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[Experimental verification of several assumptions and methods of statistical genetics. II].

The applicability of A. S. Serebrovsky's formulas and N. A. Sobolev's methods was investigated for a dihybrid cross. It was shown that Serebrovsky's formulas do not always lead to a correct estimation of the minimal number of genes by which the parents are distinguished. In the case of gene interaction this estimation sometimes proved to be exaggerated 2-4 times. A test of Sobolev's method demonstrated that this method cannot be considered as reliable for work. Most of his estimations are not correct. Various estimations of the same phenomenon are often contradictory.

Alleles↗
PubMed1976

HLA-SD antigens and schizophrenia: statistical and genetical considerations.

The HLA-SD phenotype distributions of hebephrenic and paranoid schizophrenics, and of the two groups combined, in an Italian population and in a combined group from the Swedish population have been analyzed statistically. There is a significantly decreased frequency of HLA-A10 in all of these. Theae are some preliminary indications of an increased frequency (a positive association) for some of the other antigens of the HLA-SD series, but there is insufficient data at present for evaluating the significance of these findings. Differences between hebephrenic and paranoid schizophrenics have been detected.

Diagnosis, Differential↗
PubMed1976

A genetic and statistical study of the respiratory distress syndrome.

The hospital records of 197 infants with the respiratory distress syndrome (RDS) were reviewed and the families of 111 of them subsequently contacted to obtain a family history. After correcting for biasis of ascertainment, the incidence of RDS among the full sibs was found to be between 12 and 19% depending on whether the individuals diagnosed as "possible RDS" were counted as affected. Among the low birth weight (LBW, less than or equal to 2.5 kg) and/or preterm (less than or equal to 37 weeks gestation) infants in the sibships, the incidence of RDS was 32-50%. Considering only sibs born after the probands yielded the empiric recurrence risk of 17--27% for all younger sibs and 39--67% for LBW/preterm younger sibs. The risk for maternal half-sibs was of about the same magnitude as that for full sibs, while the risk for paternal half-sibs was minimal. Among the LBW/preterm first cousins of probands, only the infants of maternal aunts showed an RDS incidence clearly higher than that in the general population. We think these data suggest a genetically determined maternal factor predisposing the infants of certain mothers to RDS. Other significant findings include: 1) an excess of males among the probands but a normal sex ratio among the sibs of the probands; 2) a decrease in mean birth weight and mean length of gestation for not only the probands but also their sibs; 3) a decrease in the mean parental ages at the birth of the probands; 4) a relative dearth of first-born and an excess of second-born infants among the probands; 5) an increased incidence of stillbirths in the sibships; 6) an increased number of probands born by cesarean section; and 7) a twin concordance of 75%.

Age Factors↗
PubMed2024

Genetics of Latin American Diversity Project: Insights into population genetics and association studies in admixed groups in the Americas.

Latin Americans are underrepresented in genetic studies, increasing disparities in personalized genomic medicine. Despite available genetic data from thousands of Latin Americans, accessing and navigating the bureaucratic hurdles for consent or access remains challenging. To address this, we introduce the Genetics of Latin American Diversity (GLAD) Project, compiling genome-wide information from 53,738 Latin Americans across 39 studies representing 46 geographical regions. Through GLAD, we identified heterogeneous ancestry composition and recent gene flow across the Americas. Additionally, we developed GLAD-match, a simulated annealing-based algorithm, to match the genetic background of external samples to our database, sharing summary statistics (i.e., allele and haplotype frequencies) without transferring individual-level genotypes. Finally, we demonstrate the potential of GLAD as a critical resource for evaluating statistical genetic software in the presence of admixture. By providing this resource, we promote genomic research in Latin Americans and contribute to the promises of personalized medicine to more people.

Humans↗
PubMed2025

SPC: a SPectral Component approach leveraging Identity-by-Descent graphs to address recent population structure in genomic analysis.

Population structure is a well-known confounder in statistical genetics, particularly in genome-wide association studies (GWAS), where it can lead to inflated test statistics and spurious associations. Traditional methods, such as principal components (PCs), commonly used to adjust for population structure, are limited in capturing fine-scale, non-linear patterns that arise from recent demographic events - patterns that are crucial for understanding rare variant effects. To address this challenge, we propose a novel method called SPectral Components (SPCs), which leverages identity-by-descent (IBD) graphs to capture and transform local, non-linear fine-scale population structure into continuous representations that can be seamlessly integrated into genetic analysis pipelines. Using both simulated datasets and empirical data from the UK Biobank (N ≈ 420,000), we demonstrate that SPCs outperform PCs in adjusting for fine-scale population structure. In simulations, SPCs explained over 90% of the fine-scale population structure with fewer components, while PCs captured less than 5%. In the UK Biobank, SPCs reduced the inflation of p-values in the GWAS of an environmental-driven phenotype by 12% compared to PCs, while maintaining a similar performance to PCs in height, a highly heritable phenotype. Additionally, SPCs improved rare variant association analyses, reducing genomic inflation (e.g., from 7.6 to 1.2 in one analysis), and provided more accurate heritability estimates. Spatial autocorrelation analysis further confirmed the ability of SPCs to account for environmental effects, reducing Moran's I for both environmental and heritable phenotypes more effectively than PCs. Overall, our findings demonstrate that SPCs provide a robust, scalable adjustment for recent population structure, offering a powerful alternative or complement to PCs in large-scale biobank studies.

GWAS↗
PubMed2026

Causal Relationship Between Ischemic Stroke and Vascular Dementia: A Mendelian Randomization Study.

Ischemic stroke (IS) is a major cause of disability and mortality worldwide, and vascular dementia (VaD) is a common dementia subtype associated with cerebrovascular injury. Observational studies have suggested a relationship between IS and VaD, but these studies are vulnerable to confounding and reverse causality. This protocol describes a reproducible two-sample Mendelian randomization (MR) workflow for evaluating the potential causal association between IS and VaD using publicly available genome-wide association study (GWAS) summary statistics. Genetic instruments associated with IS were extracted from a public GWAS dataset, and outcome associations for VaD were obtained from a public VaD GWAS dataset. The corresponding dataset IDs are provided in the Protocol section. After outcome matching and allele harmonization, 51 single-nucleotide polymorphisms (SNPs) were retained for the final MR analysis. The workflow includes instrumental variable selection, linkage disequilibrium clumping, allele harmonization, instrument strength assessment, inverse variance weighted (IVW) analysis, weighted median analysis, MR-Egger analysis, heterogeneity testing, horizontal pleiotropy assessment, and leave-one-out sensitivity analysis. In the representative analysis, the IVW method showed a positive association between genetically predicted IS and VaD risk, and the weighted median method yielded a directionally concordant result. The MR-Egger estimate was directionally consistent but did not reach statistical significance. Therefore, these findings should be interpreted as suggestive evidence of a possible causal effect, rather than definitive proof of causality. This protocol may help researchers apply a transparent and reproducible MR workflow to investigate cerebrovascular disease-related outcomes using public GWAS data.

Humans↗
PubMed2025

The role of the brain-bone axis in skeletal degenerative diseases and psychiatric disorders, A genome-wide pleiotropic analysis.

INTRODUCTION: Skeletal degenerative diseases and psychiatric disorders often coexist clinically. However, the genetic correlations and underlying biological mechanisms between these two types of diseases remain unclear. OBJECTIVES: To investigate the genetic correlations between skeletal degenerative diseases and psychiatric disorders and to identify shared genomic loci, genes, and pathways. METHODS: This comprehensive genome-wide pleiotropic association study utilized summary statistics from publicly available genome-wide association data. Various statistical genetic correlation methods were employed, including LDSC, HDL, PLACO, Coloc, Hyprcoloc, and Mendelian randomization (MR) analysis, along with immune cell colocalization analysis. The study aimed to identify potential shared genetic factors among three skeletal degenerative diseases (osteoarthritis, intervertebral disc degeneration, and osteoporosis) and three psychiatric disorders (schizophrenia, anxiety disorder, and major depressive disorder). RESULTS: Analyses using LDSC, HDL, and Bonferroni corrections revealed significant genetic correlations between intervertebral disc degeneration (IVDD) and anxiety disorder (ANX); fractures, IVDD, and arthritis with major depressive disorder (MDD); and arthritis with schizophrenia (SCZ). Significant genetic correlations were also observed between VDD and ANX, fractures, IVDD, hip osteoarthritis (HipOA), knee osteoarthritis (KneeOA) and MDD, and KneeOA and SCZ. Pleiotropy analysis using PLACO, MAGMA, and multitrait colocalization Hyprcoloc identified 65 pleiotropic loci, 27 shared causal loci, and 9 shared risk loci involving immune cells related to both psychiatric and bone-related diseases. Additionally, tissue-specific enrichment analysis showed that genes mapped to these loci were enriched in brain, cardiovascular, pancreatic, and other tissues. The IVW method demonstrated that MDD increased the risk of IVDD and KneeOA, while IVDD increased the risk of ANX and MDD. Conversely, SCZ was associated with a reduced risk of KneeOA. Multiple sensitivity analyses further supported a positive causal effect of IVDD on MDD. CONCLUSION: These findings suggest significant genetic correlations between skeletal degenerative diseases and psychiatric disorders, highlighting multiple shared comorbid genes and key immune cell types. Importantly, the study supports the role of the brain-bone axis in the regulation of skeletal degenerative diseases and psychiatric disorders, which could provide valuable insights for potential therapeutic targets and interventions for these conditions.

Humans↗
PubMed2025

Tsbrowse: an interactive browser for ancestral recombination graphs.

SUMMARY: Ancestral recombination graphs (ARGs) represent the interwoven paths of genetic ancestry of a set of recombining sequences. The ability to capture the evolutionary history of samples makes ARGs valuable in a wide range of applications in population and statistical genetics. ARG-based approaches are increasingly becoming a part of genetic data analysis pipelines due to breakthroughs enabling ARG inference at biobank-scale. However, there is a lack of visualization tools, which are crucial for validating inferences and generating hypotheses. We present tsbrowse, an open-source, web-based Python application for the interactive visualization of the fundamental building blocks of ARGs, i.e. nodes, edges and mutations. We demonstrate the application of tsbrowse to various data sources and scenarios, and highlight its key features of browsability along the genome, user interactivity, and scalability to very large sample sizes. AVAILABILITY AND IMPLEMENTATION: Tsbrowse is installed as a Python package from PyPI (https://pypi.org/project/tsbrowse/), while a development version is maintained at https://github.com/tskit-dev/tsbrowse. Documentation is available at https://tskit.dev/tsbrowse/docs/. Source code is archived on Zenodo with DOI, https://doi.org/10.5281/zenodo.15683039.

Software↗
PubMed2026

Human skin microbiota and postpartum depression: A bidirectional Mendelian randomization study.

Postpartum depression (PPD) is a common mental health disorder after childbirth. Although microbiome research in PPD has mainly focused on the gut, the role of skin microbiota remains unclear. We used Mendelian randomization (MR) to assess potential causal associations between skin microbiota and PPD. A bidirectional 2-sample MR analysis used genome-wide association study (GWAS) summary statistics. Genetic instruments for skin microbial features were obtained from a published skin microbiota GWAS, and PPD data were derived from 67,205 mothers (7604 cases, 59,601 controls). Instruments were selected at P&#x2005;<1&#x2005;&#xd7;&#x2005;10-5, linkage disequilibrium-clumped, harmonized, and filtered for weak instruments (F statistic&#x2005;<10). Because this microbiome threshold is exploratory, Benjamini-Hochberg false discovery rate correction was applied within taxonomic levels. The inverse-variance weighted method was primary, complemented by weighted median and mode-based methods. Heterogeneity, pleiotropy, and outliers were assessed using Cochran Q, MR-Egger intercept, and MR-PRESSO. Three skin microbial taxa showed nominal associations with PPD. Higher genetically predicted Acinetobacter on the dorsal forearm (dry skin; 9 single nucleotide polymorphisms [SNPs]; mean F&#x2005;=&#x2005;22.12) and Proteobacteria in the antecubital fossa (moist skin; 6 SNPs; mean F&#x2005;=&#x2005;23.44) were associated with increased PPD risk, whereas Betaproteobacteria in the antecubital fossa (11 SNPs; mean F&#x2005;=&#x2005;21.54) was associated with decreased risk. Associations were directionally consistent, with no substantial heterogeneity or horizontal pleiotropy. After multiple-testing assessment, the findings were exploratory rather than definitive. Reverse MR did not support an effect of PPD on the identified skin microbiota. This MR study provides exploratory genetic evidence linking specific skin microbial features to PPD risk. The findings extend microbiota-related hypotheses beyond the gut microbiome but require validation in larger microbiome GWAS datasets, longitudinal cohorts, and mechanistic studies before clinical or causal conclusions are drawn.

Humans↗
PubMed1978

Research designs for the study of gene-environment interactions in psychiatric disorders. Report of a Foundations Fund for Research in Psychiatry Panel.

Understanding the genetic and environmental contributions (and their interactions, which are likely to be complex) to the etiology of psychiatric disorders requires research designs incorporating many basic principles of genetics. Genetic variation is likely to contribute to psychiatric disorders and genetic heterogeneity is likely to exist for any single disorder, ie, completely different genetic variants may each be capable of increasing an individual's susceptibility to the disorder. Thus, it is important to define phenotypes that may more closely reflect each individual genetic variant rather than to rely solely on the psychiatric diagnosis. Research should be undertaken with the goal of testing specific hypotheses that can be excluded. Research designs can include studies of unrelated individuals, twins, separated relatives, nuclear families, or extended pedigrees. Not all hypotheses can be tested on one type of data, and appropriate analytic methods vary. Because genetic hypotheses cannot be tested on studies of unrelated individuals, it is important that data be collected on families instead of unrelated individual patients and/or controls. Studies should include traits that bridge the gap between the genotype and the diagnostic phenotype. Such studies should be multidisciplinary, and the best statistical-genetics methodology should be used for data analysis.

Adoption↗
PubMed2025

Joint, multifaceted genomic analysis enables diagnosis of diverse, ultra-rare monogenic presentations.

Genomics for rare disease diagnosis has advanced at a rapid pace due to our ability to perform in-depth analyses on individual patients with ultra-rare diseases. The increasing sizes of ultra-rare disease cohorts internationally newly enables cohort-wide analyses for new discoveries, but well-calibrated statistical genetics approaches for jointly analyzing these patients are still under development. The Undiagnosed Diseases Network (UDN) brings multiple clinical, research and experimental centers under the same umbrella across the United States to facilitate and scale case-based diagnostic analyses. Here, we present the first joint analysis of whole genome sequencing data of UDN patients across the network. We introduce new, well-calibrated statistical methods for prioritizing disease genes with de novo recurrence and compound heterozygosity. We also detect pathways enriched with candidate and known diagnostic genes. Our computational analysis, coupled with a systematic clinical review, recapitulated known diagnoses and revealed new disease associations. We further release a software package, RaMeDiES, enabling automated cross-analysis of deidentified sequenced cohorts for new diagnostic and research discoveries. Gene-level findings and variant-level information across the cohort are available in a public-facing browser ( https://dbmi-bgm.github.io/udn-browser/ ). These results show that case-level diagnostic efforts should be supplemented by a joint genomic analysis across cohorts.

Humans↗
PubMed2026

Understanding Genomic Landscapes of Differentiation in Round-Tailed Horned Lizards (Phrynosoma modestum).

Population divergence is promoted by divergent selection and inhibited by gene flow, but the mechanisms of and relationship between these two processes remain poorly understood. Developing a well-informed hypothesis of the selective pressures underlying divergence in a natural population requires a thorough understanding of both species structure and demographic history. In this study, we assess whole-genome sequences of round-tailed horned lizards (Phrynosoma modestum) from throughout the species range and combine phylogenetic analyses with genomic landscape scans to understand how current genetic diversity has been influenced by demographic histories and evolutionary pressures. Maximum likelihood (ML) phylogenetic analysis supports two lineages within the species, corresponding to a North/South population divide that developed around 7&#x2005;million years ago (Ma) and displays little migration. However, intermediate genealogical divergence index values between the two lineages ultimately leave us unable to recommend a full taxonomic distinction. Genome-wide scans of population genetic statistics identified islands of divergence exhibiting differentiation patterns linked to models of reproductive isolation and within-population selection. Significantly negative values of Tajima's D and positive selection statistics in these islands offer support for selection acting on P. modestum, but patterns may also stem from recent population expansions. We posit that selection within populations has played a large role in shaping genomic divergence across the species' range. Taken together, our results provide perspective into how variable selective pressures shape the genomics of two divergent populations currently maintaining species integrity, despite significant signatures of geographic structure and divergence.

Animals↗
PubMed1979

Trends and developments in physical anthropology, 1978-1979.

Members of the American Association of Physical Anthropologists were asked to supply information about their current programs and their own graduate training in order to compile a training directory and to analyze certain aspects of the discipline. The data indicate that the majority consider their graduate training to have been deficient, mainly in statistics, genetics, chemistry, physiology, and mathematics. The areas though most important for future research in physical anthropology include fields such a genetics, anatomy, ecology, physiology, and paleontology, although a great many individuals are engaged in teaching and research in other areas. A brief analysis of relative growth in the field over the last few decades indicates a serious imbalance between the number of new Ph.D.'s and available employment opportunities.

Anthropology, Physical↗
PubMed2025

Exploring genetic adaptation and microbial dynamics in engineered anaerobic ecosystems via strain-level metagenomics.

Genetic heterogeneity exists within all microbial populations, with sympatric cells of the same species often exhibiting single-nucleotide variations that influence phenotypic traits, including metabolic efficiency. However, the evolutionary dynamics of these strain-level differences in response to environmental stress remain poorly understood. Here, we present a first-of-its-kind study tracking the adaptive evolution of an anaerobic, carbon-fixing microbiota under a controlled engineered ecosystem focused on carbon dioxide bioconversion into methane. Leveraging strain-resolved metagenomics with an ad hoc variant calling and phasing approach, we mapped mutation trajectories and observed that the two dominant Methanothermobacter species maintained distinct sweeping haplotypes over time, most likely due to niche-specific metabolic roles. By combining population genetic statistics and peptide reconstruction, mer and mcrB genes emerged as potential drivers of archaeal strain-level competition. These findings pave the way for targeted engineering of microbial communities to enhance bioconversion efficiency, with significant implications for sustainable energy and carbon management in anaerobic systems.

Metagenomics↗
PubMed2026

Genome-wide association and selective sweep analyses reveal genetic loci for teat number trait in pigs.

Teat number is a key reproductive trait for the commercial pig industry, as an optimum number enhances weaned piglet survival rate. This study aimed to identify single nucleotide polymorphisms (SNPs) and genomic regions that are associated with teat number in the Large White sow. A total of 1000 French Large White sows were used in an analysis of total, left/right, and maximum unilateral teat number. Environmental factor, Spearman correlation, genome-wide association study (GWAS), linkage disequilibrium, and selective sweep analyses were conducted, with validation performed in a population of 1145 Landrace pigs. Genetic statistics showed that this population's teat number had moderate-low genomic heritability (h2&#xa0;=&#xa0;0.17-0.21) and weak negative correlation with weaned piglet litter weight. Parity and season affected teat development. GWAS identified 17 candidate SNPs on SSC 4, 7, and 17. Combined with selective sweep analysis, two key regions on SSC 7 were found, with four teat number-related SNPs, annotated to VRTN, DIO2, NRXN3. These candidate genes are associated with thoracic vertebrae development, hormone regulation during the early stage of teat formation, and nervous system development. These five SNPs showed similar results in the Landrace pig validation population; non-mutant homozygotes had 0.25-1.15 more teats than mutant ones in both populations. This study contributes to the identification of key variant loci associated with teat number-related traits in sows, thereby providing reliable molecular markers and a theoretical basis for marker-assisted selection of sow reproductive performance.

Animals↗
PubMed1976

Statistical resolution of genetic heterogeneity in familial disease.

If a disease can be split into two or more groups on any criterion (clinical, biochemical, physiological or statistical) then the grouping can be tested to establish if genetically independent forms of the disease have been identified. The data required are simply the frequencies of the two disease groups in relatives of probands for each of the disease groups. A systematic search for such distinct groups is proposed in searches for genetic heterogeneity in familial diseases. In disease forms with overlapping, correlated genetic liabilities, the method of Falconer (1967) can be used to estimate the genetic correlation. However, when the groupings of the disease are confounded (such as one form precluding the other as in early and late onset diabetes) Falconer's method will be biased. Special methods of analysis to estimate the genetic parameters have been developed and are presented here. However, even when the groupings are confounded the Falconer method still gives reasonable estimates of the genetic correlation, in that they are unlikely to seriously mislead the investigator in the analysis and interpretation of observed data. In practice Falconer's simple method may be preferred to the more complex methods developed here because it involves fewer assumptions and can be applied over a wider range of circumstances.

Anencephaly↗