Publications by authors named "Peter Visscher"

Polygenic genome editing in human embryos and germ cells is predicted to become feasible in the next three decades. Several recent books and academic papers have outlined the ethical concerns raised by germline genome editing and the opportunities that it may present. To date, no attempts have been made to predict the consequences of altering specific variants associated with polygenic diseases.

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Biobanks aim to improve our understanding of health and disease by collecting and analysing diverse biological and phenotypic information in large samples. So far, biobanks have largely pursued a population-based sampling strategy, where the individual is the unit of sampling, and familial relatedness occurs sporadically and by chance. This strategy has been remarkably efficient and successful, leading to thousands of scientific discoveries across multiple research domains, and plans for the next wave of biobanks are underway.

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Article Synopsis
  • Scientists studied how certain genes affect height and body mass index (BMI) by looking at families with siblings.
  • They found that links between genes and these traits could be seen both in family studies and in studies that look at a lot of DNA variations (called SNPs).
  • They discovered that there are still many genetic factors influencing height and BMI that haven't been identified yet, showing that genetics is really complex and involves many genes working together.
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Fine-mapping refines genotype-phenotype association signals to identify causal variants underlying complex traits. However, current methods typically focus on individual genomic segments without considering the global genetic architecture. Here, we demonstrate the advantages of performing genome-wide fine-mapping (GWFM) and develop methods to facilitate GWFM.

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Article Synopsis
  • Fine-mapping is a method used to identify specific genetic variants that cause complex traits, but traditional approaches often overlook the overall genetic context.
  • This study introduces genome-wide fine-mapping (GWFM) as a more effective method, showing better performance in accuracy, replication, and cross-ancestry predictions compared to existing techniques.
  • In analyzing the UK Biobank data, GWFM helped identify causal variants contributing to significant heritability for traits like body mass index, schizophrenia, and Crohn's disease, demonstrating its potential for future genetic research.
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The causes of temporal fluctuations in adult traits are poorly understood. Here, we investigate the genetic determinants of within-person trait variability of 8 repeatedly measured anthropometric traits in 50,117 individuals from the UK Biobank. We found that within-person (non-directional) variability had a SNP-based heritability of 2-5% for height, sitting height, body mass index (BMI) and weight (P 2.

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  • * The research showed that individuals with high polygenic risk scores have significantly higher blood pressure (almost 17 mmHg more) and over seven times the risk of developing hypertension compared to those with low scores.
  • * Incorporating these genetic risk scores into hypertension prediction models improved their accuracy, and excitingly, similar genetic associations were found in a large African-American sample, underscoring the potential of these findings for precision health initiatives.
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  • The SBayesRC method combines genome-wide association study (GWAS) summary statistics with functional genomic data to enhance the prediction of complex traits using genetics.* -
  • It shows a notable increase in prediction accuracy—14% for European ancestry and up to 34% for cross-ancestry predictions—compared to previous methods, especially SBayesR, which lacks functional annotations.* -
  • The study finds that incorporating SNP density and functional information can further improve predictions, with key contributions from evolutionary constrained regions and nonsynonymous SNPs being the most impactful.*
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DNA methylation is an ideal trait to study the extent of the shared genetic control across ancestries, effectively providing hundreds of thousands of model molecular traits with large QTL effect sizes. We investigate cis DNAm QTLs in three European (n = 3701) and two East Asian (n = 2099) cohorts to quantify the similarities and differences in the genetic architecture across populations. We observe 80,394 associated mQTLs (62.

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Background: Substance use behaviours (SUB) including smoking, alcohol consumption, and coffee intake are associated with many health outcomes. However, whether the health effects of SUB are causal remains controversial, especially for alcohol consumption and coffee intake.

Methods: In this study, we assess 11 commonly used Mendelian Randomization (MR) methods by simulation and apply them to investigate the causal relationship between 7 SUB traits and health outcomes.

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Vitamin D status-a complex trait influenced by environmental and genetic factors-is tightly associated with skin colour and ancestry. Yet very few studies have investigated the genetic underpinnings of vitamin D levels across diverse ancestries, and the ones that have, relied on small sample sizes, resulting in inconclusive results. Here, we conduct genome-wide association studies (GWAS) of 25 hydroxyvitamin D (25OHD)-the main circulating form of vitamin D-in 442,435 individuals from four broad genetically-determined ancestry groups represented in the UK Biobank: European (N = 421,867), South Asian (N = 9,983), African (N = 8,306) and East Asian (N = 2,279).

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A fundamental goal in evolutionary biology is to understand the genetic architecture of adaptive traits. Using whole-genome data of 3955 of Darwin's finches on the Galápagos Island of Daphne Major, we identified six loci of large effect that explain 45% of the variation in the highly heritable beak size of a key ecological trait. The major locus is a supergene comprising four genes.

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Genome-wide association studies (GWASs) have been mostly conducted in populations of European ancestry, which currently limits the transferability of their findings to other populations. Here, we show, through theory, simulations and applications to real data, that adjustment of GWAS analyses for polygenic scores (PGSs) increases the statistical power for discovery across all ancestries. We applied this method to analyze seven traits available in three large biobanks with participants of East Asian ancestry (n = 340,000 in total) and report 139 additional associations across traits.

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Molecular quantitative trait loci (xQTLs) are often harnessed to prioritize genes or functional elements underpinning variant-trait associations identified from genome-wide association studies (GWASs). Here, we introduce OPERA, a method that jointly analyzes GWAS and multi-omics xQTL summary statistics to enhance the identification of molecular phenotypes associated with complex traits through shared causal variants. Applying OPERA to summary-level GWAS data for 50 complex traits (n = 20,833-766,345) and xQTL data from seven omics layers (n = 100-31,684) reveals that 50% of the GWAS signals are shared with at least one molecular phenotype.

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The impact of chromosomal inversions on human brain morphology remains underexplored. We studied 35 common inversions classified from genotypes of 33,018 adults with European ancestry. The inversions at 2p22.

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In polygenic score (PGS) analysis, the coefficient of determination (R) is a key statistic to evaluate efficacy. R is the proportion of phenotypic variance explained by the PGS, calculated in a cohort that is independent of the genome-wide association study (GWAS) that provided estimates of allelic effect sizes. The SNP-based heritability (h, the proportion of total phenotypic variances attributable to all common SNPs) is the theoretical upper limit of the out-of-sample prediction R.

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Autism omics research has historically been reductionist and diagnosis centric, with little attention paid to common co-occurring conditions (for example, sleep and feeding disorders) and the complex interplay between molecular profiles and neurodevelopment, genetics, environmental factors and health. Here we explored the plasma lipidome (783 lipid species) in 765 children (485 diagnosed with autism spectrum disorder (ASD)) within the Australian Autism Biobank. We identified lipids associated with ASD diagnosis (n = 8), sleep disturbances (n = 20) and cognitive function (n = 8) and found that long-chain polyunsaturated fatty acids may causally contribute to sleep disturbances mediated by the FADS gene cluster.

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Human cortical expansion has occurred non-uniformly across the brain. We assessed the genetic architecture of cortical global expansion and regionalization by comparing two sets of genome-wide association studies of 24 cortical regions with and without adjustment for global measures (i.e.

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In this study we quantify the accuracy of scoring the quality of research grants using a finite set of distinct categories (1, 2, …., k), when the unobserved grant score is a continuous random variable comprising a true quality score and measurement error, both normally distributed. We vary the number of categories, the number of assessors that score the same grant and a signal-to-noise ratio parameter.

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Testing the effect of rare variants on phenotypic variation is difficult due to the need for extremely large cohorts to identify associated variants given expected effect sizes. An alternative approach is to investigate the effect of rare genetic variants on DNA methylation (DNAm) as effect sizes are expected to be larger for molecular traits compared with complex traits. Here, we investigate DNAm in healthy ageing populations-the Lothian Birth Cohorts of 1921 and 1936-and identify both transient and stable outlying DNAm levels across the genome.

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The genetic regulation of post-prandial glucose levels is poorly understood. Here, we characterise the genetic architecture of blood glucose variably measured within 0 and 24 h of fasting in 368,000 European ancestry participants of the UK Biobank. We found a near-linear increase in the heritability of non-fasting glucose levels over time, which plateaus to its fasting state value after 5 h post meal (h = 11%; standard error: 1%).

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It has been 15 years since the advent of the genome-wide association study (GWAS) era. Here, we review how this experimental design has realized its promise by facilitating an impressive range of discoveries with remarkable impact on multiple fields, including population genetics, complex trait genetics, epidemiology, social science, and medicine. We predict that the emergence of large-scale biobanks will continue to expand to more diverse populations and capture more of the allele frequency spectrum through whole-genome sequencing, which will further improve our ability to investigate the causes and consequences of human genetic variation for complex traits and diseases.

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Article Synopsis
  • Gene-based association tests analyze multiple SNP-trait connections by examining groups within gene boundaries, commonly using the sum of χ statistics, but this can overlook important SNP effect directions that may reduce detection power.
  • The new method "mBAT-combo" enhances the detection of multi-SNP associations, especially in scenarios where some SNP effects mask others, and is shown to have superior performance compared to traditional methods.
  • Validation studies with the UK Biobank indicate that masking effects are prevalent across various traits, with significant genes identified by mBAT-combo that were not detected by single-SNP analyses, underscoring its value in studying complex traits.
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