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PubMed2025

Determining genotype and antimicrobial resistance of Salmonella Typhi in environmental samples by amplicon sequencing.

BACKGROUND: Estimates of the burden of typhoid fever due to Salmonella enterica serovar Typhi (S. Typhi) rely on data from clinical surveillance, which is rarely done in low income settings and is also limited by the poor sensitivity of the assays used and the reliance on health seeking by patients. Environmental surveillance for S. Typhi shed by symptomatic and asymptomatic individuals in wastewater offers a sensitive surveillance tool that could help to inform burden estimates. Sequencing S. Typhi direct from wastewater concentrates has the potential to identify circulating genotypes and associated antimicrobial resistance (AMR) genes, supporting public health interventions such as vaccination and antimicrobial usage. METHODOLOGY AND PRINCIPAL FINDINGS: We designed a multiplex targeted amplicon sequencing protocol for genotyping and determining AMR in S. Typhi from wastewater samples, targeting SNPs that identify genotypes of interest and both chromosomal and plasmid-borne AMR. PCR products were sequenced using the Oxford Nanopore Technologies (ONT) MinION, and genotypes and AMR identified using the GenoTyphi program. We tested this approach on samples from south India from both hospital outflow and wastewater collected from the community. All samples tested were suspected to be positive for S. Typhi following quantitative PCR for ttr, tviB, and staG gene targets. Out of 110 samples tested we were able to determine a genotype and/or AMR for 8. All samples that gave a genotype call suggested a genotype consistent with those found in clinical cases in India during the same time period and produced consensus sequences that clustered with S. Typhi when included in a phylogenetic tree. CONCLUSIONS: In this study, we provide proof of concept data for amplicon sequencing of S. Typhi in wastewater which with further optimisation could be used to complement clinical surveillance data or provide data on S. Typhi presence in the absence of clinical surveillance. This information can inform public health interventions, and the concept could be applied to other pathogens of interest for genotyping from environmental surveillance samples.

Salmonella typhi↗

PubMed2025

Development and application of a novel beta-tubulin genotyping tool reveals host-specific transmission cluster in Balantioides coli.

Balantioides coli is a zoonotic ciliated protozoan that infects humans and other mammals. Conventional and ITS-based genotyping approaches have limitations that hinder precise molecular epidemiological investigations. The objective of this study was to develop a new β-tubulin gene-based approach to enhance the detection and genotyping of B. coli. We performed single-cell isolation and whole-genome sequencing on two B. coli isolates from pigs and two from guinea pigs. We then used the β-tubulin gene sequences to design PCR primers for the new genotyping assay. We validated the assay using 56 ITS-confirmed B. coli-positive fecal DNA samples from pigs, cattle, sheep, and guinea pigs. Phylogenetic analyses were conducted using both β-tubulin and ITS sequences. The β-tubulin-based nested PCR assay exhibited 100% detection efficiency and greater specificity than ITS-based methods. Phylogenetic analysis of the β-tubulin gene sequences classified B. coli into three genotypes (I-III). Genotype III appears to be specific to guinea pigs. Genotypes I and II were found across multiple hosts, indicating potential cross-species transmission. Of the five full-length B. coli β-tubulin sequences obtained in this study, 264 polymorphic sites (19.8%) were identified, including both synonymous and non-synonymous mutations. Frequent recombination events within the β-tubulin locus were detected, indicating substantial genetic diversity. Therefore, the β-tubulin gene is a robust marker for genotyping and epidemiological studies of B. coli. The novel nested PCR assay overcomes the limitations of ITS-based methods and has produced data revealing previously unrecognized genetic diversity and host specificity patterns of B. coli.

Tubulin↗

PubMed2026

Management and Consequences of Genotype-Positive Familial Hypercholesterolemia.

IMPORTANCE: Familial hypercholesterolemia (FH) is a common genetic condition that causes hypercholesterolemia and increased risk for premature atherosclerotic cardiovascular disease (ASCVD). The prevalence, management, and consequences of genetically confirmed FH across the US are poorly understood. OBJECTIVE: To identify genotype-positive FH in a national US cohort and describe its prevalence, consequences, and lipid-lowering management. DESIGN, SETTING, AND PARTICIPANTS: In the All of Us (AoU) cohort study, whole-genome sequencing and phenotypic data from US adult participants enrolled between May 2018 and July 2022 were analyzed to identify and study genotype-positive FH. Data were analyzed between May 2024 and May 2025. EXPOSURE: FH variants (pathogenic or likely pathogenic) in LDLR, APOB, and PCSK9 genes were manually classified with standard criteria. MAIN OUTCOMES AND MEASURES: The primary outcomes were demographic characteristics, lipid measurements, ASCVD, and prevalence of FH and noncarriers in AoU. Lipid management was then characterized among individuals with FH through lipid-lowering therapy (LLT) documentation and guideline-based low-density lipoprotein cholesterol (LDL-C) targets. RESULTS: A total of 245 388 participants were included, with mean (SD) age of 56.5 (16.9) years and 145 563 female participants (59.3%). Genotype-positive FH was identified in 865 participants (prevalence, 0.35%; 95% CI, 0.33%-0.38%; 1 in 287 participants). Among individuals with genotype-positive FH, 349 (40%) were prescribed statins, and 332 (38.4%) had LDL-C measured. Coronary artery disease, peripheral artery disease, and transient ischemic attack or stroke were significantly more common in genotype-positive FH carriers compared to noncarriers (coronary artery disease: odds ratio [OR], 2.91; 95% CI, 2.34-3.58; peripheral artery disease: OR, 1.51; 95% CI, 1.16-1.96; and transient ischemic attack or stroke: OR, 1.54; 95% CI, 1.11-2.09). Only 30.1% of participants positive for FH variants had LDL-C less than 100 mg/dL at their most recent result compared to 48.2% of noncarriers (P < .001). Of the total participants with ASCVD and LLT prescription, significantly fewer individuals with FH met the secondary prevention LDL-C target (<70 mg/dL; 19.33% vs 43.12%; P < .001) compared to noncarriers. CONCLUSIONS AND RELEVANCE: This cohort study finds a prevalence of genotype-positive FH in All of Us participants of 0.35% (95% CI, 0.33%-0.38%), with state-level variation. A minority of individuals with genotype-positive FH met guideline-recommended LDL-C targets and had increased rates of ASCVD.

Humans↗

PubMed2025

Generating synthetic genotypes using diffusion models.

SUMMARY: In this paper, we introduce the first diffusion model designed to generate complete synthetic human genotypes, which, by standard protocols, one can straightforwardly expand into full-length, DNA-level genomes. The synthetic genotypes mimic real human genotypes without just reproducing known genotypes, in terms of approved metrics. When training biomedically relevant classifiers with synthetic genotypes, accuracy is near-identical to the accuracy achieved when training classifiers with real data. We further demonstrate that augmenting small amounts of real with synthetically generated genotypes drastically improves performance rates. This addresses a significant challenge in translational human genetics: real human genotypes, although emerging in large volumes from genome wide association studies, are sensitive private data, which limits their public availability. Therefore, the integration of additional, insensitive data when striving for rapid sharing of biomedical knowledge of public interest appears imperative. AVAILABILITY AND IMPLEMENTATION: All non proprietary data and the code to replicate the experiments is available on Github.

Humans↗

PubMed2026

Upscaling Genotyping by Amplicon Sequencing With GBAS-GUI.

Genotyping by amplicon sequencing (GBAS) is a relatively low-cost approach for generating genotypic data compared with established genomic methods, making it highly scalable and particularly suitable for large-scale genetic monitoring projects. However, most existing analytical pipelines are either marker-specific, insufficiently scalable, or lacking efficient data management systems for the long-term integration of genotypic information, limiting the full potential of GBAS. Here, we address this gap by introducing GBAS-GUI (https://github.com/sonnenbe-dot/GBAS-GUI), a pipeline capable of generating GBAS-based genotypic data for a wide variety of loci at scale. GBAS-GUI integrates a graphical user interface with multiple checkpoints to improve accessibility and robustness. It implements multiprocessing architecture and a relational database that links genotypic data with associated sample metadata to enhance scalability and data management. The pipeline further enables marker screening through automated calculation of polymorphism information content (PIC) and implements a strategy to recover homologous genotypic information from paralogous loci with non-overlapping amplicon length ranges. Using multiple empirical datasets, we demonstrate substantial improvements in processing speed, database management and handling artefacts related to co-amplification of unspecific regions and duplicates of the same genomic region. We further show that incorporating the full sequence information captured by an amplicon increases marker information content beyond what is achievable with length-based genotyping alone and expands the analytical versatility of GBAS. Overall, GBAS-GUI provides a robust, scalable and versatile framework that unlocks the potential of GBAS for large-scale population genetic and phylogeographic studies.

Genotyping Techniques↗

PubMed2026

Personalised Nutraceutical Treatment Guided by MTHFR Genotype in Mental Health: A Retrospective Cohort Study.

BACKGROUND & AIMS: One-carbon metabolism plays a central role in neurotransmitter synthesis, methylation capacity, and neurobiological resilience. Variants in the methylenetetrahydrofolate reductase (MTHFR) gene can reduce enzymatic activity, affecting folate- and methionine-cycle functions and potentially influencing biological pathways relevant to mood and anxiety disorders. Personalised nutraceutical treatment strategies, particularly those addressing methylation capacity through targeted B-vitamin, folate, and adjunctive metabolic interventions are increasingly implemented in integrative clinical practice, yet evidence regarding their clinical outcomes remains limited. METHODS: We conducted a retrospective cohort study of 50 adults attending an integrative general practice clinic for anxiety and/or depression. All received personalised nutraceutical treatment informed by clinical assessment, laboratory testing and, for 37/50 patients, MTHFR genotyping. Psychological distress was measured using the Kessler-10 (K10) scale at baseline and approximately three months later. Secondary analyses evaluated whether outcomes differed by MTHFR genotype, whether specific supplements (e.g., L-methylfolate and SAMe) were associated with greater improvement, whether biomarker changes correlated with symptom change, and the safety/tolerability profile. RESULTS: Across the full cohort, mean K10 scores significantly decreased by four points over the treatment period, with 72% of patients showing clinical improvement. Reductions in psychological distress were seen across all MTHFR genotypes, including individuals with homozygous variant genotypes. Supplement-specific analyses showed improvement among those receiving methylfolate or SAMe, although the differences were not statistically significant. Following nutraceutical treatment, biomarker analyses demonstrated significant increases in serum vitamin B12 and modest reductions in homocysteine, but biomarker shifts did not correlate strongly with K10 change. No serious adverse events or clinically significant abnormalities in liver or renal function were identified. CONCLUSIONS: In this real-world primary care cohort, personalised nutraceutical treatment, grounded in one-carbon metabolism support and applied alongside usual care, was associated with clinically meaningful reductions in psychological distress. Outcomes were comparable across MTHFR genotypes when treatments were appropriately tailored, suggesting that genotype and biomarker-informed nutraceutical strategies may mitigate potential metabolic disadvantages. These findings support further controlled research into precision nutraceutical psychiatry for anxiety and depression. Secondary analyses of genotype subgroup, specific supplements, and biomarker-outcome associations are reported alongside Benjamini-Hochberg FDR-adjusted p-values and should be interpreted as hypothesis-generating.

Humans↗

PubMed2026

Human Monocytic Models Reveal Genotype-Dependent Inflammatory Programs in VEXAS Syndrome.

OBJECTIVES: VEXAS syndrome is a severe X-linked autoinflammatory disorder caused by somatic mutations in ubiquitin-like modifier activating enzyme 1 (UBA1), with clinical outcomes that vary by UBA1 genotype. We aimed to elucidate genotype-specific inflammatory programs and identify potential therapeutic targets. METHODS: We conducted longitudinal deep phenotyping, including whole-blood RNA sequencing (RNA-seq) and clinical activity assessment. Peripheral blood samples were analyzed by single-cell RNA-seq. Human monocytic cell lines harboring each major UBA1 mutation (p.Met41Val, p.Met41Thr, or p.Met41Leu) were generated and subjected to transcriptomic and functional analyses. RESULTS: Thirteen patients with VEXAS syndrome contributed a total of 79 RNA-seq samples. Among genes upregulated in VEXAS syndrome, RNASE1 showed the strongest correlation with longitudinal disease activity (r = 0.70, FDR < 0.05) and was upregulated in patients' monocytes. In UBA1-mutant monocytic cell lines, genotype-dependent ubiquitination defects were observed in a graded manner (p.Met41Val > p.Met41Thr > p.Met41Leu), even in the absence of exogenous stimuli. These defects were accompanied by unfolded protein response activation, increased pro-inflammatory cytokine production, progressive cell death, and RNASE1 upregulation, all following the same graded pattern, recapitulating patient genotype-phenotype associations. Transcriptomic analyses demonstrated enrichment of pro-inflammatory, interferon, and necroptosis signatures in more severe genotypes. Notably, inhibition of receptor-interacting protein kinase 3 (RIPK3) markedly attenuated all pathological features, including RNASE1 upregulation. CONCLUSIONS: Our UBA1-mutant monocytic cell-line models, representing three distinct genotypes, recapitulate genotype-dependent inflammatory phenotypes that can be modulated by RIPK3 inhibition, providing a translational platform for mechanistic investigation and precision therapy development in VEXAS syndrome.

Journal Article↗

PubMed2017

Infection rate of Aedes aegypti mosquitoes with dengue virus depends on the interaction between temperature and mosquito genotype.

Dengue fever is the most prevalent arthropod-transmitted viral disease worldwide, with endemic transmission restricted to tropical and subtropical regions of different temperature profiles. Temperature is epidemiologically relevant because it affects dengue infection rates in Aedes aegypti mosquitoes, the major vector of the dengue virus (DENV). Aedes aegypti populations are also known to vary in competence for different DENV genotypes. We assessed the effects of mosquito and virus genotype on DENV infection in the context of temperature by challenging Ae. aegypti from two locations in Vietnam, which differ in temperature regimes, with two isolates of DENV-2 collected from the same two localities, followed by incubation at 25, 27 or 32°C for 10 days. Genotyping of the mosquito populations and virus isolates confirmed that each group was genetically distinct. Extrinsic incubation temperature (EIT) and DENV-2 genotype had a direct effect on the infection rate, consistent with previous studies. However, our results show that the EIT impacts the infection rate differently in each mosquito population, indicating a genotype by environment interaction. These results suggest that the magnitude of DENV epidemics may not only depend on the virus and mosquito genotypes present, but also on how they interact with local temperature. This information should be considered when estimating vector competence of local and introduced mosquito populations during disease risk evaluation.

Aedes↗

PubMed2025

Genotypic Analysis and Clinical Findings of Sapovirus-Associated Acute Gastroenteritis in Mie Prefecture, Japan, 2010-2022.

Sapovirus (SaV) is one of the major viruses causing acute gastroenteritis. Of the 1981 fecal specimens collected through sentinel pediatric acute gastroenteritis pathogen surveillance in Mie Prefecture, Japan (2010-2022), 236 were positive for SaV, according to PCR screening. Whole or near-whole genome sequences were determined for 158 strains by next-generation sequencing. Genotype GI.1 was the most common of the nine SaV genotypes detected, followed by GII.3 and GII.1. Phylogenetic analysis showed that SaVs of these three genotypes separated into three different clusters depending on the year of detection, suggesting continuous genetic changes in the same genotype. Coinfections involving different SaV genotypes, as well as reinfections with SaV in the same individual, were observed in this study. The main clinical manifestations were diarrhea (68.4%) and vomiting (61.6%), with an increased rate of emesis, particularly in patients over 3 years of age. In addition, 18.1% of the children had fever. This study clarified the prevalence of viral genotypes as well as clinical findings of SaV-positive gastroenteritis in children, and revealed trends by age.

Humans↗

PubMed1977

Influence of defined gene blocks on the competitive ability of yeast genotypes.

Competition experiments were carried out under varying exogenic and endogenic conditions. The genotypes were marked by combinations of two esterase loci, each with two alleles. When genotypes of the line W7 were used, there was no demonstrable influence of the gene blocks marked by the Est-1 locus on the competitive ability at temperatures of 21 and 29 C. However, genotypes carrying the fast allele of the Est-2 locus were favored. At 38 C, the outcome of the competition was reversed. The defined gene blocks showed different effects when interacting with different genetic backgrounds (line M7). Genotypes marked by the slow allele of the Est-2 locus were now favored (21 and 29 C), and even the gene blocks marked by the alleles of the Est-1 locus influenced the genotypes' competitive abilities. Again, the results were partly reversed at 38 C. The results are discussed with regard to the importance of enzyme variants for the genotypic selection value.

Alleles↗

PubMed1976

Enzyme variability in natural populations of Daphnia magna. IV. Ecological differentiation and frequency changes of genotypes at Audley End.

Genotypic frequencies were analysed for two years in a permanent population of the cladoceran crustacean, Daphnia magna, which was polymorphic for an esterase and for malate dehydrogenase. Large temporal changes in genotypic frequencies occurred at both loci. There was no evidence of a seasonal pattern in the frequency changes. In most samples, genotypes at the two enzyme loci were non-randomly associated; these associations showed temporal changes. On some occasions marked spatial heterogeneity in genotypic frequencies existed within the population. Genotypic differences in parthenogenetic and sexual egg production were observed. In a primarily parthenogenetically reproducing population, non-random associations between genotypes of structural and regulatory loci will be the rule. The allozyme variants themselves may or may not be under selection. The relevance of these observations to ecological studies on Daphnia is considered.

Animals↗

PubMed1999

An optimal algorithm for automatic genotype elimination.

In an effort to accelerate likelihood computations on pedigrees, Lange and Goradia defined a genotype-elimination algorithm that aims to identify those genotypes that need not be considered during the likelihood computation. For pedigrees without loops, they showed that their algorithm was optimal, in the sense that it identified all genotypes that lead to a Mendelian inconsistency. Their algorithm, however, is not optimal for pedigrees with loops, which continue to pose daunting computational challenges. We present here a simple extension of the Lange-Goradia algorithm that we prove is optimal on pedigrees with loops, and we give examples of how our new algorithm can be used to detect genotyping errors. We also introduce a more efficient and faster algorithm for carrying out the fundamental step in the Lange-Goradia algorithm-namely, genotype elimination within a nuclear family. Finally, we improve a common algorithm for computing the likelihood of a pedigree with multiple loops. This algorithm breaks each loop by duplicating a person in that loop and then carrying out a separate likelihood calculation for each vector of possible genotypes of the loop breakers. This algorithm, however, does unnecessary computations when the loop-breaker vector is inconsistent. In this paper we present a new recursive loop breaker-elimination algorithm that solves this problem and illustrate its effectiveness on a pedigree with six loops.

Algorithms↗

PubMed2025

Inference and visualization of complex genotype-phenotype maps with gpmap-tools.

Understanding how biological sequences give rise to observable traits, that is, how genotype maps to phenotype, is a central goal in biology. Yet our knowledge of genotype-phenotype maps in natural systems is limited due to the high dimensionality of sequence space and the context-dependent effects of mutations. The emergence of Multiplex assays of variant effect (MAVEs), along with large collections of natural sequences, offer new opportunities to empirically characterize these maps at an unprecedented scale. However, tools for statistical and exploratory analysis of these high-dimensional data are still needed. To address this gap, we developed gpmap-tools (https://github.com/cmarti/gpmap-tools), a python library that integrates a series of models for inference, phenotypic imputation, and error estimation from MAVE data or collections of natural sequences in the presence of genetic interactions of every possible order. gpmap-tools also provides methods for summarizing patterns of epistasis and visualization of genotype-phenotype maps containing up to millions of genotypes. To demonstrate its utility, we used gpmap-tools to infer genotype-phenotype maps containing 262,144 variants of the Shine-Dalgarno sequence from both genomic 5'UTR sequences and experimental MAVE data. Visualization of the inferred landscapes consistently revealed high-fitness ridges that link core motifs at different distances from the start codon. In summary, gpmap-tools provides a flexible, interpretable framework for studying complex genotype-phenotype maps, opening new avenues for understanding the architecture of genetic interactions and their evolutionary consequences.

Gaussian process↗

PubMed2026

Phylogeographic epidemiology of Dabie bandavirus in East Asia: divergent transmission networks and genotype‑linked clinical severity.

BACKGROUND: Severe fever with thrombocytopenia syndrome (SFTS), caused by Dabie bandavirus (SFTSV), exhibits geographically decoupled incidence and fatality patterns across East Asia. We aimed to elucidate the distinct ecological drivers and phylogeographic dynamics underlying this inland-coastal epidemiological divergence. METHODS: Integrating 1820 high-quality global genomes of SFTSV with well-characterized clinical cohorts (936 patients) and nationwide surveillance data (27,457 cases) from China, we constructed a comprehensive analytical framework. Ecological modeling, Bayesian phylogeography, and genotype-phenotype association analyses were employed to trace the evolutionary trajectories and clinical implications of the virus. RESULTS: A pronounced "inland-high-incidence vs. coastal-high-fatality" pattern of SFTS was identified. The incidence of SFTS exhibited divergent sensitivities to meteorological factors; inland transmission was sensitive to thermal fluctuations, whereas coastal dynamics were constrained by a sunshine threshold (> 200 h/month). In contrast, spatial divergence in clinical severity correlated with the distribution of regional viral genetic structures. Inland regions mainly co-circulated genotypes A, C, and D, while coastal regions were dominated by genotype B. Zhejiang province was identified as a genetic hub with significantly higher recombination frequencies than inland regions (11.0% vs. 3.5%, P < 0.001). Bayesian phylogeographic inference indicated frequent lineage exchange of Zhejiang province in China with the Republic of Korea and Japan. Clinically, genotypes B and D were associated with elevated mortality in coastal and inland regions, respectively, suggesting that the severe coastal phenotype is shaped by its genotype B-dominated structure. Additionally, the RdRp-N828S mutation emerged as a robust molecular correlate of fatal outcomes, warranting further functional validation. CONCLUSIONS: Divergent meteorological factors and plausible maritime transmission networks may underlie the geographically decoupled epidemiology of SFTS. These findings highlight that risk assessment must extend beyond incidence alone and provide a phylogeographically informed framework for targeted surveillance and genotype-specific interventions in high-risk hotspots.

Humans↗

PubMed2025

The clinical and electrocardiographic phenotype of patients with genotype-negative long QT syndrome.

BACKGROUND: Long QT syndrome (LQTS) is a genetic heart disease that increases the risk of ventricular arrhythmias and sudden cardia arrest. Despite advances in genetic testing, a small subset of patients with LQTS remain genetically elusive. OBJECTIVE: This study aimed to determine the prevalence and clinical characteristics of patients with a phenotype of LQTS but without a genotype. METHODS: This study aimed to identify phenotype-positive, genotype-negative patients with LQTS seen at Mayo Clinic (2000-2024). Retrospective data included demographics, clinical evaluations, electrocardiograms, and genetic results. Diagnosis adhered to established criteria, and genotype-negative LQTS was defined by the absence of pathogenic variants despite clinical presentation. RESULTS: The study included 1829 patients with LQTS. Of these, 1706 (93%) had pathogenic or likely pathogenic variants, and 95 patients (5%) had upgraded clinical variants of uncertain significance, leaving 32 (1.7%) with negative genetic tests. Among the genotype-negative patients, 17 underwent next-generation sequencing, identifying a genetic cause in 6 cases (0.3% of the total). The mean age at diagnosis for the remaining 26 patients was 25 ± 15 years, with 76% being women and an average initial corrected QT of 498 ± 41 ms. Fourteen patients (53%) experienced cardiac events prior to diagnosis, and 11 (44%) received an implantable cardioverter-defibrillator. The mean follow-up period was 8 ± 7 years. CONCLUSION: Genotype-negative LQTS accounted for < 2% of our cohort, highlighting diagnostic and management challenges. Comprehensive clinical evaluation and advanced genetic testing remain essential for accurate diagnosis and care.

Humans↗

PubMed2025

Genotyping of natural killer cell immunoglobulin-like receptors in human early reproductive losses.

Genotyping of killer cell immunoglobulin-like receptors (KIR) of NK-cells was performed in 634 women with early pregnancy losses (EPL), including 158 women with recurrent implantation failure (RIF) after at least three IVF cycles, and 110 women with at least two intrauterine pregnancy losses characterized by clinically confirmed retention of a non-viable fetus in the uterus without spontaneous miscarriage, defined as recurrent pregnancy loss (RPL). The control group consisted of 431 women with at least two healthy children. In the RIF, a significant shift in the frequency of KIR-genotypes was observed compared with both the control and the RPL groups. A significantly higher frequency of the KIR-AA genotype was observed in the RIF group compared to the control group (χ² = 26.78; p < 0.0001; OR = 2.7) and the RPL group (χ² = 15.83; p < 0.0001; OR = 2.86). Analysis of the frequency of full-length/deletion alleles of KIR2DS4 among AA genotype carriers showed an increased frequency of the 2DS4-del in the RIF compared with the RPL and control groups. A significantly higher frequency of the cenAA was also observed in RIF compared with the control (χ² = 20.10; p < 0.0001) and the RPL(χ² = 12.05; p < 0.005). The significantly increased frequency of the KIR-AA genotype with predominance of deletion KIR2DS4 alleles, along with the elevated frequency of the cenAA in RIF, may indicate insufficient NK-cell activation at the stage of embryo implantation. These findings suggest different etiological mechanisms for RIF and RPL.

Humans↗

PubMed2025

Adjustment for Genotype Imputation Uncertainty Corrects for Inflated Type I Error in Family-Based Association Testing.

Genotype imputation is a widely-used data augmentation approach that is applied to samples of related and/or unrelated individuals. Association testing may then be carried out on the complete data with commonly-used methods. This approach has typically not accounted for the mix of observed and imputed data, although recent work has noted the potential for introduction of confounding in case-control studies. In the Alzheimer's Disease Sequencing Project family sample we found severe inflation of the test statistics in logistic regression analysis following genotype imputation, even after standard covariate adjustments. Here we dissect sources of this inflation, which is driven by three factors: frequency-dependent bias in imputation-induced allele frequencies, differential measurement error, and differential genotyping rates in cases versus controls that introduces confounding. To address the problem, we propose a statistic, imputation deviance (), which can be easily computed from the observed and imputed genotype probabilities. We show that, as an additional fixed-effect covariate, controls the genome-wide inflation in analysis of this family-based sample, and we speculate that use of imputation deviance may also provide a practical approach to correct for genotype imputation effects in other settings, particularly when a data set is unbalanced and includes related individuals.

Humans↗

PubMed1975

Reproductive performance of male and female phenotypes in three sex chromosomal genotypes(XX, XY, YY) in the killifish, Oryzias latipes.

The present study investigates the juvenile and adult reproductive performance of Japanese killifish, Oryzias latipes, which were successfully sex-reversed by feeding them male or female sex hormones during the fry stage. Sexual maturation of these laboratory grown fish of three known genotypes (XX, SY, YY) occurred earliest in untreated genotypes, next in genotypes treated with male hormone (methyl testosterone) and female hormone (estrone), respectively. The delay in sexual maturation caused by early exogenous, sex-hormone treatment may represent a disturbance in the delicate neural-gonadal axis. However, the degree of response was also strongly influenced by the animal's sex chromosomal genotype. XX fish, normally phenotypic females, were affected more by the male hormone than by the female hormone. XY and YY fish, normally phenotypic males, were delayed more by the female hormone than by the male hormone. This specific sex hormone-sex genotype interaction also influenced adult reproductive performance (sperm or egg production). Differences in the metabolism of male and female sex hormones by the XX, XY, and YY fish are probably responsible for these interesting findings.

Age Factors↗