic loci associated with complex human traits and disorders, the biological...
While genome-wide association studies are increasingly successful in discovering genomic loci associated with complex human traits and disorders, the biological interpretation of these findings remains challenging. Here we developed the GSA-MiXeR analytical tool for gene set analysis (GSA), which fits a model for the heritability of individual genes, accounting for linkage disequilibrium across variants and allowing the quantification of partitioned heritability and fold enrichment for small gene sets. We validated the method using extensive simulations and sensitivity analyses. When applied to a diverse selection of complex traits and disorders, including schizophrenia, GSA-MiXeR prioritizes gene sets with greater biological specificity compared to standard GSA approaches, implicating voltage-gated calcium channel function and dopaminergic signaling for schizophrenia. Such biologically relevant gene sets, often with fewer than ten genes, are more likely to provide insights into the pathobiology of complex diseases and highlight potential drug targets.
Topics: Humans; Genome-Wide Association Study; Schizophrenia; Linkage Disequilibrium; Multifactorial Inheritance; Models, Genetic; Polymorphism, Single Nucleotide; Quantitative Trait Loci; Genetic Predisposition to Disease; Chromosome Mapping; Computer Simulation; Quantitative Trait, Heritable
PubMed: 38831010
DOI: 10.1038/s41588-024-01771-1