Genetic basis of partner choice.

Previous genetic studies of human assortative mating have primarily focused on searching for its genomic footprint but have revealed limited insights into its biological and social mechanisms. Combining insights from the economics of the marriage market with advanced tools in statistical genetics, we perform the first genome-wide association study (GWAS) on a latent index for partner choice. Using 206,617 individuals from four global cohorts, we uncover phenotypic characteristics and social processes underlying assortative mating.

One score to rule them all: regularized ensemble polygenic risk prediction with GWAS summary statistics.

Ensemble learning has been increasingly popular for boosting the predictive power of polygenic risk scores (PRS), with almost every recent multi-ancestry PRS approach employing ensemble learning as a final step. Existing ensemble approaches rely on individual-level data for model training, which severely limits their real-world applications, especially in non-European populations without sufficient genomic samples. Here, we introduce a statistical framework to construct regularized ensemble PRS, which allows us to combine a large number of candidate PRS models using only summary statistics from genome-wide association studies.

Pervasive biases in proxy genome-wide association studies based on parental history of Alzheimer's disease.

Almost every recent Alzheimer's disease (AD) genome-wide association study (GWAS) has performed meta-analysis to combine studies with clinical diagnosis of AD with studies that use proxy phenotypes based on parental disease history. Here, we report major limitations in current GWAS-by-proxy (GWAX) practices due to uncorrected survival bias and nonrandom participation in parental illness surveys, which cause substantial discrepancies between AD GWAS and GWAX results. We demonstrate that the current AD GWAX provide highly misleading genetic correlations between AD risk and higher education, which subsequently affects a variety of genetic epidemiological applications involving AD and cognition.

Minimally Invasive Sinus Augmentation: A Systematic Review.

Aim: Technology improvement and a better understanding of sinus anatomy and wound healing in the past decade have allowed the development of minimally invasive surgical techniques. This systematic review focused on identifying and describing these techniques for vertical and lateral sinus augmentation (VSA and LSA).

Materials And Methods: Electronic and hand search were conducted to screen the literature published from January 2003 to May 2024.

Optimizing and benchmarking polygenic risk scores with GWAS summary statistics.

Background: Polygenic risk score (PRS) is a major research topic in human genetics. However, a significant gap exists between PRS methodology and applications in practice due to often unavailable individual-level data for various PRS tasks including model fine-tuning, benchmarking, and ensemble learning.

Results: We introduce an innovative statistical framework to optimize and benchmark PRS models using summary statistics of genome-wide association studies.

Interpreting polygenic score effects in sibling analysis.

Researchers often claim that sibling analysis can be used to separate causal genetic effects from the assortment of biases that contaminate most downstream genetic studies (e.g. polygenic score predictors).

Pervasive biases in proxy GWAS based on parental history of Alzheimer's disease.

Almost every recent Alzheimer's disease (AD) genome-wide association study (GWAS) has performed meta-analysis to combine studies with clinical diagnosis of AD with studies that use proxy phenotypes based on parental disease history. Here, we report major limitations in current GWAS-by-proxy (GWAX) practices due to uncorrected survival bias and non-random participation of parental illness survey, which cause substantial discrepancies between AD GWAS and GWAX results. We demonstrate that current AD GWAX provide highly misleading genetic correlations between AD risk and higher education which subsequently affects a variety of genetic epidemiologic applications involving AD and cognition.

Mid-high-frequency error suppression of small optical aspheric molds.

To suppress the mid-high-frequency error of small optical tungsten carbide aspheric molds, it is proposed to quickly select the critical process parameters by simulating the residual error after convolution of the tool influence function (TIF). After polishing for 10.47 min by the TIF, two simulation optimizations, RMS and Ra, converge to 9.

The production of within-family inequality: Insights and implications of integrating genetic data.

The integration of genetic data within large-scale social and health surveys provides new opportunities to test long-standing theories of parental investments in children and within-family inequality. Genetic predictors, called polygenic scores, allow novel assessments of young children's abilities that are uncontaminated by parental investments, and family-based samples allow indirect tests of whether children's abilities are reinforced or compensated. We use over 16,000 sibling pairs from the UK Biobank to test whether the relative ranking of siblings' polygenic scores for educational attainment is consequential for actual attainments.

Decomposing heritability and genetic covariance by direct and indirect effect paths.

Estimation of heritability and genetic covariance is crucial for quantifying and understanding complex trait genetic architecture and is employed in almost all recent genome-wide association studies (GWAS). However, many existing approaches for heritability estimation and almost all methods for estimating genetic correlation ignore the presence of indirect genetic effects, i.e.

A quantile integral linear model to quantify genetic effects on phenotypic variability.

Detecting genetic variants associated with the variance of complex traits, that is, variance quantitative trait loci (vQTLs), can provide crucial insights into the interplay between genes and environments and how they jointly shape human phenotypes in the population. We propose a quantile integral linear model (QUAIL) to estimate genetic effects on trait variability. Through extensive simulations and analyses of real data, we demonstrate that QUAIL provides computationally efficient and statistically powerful vQTL mapping that is robust to non-Gaussian phenotypes and confounding effects on phenotypic variability.

GWAS on birth year infant mortality rates provides evidence of recent natural selection.

Following more than a century of phenotypic measurement of natural selection processes, much recent work explores relationships between molecular genetic measurements and realized fitness in the next generation. We take an innovative approach to the study of contemporary selective pressure by examining which genetic variants are “sustained” in populations as mortality exposure increases. Specifically, we deploy a so-called “regional GWAS” (genome-wide association study) that links the infant mortality rate (IMR) by place and year in the United Kingdom with common genetic variants among birth cohorts in the UK Biobank.

Computational Genomics in the Era of Precision Medicine: Applications to Variant Analysis and Gene Therapy.

Rapid methodological advances in statistical and computational genomics have enabled researchers to better identify and interpret both rare and common variants responsible for complex human diseases. As we continue to see an expansion of these advances in the field, it is now imperative for researchers to understand the resources and methodologies available for various data types and study designs. In this review, we provide an overview of recent methods for identifying rare and common variants and understanding their roles in disease etiology.

What's the use?

A theoretical framework predicts that using polygenic screening to select embryos against traits that depend on many genes has few benefits.

PUMAS: fine-tuning polygenic risk scores with GWAS summary statistics.

Polygenic risk scores (PRSs) have wide applications in human genetics research, but often include tuning parameters which are difficult to optimize in practice due to limited access to individual-level data. Here, we introduce PUMAS, a novel method to fine-tune PRS models using summary statistics from genome-wide association studies (GWASs). Through extensive simulations, external validations, and analysis of 65 traits, we demonstrate that PUMAS can perform various model-tuning procedures using GWAS summary statistics and effectively benchmark and optimize PRS models under diverse genetic architecture.

Transcriptome-wide transmission disequilibrium analysis identifies novel risk genes for autism spectrum disorder.

Recent advances in consortium-scale genome-wide association studies (GWAS) have highlighted the involvement of common genetic variants in autism spectrum disorder (ASD), but our understanding of their etiologic roles, especially the interplay with rare variants, is incomplete. In this work, we introduce an analytical framework to quantify the transmission disequilibrium of genetically regulated gene expression from parents to offspring. We applied this framework to conduct a transcriptome-wide association study (TWAS) on 7,805 ASD proband-parent trios, and replicated our findings using 35,740 independent samples.

Cerebrospinal fluid metabolomics identifies 19 brain-related phenotype associations.

The study of metabolomics and disease has enabled the discovery of new risk factors, diagnostic markers, and drug targets. For neurological and psychiatric phenotypes, the cerebrospinal fluid (CSF) is of particular importance. However, the CSF metabolome is difficult to study on a large scale due to the relative complexity of the procedure needed to collect the fluid.

The treatment response of barrier membrane with amoxicillin-loaded nanofibers in experimental periodontitis.

Background: Infection control is a major determinant of guided tissue regeneration (GTR). This study aims to develop an antibiotic-loaded membrane to assist periodontal repair.

Methods: Poly(D,L-lactic acid) (PDLLA) nanofibers encapsulating amoxicillin (PDLLA-AMX) were fabricated using the electrospinning technique, and their structures, drug encapsulation efficiency, and release characteristics were assessed.

Spatiotemporal segregation of human marginal zone and memory B cell populations in lymphoid tissue.

Human memory B cells and marginal zone (MZ) B cells share common features such as the expression of CD27 and somatic mutations in their IGHV and BCL6 genes, but the relationship between them is controversial. Here, we show phenotypic progression within lymphoid tissues as MZ B cells emerge from the mature naïve B cell pool via a precursor CD27CD45RB population distant from memory cells. By imaging mass cytometry, we find that MZ B cells and memory B cells occupy different microanatomical niches in organised gut lymphoid tissues.

IgE repertoire and immunological memory: compartmental regulation and antibody function.

It is now generally recognized that bone marrow is the survival niche for antigen-specific plasma cells with long-term immunological memory. These cells release antibodies into the circulation, needed to prime effector cells in the secondary immune response. These antibodies participate in the surveillance for antigen and afford immune defence against pathogens and toxins previously encountered in the primary immune response.

Transitional B Cells in Early Human B Cell Development - Time to Revisit the Paradigm?

The B cell repertoire is generated in the adult bone marrow by an ordered series of gene rearrangement processes that result in massive diversity of immunoglobulin (Ig) genes and consequently an equally large number of potential specificities for antigen. As the process is essentially random, the cells exhibiting excess reactivity with self-antigens are generated and need to be removed from the repertoire before the cells are fully mature. Some of the cells are deleted, and some will undergo receptor editing to see if changing the light chain can rescue an autoreactive antibody.

Significant Differences in Physicochemical Properties of Human Immunoglobulin Kappa and Lambda CDR3 Regions.

Antibody variable regions are composed of a heavy and a light chain, and in humans, there are two light chain isotypes: kappa and lambda. Despite their importance in receptor editing, the light chain is often overlooked in the antibody literature, with the focus being on the heavy chain complementarity-determining region (CDR)-H3 region. In this paper, we set out to investigate the physicochemical and structural differences between human kappa and lambda light chain CDR regions.

Antibodies and superantibodies in patients with chronic rhinosinusitis with nasal polyps.

Background: Chronic rhinosinusitis with nasal polyps is associated with local immunoglobulin hyperproduction and the presence of IgE antibodies against Staphylococcus aureus enterotoxins (SAEs). Aspirin-exacerbated respiratory disease is a severe form of chronic rhinosinusitis with nasal polyps in which nearly all patients express anti-SAEs.

Objectives: We aimed to understand antibodies reactive to SAEs and determine whether they recognize SAEs through their complementarity-determining regions (CDRs) or framework regions.