Publications by authors named "Nikolas Baya"

Overall adiposity and body fat distribution are heritable traits associated with altered risk of cardiometabolic disease and mortality. Performing rare variant (minor allele frequency<1%) association testing using exome-sequencing data from 402,375 participants in the UK Biobank (UKB) for nine overall and tissue-specific fat distribution traits, we identified 19 genes where putatively damaging rare variation associated with at least one trait (Bonferroni-adjusted <1.58×10) and 52 additional genes at FDR≤1% (≤4.

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The phenotypic impact of compound heterozygous (CH) variation has not been investigated at the population scale. We phased rare variants (MAF ∼0.001%) in the UK Biobank (UKBB) exome-sequencing data to characterize recessive effects in 175,587 individuals across 311 common diseases.

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  • Genome-wide association studies (GWASs) analyzed data from over 41,000 infertility cases and 687,000 controls, identifying 21 genetic risk loci for infertility, with 12 previously unreported.
  • The study found significant genetic correlations between female infertility and conditions like endometriosis and polycystic ovary syndrome, suggesting interactions between genetic risk factors.
  • Exome sequencing revealed that women with rare testosterone-lowering variants are at higher risk for infertility, yet no general correlation between reproductive hormones and infertility was found, highlighting a complex genetic landscape.
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Exome-sequencing association studies have successfully linked rare protein-coding variation to risk of thousands of diseases. However, the relationship between rare deleterious compound heterozygous (CH) variation and their phenotypic impact has not been fully investigated. Here, we leverage advances in statistical phasing to accurately phase rare variants (MAF ~ 0.

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  • Response to survey questionnaires is crucial in social and behavioral research, but nonresponse is common and complicates result interpretation.
  • The study analyzed nonresponse behavior in 109 questionnaire items from the UK Biobank with 360,628 participants, finding that responses like "Prefer not to answer" and "I don't know" are linked to further nonresponse in follow-up surveys, even when accounting for education and health.
  • Genetic associations were discovered, indicating that these nonresponse answers correlate with education, health, and income, which could bias research findings; the authors emphasized participant privacy by not focusing on individual questions.
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Population genetic models only provide coarse representations of real-world ancestry. We used a pedigree compiled from 4 million parish records and genotype data from 2276 French and 20,451 French Canadian individuals to finely model and trace French Canadian ancestry through space and time. The loss of ancestral French population structure and the appearance of spatial and regional structure highlights a wide range of population expansion models.

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Classical statistical genetics theory defines dominance as any deviation from a purely additive, or dosage, effect of a genotype on a trait, which is known as the dominance deviation. Dominance is well documented in plant and animal breeding. Outside of rare monogenic traits, however, evidence in humans is limited.

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  • Autism spectrum disorder (ASD) is diagnosed more often in males than females, and studies suggest a "female protective effect" (FPE) could explain this difference.
  • Research using the Danish iPSYCH resource shows that female ASD cases have siblings with higher ASD rates compared to male ASD cases.
  • Genetic analysis reveals that mothers of ASD cases tend to have higher genetic risk for ASD, supporting the idea that females may be more resilient to inherited genetic factors associated with ASD.
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  • - This study offers a new method to analyze genetic influences on autism by exploring a large area of the genome instead of just mapping individual gene associations.
  • - Researchers identified a significant region (the 33-Mb p-arm of chromosome 16) that has a higher concentration of genetic factors linked to autism, including the 16p11.2 copy number variant.
  • - The findings show both common and rare genetic variations on chromosome 16 are linked to lower gene expression levels, suggesting they may work together in affecting autism risk.
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Genetic association results are often interpreted with the assumption that study participation does not affect downstream analyses. Understanding the genetic basis of participation bias is challenging since it requires the genotypes of unseen individuals. Here we demonstrate that it is possible to estimate comparative biases by performing a genome-wide association study contrasting one subgroup versus another.

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