Biology subjects

Campos, A. I.

Publications and source records attributed to Campos, A. I..

3 recordsLinked to original sources

bioRxiv2026

Using summary data to detect and quantify ascertainment in biobanks

Non-random participation in genetic studies can bias associations between genetic variants and outcomes. Existing methods to detect ascertainment bias often require individual-level data, thus limiting their broad applicability. Here, we introduce a summary-statistics-based method to detect and quantify ascertainment bias in large-scale genetic studies. Our method estimates a parameter,{theta} , which captures deviations in the mean polygenic score (PGS) of an ascertained sample relative to its expectation across non-ascertained or differentially ascertained references. We show through extensive simulations that our method is robust to population stratification and reference misspecification unlike naive mean PGS comparison. When applied to 21 traits across 11 large-scale biobanks, our method recapitulates known patterns of ascertainment and detects new evidence of ascertainment on genetic susceptibility to depression, height and blood pressure in many biobanks. Overall, our framework enables systematic assessment of ascertainment directly from summary statistics and provides a scalable tool for evaluating representativeness in large scale genetic studies.

genetics↗

bioRxiv2020

Evidence of genetic overlap between circadian preference and brain white matter microstructure

Study objectivePrevious neuroimaging studies have highlighted differences in white matter microstructure among individuals with different chronotypes, but it is unclear whether those differences are due to genetic or environmental factors. MethodsHere we leverage summary statistics from recent large-scale genome-wide association studies (GWAS) of chronotype and diffusion tensor imaging (DTI) measures to examine the genetic overlap and infer causal relationships between these traits. ResultsWe identified 29 significant pairwise genetic correlations, of which 13 also had evidence for a causal association. Negative genetic correlations were identified between chronotype and brain-wide mean, axial and radial diffusivities. When exploring individual tracts, ten negative genetic correlations were observed with mean diffusivities, 10 with axial diffusivities, 4 with radial diffusivities and 2 with mode of anisotropy. We found evidence for a possible causal association of chronotype with white matter microstructure in individual tracts including the posterior limb and retrolenticular part of the internal capsule; the genu and splenium of the corpus callosum and the posterior, superior and anterior regions of the corona radiata. ConclusionsOur results suggest that eveningness is associated with variation in tract-specific white matter microstructure and, for an evening person, increases in axial and / or radial diffusivities may influence a higher mean diffusivity. These findings add to our understanding of circadian preference and its relationship with the brain, providing new perspectives on the genetic neurological underpinnings of chronotypes role in health and disease. Statement of SignificanceSleep is essential for a healthy brain function, particularly for neural organization and brain structure development. Individual chronotype differences have been associated with depression, schizophrenia, diabetes and obesity, among other conditions. Investigating the shared genetic aetiology between chronotype and white matter microstructure is essential to understand the neurological basis of individual variation in chronotype. In the present study, we show that tract-specific white matter microstructure is genetically correlated and causally associated with chronotype.

neuroscience↗

bioRxiv2019

Insights into the aetiology of snoring from observational and genetic investigations in the UK Biobank (n=408,317)

We conducted the largest study of snoring using data from the UK Biobank (n [~] 408,000; snorers [~]152,000). A genome-wide association study (GWAS) identified 42 genome-wide significant loci, with a SNP-based heritability estimate of [~]10% on the liability scale. Genetic correlations with body mass index, alcohol intake, smoking, schizophrenia, anorexia nervosa and neuroticism were observed. Gene-based associations identified 173 genes, including DLEU7, MSRB3 and POC5 highlighting genes expressed in brain, cerebellum, lungs, blood, and oesophagus tissues. We used polygenic scores (PGS) to predict recent snoring and probable obstructive sleep apnoea (OSA) in an independent Australian sample (n[~]8,000). Mendelian randomisation analyses provided evidence that larger whole body fat mass causes snoring. Altogether, our results uncover new insights into the aetiology of snoring as a complex sleep-related trait and its role in health and disease beyond being a cardinal symptom of OSA.

genomics↗