Variance-components tests for genetic association with multiple interval-censored outcomes

Massive genetic compendiums such as the UK Biobank have become an invaluable resource for identifying genetic variants that are associated with complex diseases. Due to the difficulties of massive data collection, a common practice of these compendiums is to collect interval-censored data. One challenge in analyzing such data is the lack of methodology available for genetic association studies with interval-censored data. Genetic effects are difficult to detect because of their rare and weak nature, and often the time-to-event outcomes are transformed to binary phenotypes for access to more powerful signal detection approaches. However transforming the data to binary outcomes can result in loss of valuable information. To alleviate such challenges, this work develops methodology to associate genetic variant sets with multiple interval-censored outcomes. Testing sets of variants such as genes or pathways is a common approach in genetic association settings to lower the multiple testing burden, aggregate small effects, and improve interpretations of results. Instead of performing inference with only a single outcome, utilizing multiple outcomes can increase statistical power by aggregating information across multiple correlated phenotypes. Simulations show that the proposed strategy can offer significant power gains over a single outcome approach. We apply the proposed test to the investigation that motivated this study, a search for the genes that perturb risks of bone fractures and falls in the UK Biobank.

Evaluating the causal effect of atherosclerosis on the risk of intervertebral disc degeneration

Background

Intervertebral disc degeneration (IDD) and atherosclerosis are two common age-related conditions that can cause significant morbidity. While previous studies have suggested an association between the two conditions, the nature of this association remains unclear.

Methods

We used Mendelian randomization (MR) to investigate the causal relationship between IDD and atherosclerosis. We identified genetic variants associated with IDD using summary statistics from a large genome-wide association study (GWAS). These variants were then used as instrumental variables to infer causal relationships with atherosclerosis in summary statistics from a separate GWAS.

Results

Our MR analysis provided evidence for a causal relationship between IDD and atherosclerosis. We found that the genetic predisposition to atherosclerosis was associated with a higher risk of IDD (odds ratio [OR] = 3.55, 95% confidence interval [CI]: 1.07-11.74, p = 0.04). The IVW estimates were consistent with the observational findings and other robust MR methods. Sensitivity analyses suggested that our findings were robust to potential sources of bias.

Conclusions

Our study provides evidence for a causal link between IDD and atherosclerosis, suggesting that interventions targeting atherosclerosis could have potential benefits for reducing the risk of IDD. Further research is needed to explore the underlying mechanisms that link these two conditions and to investigate potential therapeutic interventions.

The non-causative role of abnormal serum uric acid in intervertebral disc degeneration: A Mendelian randomization study

Background

Intervertebral disc degeneration (IDD) is a common musculoskeletal disorder that contributes significantly to disability and healthcare costs. Serum urate concentration has been implicated in the development of various musculoskeletal conditions. While previous observational studies have suggested an association between the two conditions, it might confound the effect of serum urate concentrations on IDD. This Mendelian randomization (MR) study aimed to investigate the causal relationship between serum urate concentration and IDD.

Methods

We performed a two-sample MR analysis using summary-level data from genome-wide association studies (GWAS) of serum urate concentration (n = 13 585 994 European ancestry) and IDD (n = 16 380 337 European ancestry). Single nucleotide polymorphisms (SNPs) significantly associated with serum urate concentration (p < 5 × 10-8) were selected as instrumental variables. The associations between genetically predicted serum urate concentration and IDD were estimated using the inverse-variance weighted (IVW) method, with sensitivity analyses employing the weighted median, MR-Egger, and MR-PRESSO approaches to assess the robustness of the findings.

Results

In the primary IVW analysis, genetically predicted serum urate concentration was unrelated associated with IDD (odds ratio [OR] = 1.00, 95% confidence interval (CI): 1.00-1.00, p = 0.17)). The results remained consistent across the sensitivity analyses, and no significant directional pleiotropy was detected (MR-Egger intercept: p = 0.15).

Conclusions

This MR study provides evidence that there is no causal relationship between serum urate concentration and IDD. It suggests previous observational associations may be confounded. Serum urate levels are unlikely to be an important contributor to IDD.

Polygenic risk for Alzheimer's disease is associated with neuroaxonal damage before onset of clinical symptoms

INTRODUCTION

Establishing valid diagnostic strategies is a precondition for successful therapeutic intervention in Alzheimer's disease (AD).

METHODS

One hundred forty-four healthy 75-year-old participants from the Vienna-Transdanube-Aging longitudinal cohort study were tested for neuroaxonal damage by single molecular array (Simoa) plasma neurofilament light chain (NfL) levels at baseline, 30, 60, and 90 months, and onset of AD dementia. Individual risk for sporadic AD was estimated by continuous shrinkage polygenic risk score (PRS-CS, genome-wide association study).

RESULTS

Nineteen participants developed AD after a median of 60 months (interquartile range 30). In participants with AD, baseline NfL plasma levels correlated with PRS-CS (r = 0.75, p < 0.001; difference to controls: Fisher's r-to-z: z = 3.89, p < 0.001). PRS-CS combined with baseline plasma NfL predicted onset of AD (p < 0.01).

DISCUSSION

Our data suggest that polygenic risk for AD and plasma NfL closely interact years before onset of clinical symptoms. Peripheral NfL may serve as a diagnostic measure supporting early therapeutic intervention and secondary prevention in AD.

Chromosome 10q24.32 Variants Associate With Brain Arterial Diameters in Diverse Populations: A Genome-Wide Association Study

BACKGROUND

Brain arterial diameters (BADs) are novel imaging biomarkers of cerebrovascular disease, cognitive decline, and dementia. Traditional vascular risk factors have been associated with BADs, but whether there may be genetic determinants of BADs is unknown.

METHODS AND RESULTS

The authors studied 4150 participants from 6 geographically diverse population-based cohorts (40% European, 14% African, 22% Hispanic, 24% Asian ancestries). Brain arterial diameters for 13 segments were measured and averaged to obtain a global measure of BADs as well as the posterior and anterior circulations. A genome-wide association study revealed 14 variants at one locus associated with global BAD at genome-wide significance (P<5×10-8) (top single-nucleotide polymorphism, rs7921574; β=0.06 [P=1.54×10-8]). This locus mapped to an intron of CNNM2. A trans-ancestry genome-wide association study meta-analysis identified 2 more loci at NT5C2 (rs10748839; P=2.54×10-8) and AS3MT (rs10786721; P=4.97×10-8), associated with global BAD. In addition, 2 single-nucleotide polymorphisms colocalized with expression of CNNM2 (rs7897654; β=0.12 [P=6.17×10-7]) and AL356608.1 (rs10786719; β=-0.17 [P=6.60×10-6]) in brain tissue. For the posterior BAD, 2 variants at one locus mapped to an intron of TCF25 were identified (top single-nucleotide polymorphism, rs35994878; β=0.11 [P=2.94×10-8]). For the anterior BAD, one locus at ADAP1 was identified in trans-ancestry genome-wide association analysis (rs34217249; P=3.11×10-8).

CONCLUSIONS

The current study reveals 3 novel risk loci (CNNM2, NT5C2, and AS3MT) associated with BADs. These findings may help elucidate the mechanism by which BADs may influence cerebrovascular health.

Identification of nodulation-related genes in Medicago truncatula using genome-wide association studies and co-expression networks

Genome-wide association studies (GWAS) have proven to be a valuable approach for identifying genetic intervals associated with phenotypic variation in Medicago truncatula. These intervals can vary in size, depending on the historical local recombination. Typically, significant intervals span numerous gene models, limiting the ability to resolve high-confidence candidate genes underlying the trait of interest. Additional genomic data, including gene co-expression networks, can be combined with the genetic mapping information to successfully identify candidate genes. Co-expression network analysis provides information about the functional relationships of each gene through its similarity of expression patterns to other well-defined clusters of genes. In this study, we integrated data from GWAS and co-expression networks to pinpoint candidate genes that may be associated with nodule-related phenotypes in M. truncatula. We further investigated a subset of these genes and confirmed that several had existing evidence linking them nodulation, including MEDTR2G101090 (PEN3-like), a previously validated gene associated with nodule number.

Genetics of Atrial Fibrillation

Background

Atrial fibrillation (AF) is a common arrhythmia seen in clinical practice. Occasionally, no common risk factors are present in patients with this arrhythmia. This suggests the potential underlying role of genetic factors associated with predisposition to developing AF.

Methods and Results

We conducted a comprehensive review of the literature through large online libraries, including PubMed. Many different potassium and sodium channel mutations have been discussed in their relation to AF. There have also been non–ion channel mutations that have been linked to AF. Genome‐wide association studies have helped in identifying potential links between single‐nucleotide polymorphisms and AF. Ancestry studies have also highlighted a role of genetics in AF. Blacks with a higher percentage of European ancestry are at higher risk of developing AF. The emerging field of ablatogenomics involves the use of genetic profiles in their relation to recurrence of AF after catheter ablation.

Conclusions

The evidence for the underlying role of genetics in AF continues to expand. Ultimately, the role of genetics in risk stratification of AF and its recurrence is of significant interest. No established risk scores that are useful in clinical practice are present to date.

A Genome-Wide Association Study of Non-Photochemical Quenching in response to local seasonal climates in Arabidopsis thaliana

Field-grown plants have variable exposure to sunlight as a result of shifting cloud-cover, seasonal changes, canopy shading, and other environmental factors. As a result, they need to have developed a method for dissipating excess energy obtained from periodic excessive sunlight exposure. Non-photochemical quenching (NPQ) dissipates excess energy as heat, however, the physical and molecular genetic mechanics of NPQ variation are not understood. In this study, we investigated the genetic loci involved in NPQ by first growing different Arabidopsis thaliana accessions in local and seasonal climate conditions, then measured their NPQ kinetics through development by chlorophyll fluorescence. We used genome-wide association studies (GWAS) to identify 15 significant quantitative trait loci (QTL) for a range of photosynthetic traits, including a QTL co-located with known NPQ gene PSBS (AT1G44575). We found there were large alternative regulatory segments between the PSBS promoter regions of the functional haplotypes and a significant difference in PsbS protein concentration. These findings parallel studies in rice showing recurrent regulatory evolution of this gene. The variation in the PSBS promoter and the changes underlying other QTLs could give insight to allow manipulations of NPQ in crops to improve their photosynthetic efficiency and yield.

ShinyAIM: Shiny-based application of interactive Manhattan plots for longitudinal genome-wide association studies

Owning to advancements in sensor-based, non-destructive phenotyping platforms, researchers are increasingly collecting data with higher temporal resolution. These phenotypes collected over several time points are cataloged as longitudinal traits and used for genome-wide association studies (GWAS). Longitudinal GWAS typically yield a large number of output files, posing a significant challenge to data interpretation and visualization. Efficient, dynamic, and integrative data visualization tools are essential for the interpretation of longitudinal GWAS results for biologists; however, these tools are not widely available to the community. We have developed a flexible and user-friendly Shiny-based online application, ShinyAIM, to dynamically view and interpret temporal GWAS results. The main features of the application include (a) interactive Manhattan plots for single time points, (b) a grid plot to view Manhattan plots for all time points simultaneously, (c) dynamic scatter plots for p-value-filtered selected markers to investigate co-localized genomic regions across time points, (d) and interactive phenotypic data visualization to capture variation and trends in phenotypes. The application is written entirely in the R language and can be used with limited programming experience. ShinyAIM is deployed online as a Shiny web server application at https://chikudaisei.shinyapps.io/shinyaim/, enabling easy access for users without installation. The application can also be launched on a local machine in RStudio.

Genome-wide association studies of multiple sclerosis

Large-scale genetic studies of multiple sclerosis have identified over 230 risk effects across the human genome, making it a prototypical common disease with complex genetic architecture. Here, after a brief historical background on the discovery and definition of the disease, we summarise the last fifteen years of genetic discoveries and map out the challenges that remain to translate these findings into an aetiological framework and actionable clinical understanding.

The impact of genome-wide association studies on the pathophysiology and therapy of cardiovascular disease

Cardiovascular diseases are leading causes for death worldwide. Genetic disposition jointly with traditional risk factors precipitates their manifestation. Whereas the implications of a positive family history for individual risk have been known for a long time, only in the past few years have genome-wide association studies (GWAS) shed light on the underlying genetic variations. Here, we review these studies designed to increase our understanding of the pathophysiology of cardiovascular diseases, particularly coronary artery disease and myocardial infarction. We focus on the newly established pathways to exemplify the translation from the identification of risk-related genetic variants to new preventive and therapeutic strategies for cardiovascular disease.

Epigenetic heredity of human height

Genome‐wide SNP analyses have identified genomic variants associated with adult human height. However, these only explain a fraction of human height variation, suggesting that significant information might have been systematically missed by SNP sequencing analysis. A candidate for such non‐SNP‐linked information is DNA methylation. Regulation by DNA methylation requires the presence of CpG islands in the promoter region of candidate genes. Seventy two of 87 (82.8%), height‐associated genes were indeed found to contain CpG islands upstream of the transcription start site (USC CpG island searcher; validation: UCSC Genome Browser), which were shown to correlate with gene regulation. Consistent with this, DNA hypermethylation modules were detected in 42 height‐associated genes, versus 1.5% of control genes (P = 8.0199e⁻¹⁷), as were dynamic methylation changes and gene imprinting. Epigenetic heredity thus appears to be a determinant of adult human height. Major findings in mouse models and in human genetic diseases support this model. Modulation of DNA methylation are candidate to mediate environmental influence on epigenetic traits. This may help to explain progressive height changes over multiple generations, through trans‐generational heredity of progressive DNA methylation patterns.

Epigenetic heredity appears to be a determinant of adult human height. Major findings in mouse models and in human genetic diseases support this model. Modulation of DNA methylation is candidate to mediate environmental influence on epigenetic traits.