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PubMed2026

Genetic Diversity Analysis of Red Fox Populations (Vulpes vulpes L., 1758) in Natural and Anthropogenic Isolation.

This study presents a comparative analysis of the genetic structure and diversity of three red fox (Vulpes vulpes L.) populations representing different microevolutionary scenarios: panmixia (free-ranging Belarusian foxes), geographic isolation (free-ranging Scottish foxes), and anthropogenic selection (farm-bred foxes). Using a validated set of STR markers, multivariate statistical analysis was conducted to assess the genetic structure and the degree of genetic erosion across the studied groups. The wild red fox population in Belarus has been shown to maintain a state close to panmixia (PHWE = 0.090), characterized by a high effective population size (Ne = 694) and high allelic diversity. The island population from Scotland exhibits moderate gene pool depletion (Ne = 75.9) and a pronounced heterozygote deficiency (FIS = 0.18). Critical genetic erosion, which was characterized by a minimal effective population size (Ne = 60.2) and allelic fixation, was detected in the farm-bred group. The genetic distance between farm-bred and wild foxes (FST = 0.279; p = 0.001) reflects both the phylogeographic divergence between the Nearctic ancestors of farmed lineages and Palearctic wild populations, and the consequences of prolonged anthropogenic isolation, genetic drift, and selective breeding. These data indicate that artificial isolation and the impacts of genetic drift and targeted selection lead to a substantial depletion of the species' adaptive potential.

Animals↗

PubMed2026

Genomic erosion in the assessment of species' extinction risk and recovery potential.

Many species are undergoing rapid population declines and environmental deterioration, leading to genomic erosion. Here we define genomic erosion as the loss of genetic diversity, accumulation of deleterious mutations, maladaptation, and introgression, all of which can undermine individual fitness and long-term population viability. Critically, this process continues even after demographic recovery due to a time-lagged impact of genetic drift, which is known as drift debt. Current conservation assessments, such as the International Union for Conservation of Nature Red List, focus on short-term extinction risk and do not capture the long-term consequences of genomic erosion. Likewise, the longer-term assessments of the International Union for Conservation of Nature Green Status may overestimate population recovery by failing to account for the enduring effects of genomic erosion. As genome sequencing becomes increasingly accessible, there is a growing opportunity to quantify genomic erosion and integrate it into conservation planning. Here, we use genomic simulations to illustrate how different genomic metrics are sensitive to the drift debt. We test how ancestral effective population size (Ne) and bottleneck history influence the tempo and severity of genomic erosion. Furthermore, we demonstrate how these dynamics shape genetic load and additive genetic variation, which are key indicators of long-term evolutionary potential. Finally, we present a proof-of-concept for a Genomic Green Status framework that aligns genomic metrics with conservation impact assessments, laying the foundation for genomics-informed strategies to support species recovery.

Extinction, Biological↗

PubMed2026

Activity shapes large herbivores' ecological influences.

The ecological effects of large herbivores are shaped by their spatial and temporal patterns of activity (i.e. where, when and how intensely they use specific locations). When large herbivores' ecological influences are perceived to be undesirable, the traditional approach has been to reduce their population size. This numbers-first logic assumes that ecological effects scale primarily with abundance. We argue that this framing provides an incomplete understanding of large herbivores' ecological impacts. Using African elephants (Loxodonta africana) as a well-documented case study, we show that ecological effects on plants, animals and ecosystem processes correlate more with spatio-temporal patterns of activity than with population size. In large, open systems characterized by strong gradients of water availability, forage quality, shade and risk, elephants concentrate into predictable hotspots while relaxing activity elsewhere, generating localized impacts and opportunities for recovery. By contrast, in small, fenced or fragmented landscapes, where movements are constrained, and gradients are weak, spatial self-regulation breaks down, producing homogenized use and widespread ecological effects. We contend that understanding where, when and under what constraints herbivores use space provides a more general and mechanistic basis for interpreting ecological influence than abundance alone, with implications that extend beyond elephants to large herbivores globally.

Animals↗

PubMed2025

Pleistocene island connectivity did not enhance dispersal or impact population size change in Galápagos geckos.

Patterns of biodiversity on remote archipelagos are largely shaped by intra-archipelago colonization followed by in situ diversification. Pleistocene sea-level fluctuations purportedly enhanced gene flow among terrestrial organisms by increasing connectivity during periods of lower sea level. Furthermore, changes in sea-level are hypothesized to impact population sizes as a result of fluctuations in island sizes. Here, we used genomic data to test the role of Pleistocene island connectivity on the diversification and demographics of leaf-toed geckos (Phyllodactylus) endemic to the Galápagos. Consistent with previous studies, we found that present diversity of Galápagos Phyllodactylus stems from three independent dispersal events. Contrary to the hypothesis of Pleistocene-driven diversification, we found no correspondence between lineage divergence and island connectivity. Furthermore, we found no evidence of introgression; demographic modelling indicated that all species increased rapidly in effective population size in the period 20-150 ka, and these inferred demographic expansions were largely asynchronous and apparently unassociated with species or island age. Collectively, these results indicate that more complex abiotic and/or biotic factors may better explain the recent demographic history of Phyllodactylus and underscore the need for additional population genomic studies of terrestrial taxa to understand the impact of past climate cycles on Galápagos island communities.

Animals↗

PubMed2025

Conservation Arks: Genomic Erosion and Inbreeding in an Abundant Island Population of Koalas.

The persistence of many threatened species depends on isolated habitat patches such as conservation parks, fenced reserves, and islands. While these 'conservation arks' provide refuge from many contemporary threats, they can also pose risks of genetic diversity loss and inbreeding depression, further exacerbating extinction risk. A pertinent example is the Kangaroo Island koala population in South Australia that originated from a few translocated founding individuals in the 1920s but now sustains a large population with a low prevalence of infectious disease. We investigated the extent and consequences of founder effects on genomic diversity, inbreeding, and adaptive potential in Kangaroo Island koalas by comparing them with mainland Australian populations using high-coverage whole genomes. Our findings support sharp, recent declines in effective population sizes (Ne) in both mainland and Kangaroo Island populations. However, Kangaroo Island koalas had much lower individual and population-level diversity. Together with longer and more numerous runs of homozygosity and an increased proportion of homozygous genetic load, these results support the hypothesis that a severe bottleneck has contributed to inbreeding and maladaptation in Kangaroo Island koalas. While Kangaroo Island has the potential to conserve a viable population of koalas, we recommend genetic rescue to restore diversity and mitigate inbreeding depression in this isolated population. Our results emphasise the need for longitudinal genomic monitoring and genetic management to maintain long-term viability and resilience in potential conservation arks. Understanding the demographic history of such populations will help inform future conservation aimed at preventing genetic erosion and preserving biodiversity.

Animals↗

PubMed2024

Brood indicators are an early warning signal of honey bee colony loss-a simulation-based study.

Honey bees (Apis mellifera) are exposed to multiple stressors such as pesticides, lack of forage, and diseases. It is therefore a long-standing aim to develop robust and meaningful indicators of bee vitality to assist beekeepers While established indicators often focus on expected colony winter mortality based on adult bee abundance and honey reserves at the beginning of the winter, it would be useful to have indicators that allow detection of stress effects earlier in the year to allow for adaptive management. We used the established honey bee simulation model BEEHAVE to explore the potential of different indicators such as population size, number of capped brood cells, flight activity, abundance of Varroa mites, honey stores and a brood-bee ratio. We implemented two types of stressors in our simulations: 1) parasite pressure, i.e. sub-optimal Varroa treatment by the beekeeper (hereafter referred as Biotic stress) and 2) temporal forage gaps in spring and autumn (hereafter referred as Environmental stress). Neither stressor type could be detected by bee abundance or honey reserves at the end of the first year. However, all response variables used in this study did reveal early warning signals during the course of the year. The most reliable and useful measures seem to be related to brood and the abundance of Varroa mites at the end of the year. However, while in the model we have full access to time series of variables from stressed and unstressed colonies, knowledge of these variables in the field is challenging. We discuss how our findings can nevertheless be used to develop practical early warning indicators. As a next step in the interactive development of such indicators we suggest empirical studies on the importance of the number of capped brood cells at certain times of the year on bee population vitality.

Bees↗

PubMed2026

Proteomics-driven discovery of intervention windows and risk subtypes in osteoporosis: A prospective cohort study.

Given the limited feasibility of population-wide bone mineral density screening and the infrequency of long-term monitoring in healthy individuals, identifying the window for early intervention and the populations to be prioritized for screening is critical. This study aimed to identify intervention windows for osteoporosis and to determine potential high-risk subtypes within the healthy population. Based on proteomic data from 41,408 healthy adults, we conducted the DE-SWAN method to identify change peaks in plasma protein during the pre-diagnostic osteoporosis phase, and employed finite Gaussian mixture model-based clustering to delineate high-risk subtypes of osteoporosis. We identified 122 protein biomarkers significantly associated with osteoporosis risk throughout the follow-up period. Importantly, we identified two critical peaks occurring approximately 10 and 6 years before diagnosis, with the former enriched in immune-related pathways and the latter prominently involving responses to retinoic acid and glucocorticoids. Furthermore, one high-risk subtype for osteoporosis was identified in both males and females, termed the Frailty and Obesity Subtype. This subtype is characterized by a high degree of frailty and obesity, accompanied by a significantly elevated risk of both osteoporosis and fractures. Finally, we developed a predictive model comprising 10 proteins for identifying high-risk subtypes of osteoporosis, which demonstrated better performance than the traditional risk factor model (AUC: 0.743 vs. 0.680). Our findings demonstrate that proteomic profiling can reveal early molecular changes and identify high-risk subtypes years before clinical onset, providing a foundation for screening and precision prevention of osteoporosis.

Proteomics↗

PubMed2026

Combining ability and gene action for grain yield and biofortification traits in pearl millet [Pennisetum glaucum (L.) R. Br.]: implications for breeding high-yielding biofortified hybrids in arid regions.

Hybrid RIB-9184 × RIB-15131 combines high yield (18.84 g plant⁻¹) with iron (46.16 mg kg⁻¹), zinc (38.86 mg kg⁻¹), and protein (11.91%); Fe-Zn correlation (rg = 0.82) permits simultaneous biofortification. Pearl millet [Pennisetum glaucum (L.) R. Br., syn. Cenchrus americanus (L.) Morrone] is a climate-resilient cereal with inherently high micronutrient levels, making it a priority crop for biofortification. Understanding gene action for yield and nutritional traits is essential for designing effective breeding strategies. Ten diverse inbred lines were crossed in a half-diallel design (Griffing's Method 2, Model 1), and the 55 entries (45 F1 hybrids + 10 parents) were evaluated across two sowing-date environments in a randomised complete block design with three replications at Jaipur, Rajasthan, India. Biofortification traits (Fe, Zn, protein) showed predominantly additive gene action (Baker's ratio 0.71-0.91) with high heritability (0.90-0.94). G×E interaction was significant for Fe and Zn but genotypic variance was substantially larger, maintaining high heritability; protein showed no G×E interaction. Grain yield was governed largely by non-additive effects (Baker's ratio 0.54) with significant G×E interaction, favouring hybrid breeding. Among parents, RIB-9205 had the highest GCA for Fe (6.65, P < 0.001), RIB-9184 for Zn (3.85, P < 0.001) and protein (0.78, P < 0.001), and RIB-9185 was a balanced combiner for yield (1.39, P < 0.001) and micronutrients. The hybrid RIB-9184 × RIB-15131 ranked first across all five weighting schemes of the multi-trait performance index (1.31), combining grain yield of 18.84 g plant⁻1 with Fe of 46.16 mg kg⁻1, Zn of 38.86 mg kg⁻1, and protein of 11.91%. The strong Fe-Zn correlation (rg = 0.82, P < 0.01) permits simultaneous micronutrient improvement. An integrated approach combining hybrid development for yield with population improvement for micronutrient density is recommended for biofortified pearl millet cultivars in arid regions.

Pennisetum↗

PubMed2025

Combining QTL mapping and RNA-Seq reveals candidate genes controlling flag leaf width in foxtail millet.

BACKGROUND: The flag leaf, a crucial component of plant architecture, significantly influences final grain yield in crops, including foxtail millet (Setaria italica L.). Optimizing flag leaf size is considered an effective strategy for enhancing grain yield potential under higher planting densities. However, the genetic mechanism underlying flag leaf size, particularly flag leaf width (FLW), remains largely unknown under varying planting densities in foxtail millet. RESULTS: An FLW phenotype variation analysis was conducted across multiple planting densities using a recombinant inbred line (RIL) population derived from Heizhigu (narrow leaf) and Changnong 35 (wide leaf). Based on a high-density genetic map with 3795 Bin markers, 11 flag leaf width (FLW) QTLs were identified on chromosomes 3, 5, and 6, explaining 2.35%-36.06%. Among these, qFLW5-2 was a major QTL, detected consistently across 3 environments and explaining a large proportion of FLW variation. The QTL was further validated with 9 InDel markers with its candidate region across different planting densities. Moreover, RNA-seq revealed 2,293 and 2,338 differentially expressed genes (DEGs) between biparents at heading stage and grain filling stage, respectively. There were 11 and 9 DEGs within the location range of qFLW5-2 among 2 comparison groups (HZG-H_vs_CN35-H and HZG-G_vs_CN35-G). Combining QTL mapping and RNA-seq, we speculated that Seita.5g134600 (encoding an auxin responsive protein Aux/IAA) and Seita.5G123900 (encoding a cytochrome P450 family protein) as key candidate genes for qFLW5-2. Furthermore, variation analysis confirmed that the lines or germplasm with Seita.5G1346005UTR277+ allele, both within the RIL population and natural populations, exhibited significantly wider leaves than those with Seita.5G1346005UTR277- allele. These findings advance our understanding of the genetic and molecular regulatory mechanisms governing flag leaf growth. CONCLUSIONS: This study elucidates genetic and molecular mechanism regulating flag leaf growth and development in foxtail millet. The results provide a theoretical foundation for improving plant architecture and facilitating molecular marker-assisted breeding in this crop.

Quantitative Trait Loci↗

PubMed2025

T cell population size control by coronin 1 uncovered: from a spot identified by two-dimensional gel electrophoresis to quantitative proteomics.

INTRODUCTION: Recent work identified members of the evolutionarily conserved coronin protein family as key regulators of cell population size. This work originated ~25 years ago through the identification, by two-dimensional gel electrophoresis, of coronin 1 as a host protein involved in the virulence of Mycobacterium tuberculosis. We here describe the journey from a spot on a 2D gel to the recent realization that coronin proteins represent key controllers of eukaryotic cell population sizes, using ever more sophisticated proteomic techniques. AREAS COVERED: We discuss the value of 'old school' proteomics using relatively simple and cost-effective technologies that allowed to gain insights into subcellular proteomes and describe how label-free quantitative (phospho)proteomics using mass spectrometry allowed to disentangle the role for coronin 1 in eukaryotic cell population size control. Finally, we mention potential implications of coronin-mediated cell population size control for health and disease. EXPERT OPINION: Proteome analysis has been revolutionized by the advent of modern-day mass spectrometers and is indispensable for a better understanding of biology. Here, we discuss how careful dissection of physio-pathological processes by a combination of proteomics, genomics, biochemistry and cell biology may allow to zoom in on the unexplored, thereby possibly tackling hitherto unasked questions and defining novel mechanisms.

Proteomics↗

PubMed2026

Cross-kingdom genomic variation in chicken gut microbiomes: insights from China's diverse local breeds.

BACKGROUND: The gut microbiome possesses substantial genetic diversity that supports microbial adaptation, but the genomic variation patterns across its prokaryotic and viral populations remain incompletely characterized. RESULTS: Through integrated metagenomic and metatranscriptomic analysis of ten indigenous chicken breeds from China, we recovered 1527 representative prokaryotic MAGs, 37,555 representative DNA viral contigs, and 1867 representative RNA viral contigs (primarily comprising Bacillota/Bacteroidota, Uroviricota, and Lenarviricota/Pisuviricota, respectively). By integrating complementary short-read and long-read metagenomics with metatranscriptomics, we identified structural variants (SVs) and single-nucleotide variants (SNVs) in these cross-kingdom genomes. Positive SV-SNV density correlations occurred consistently across all microbial groups, indicating coordinated mutational processes. DNA viruses exhibited the highest variant prevalence (86.9% SNVs, 47.7% SVs), with temperate phages accumulating significantly more variants than virulent phages. Functionally, prokaryotic variants accumulated in carbohydrate metabolism and amino acid metabolism, while viral variants demonstrated broad metabolic hijacking. Horizontal gene transfer (HGT) was characterized by a strong virus-associated signature (69.40% of 536 events) and marked by an asymmetric pattern, with phage-to-bacteria (P-to-B) flow alone constituting 37.50% of all events. Random forest analysis revealed a strong bidirectional predictive relationship between SV and SNV densities across prokaryotic, DNA viral, and RNA viral populations, suggesting coupled genomic instability. Niche breadth emerged as a major driver of SNVs across kingdoms and was positively correlated with variant density. In prokaryotes, HGT events significantly shaped variant patterns. For viruses, genomic GC content was an important factor and consistently showed a negative correlation with SNV density in both DNA and RNA viruses. CONCLUSIONS: These findings demonstrate that coordinated mutational processes and kingdom-specific intrinsic factors drive genomic variation, with viruses serving as key genetic exchange vectors in chicken gut ecosystems. Video Abstract.

Animals↗

PubMed2026

Uric Acid-to-HDL Cholesterol Ratio is Associated with Hepatic Steatosis but Not Fibrosis in Nonobese Adults: A NHANES 2017-2020 Study.

BACKGROUND: Although metabolic dysfunction-associated steatotic liver disease (MASLD) has traditionally been regarded as a disease closely related to obesity, its prevalence is gradually rising in nonobese populations. The uric acid-to-high-density lipoprotein cholesterol ratio (UHR) is a novel metabolic biomarker that has been shown to be associated with MASLD. However, its role in nonobese individuals remains unclear. This study aimed to investigate the association between UHR and nonobese MASLD. METHODS: Data from the 2017 to 2020 National Health and Nutrition Examination Survey (NHANES) were analyzed. UHR was calculated as the serum uric acid (UA) divided by the high-density lipoprotein cholesterol (HDL). Liver steatosis (using controlled attenuation parameters, CAP) and fibrosis (using liver stiffness measurement, LSM) were evaluated through vibration-controlled transient elastography (VCTE). Multivariate linear regression was employed to evaluate associations. Nonlinear relationships were examined using smoothed curve fitting. RESULTS: This analysis included 3573 participants (47.41% male; aged 20-80 years). Log2-UHR was positively associated with CAP (β = 9.96, 95% CI: 6.93-12.98, P < 0.001) and MASLD prevalence (OR = 1.64, 95% CI: 1.38-1.95, P < 0.001). Subgroup analyses revealed significant interactions by sex, age, ethnicity, and smoking status (all P for interaction < 0.05), with stronger associations in females, adults aged 40-59 years, individuals of other Hispanic ethnicity, and never-smokers. Moreover, the association between log2-UHR and CAP was linear and positive (P < 0.01). No significant association was found between log2-UHR and LSM (P > 0.05). CONCLUSIONS: UHR is independently associated with hepatic steatosis but not fibrosis in nonobese US adults, suggesting its potential utility as an early risk assessment to tool. Large scale prospective studies are needed in the future to further validate the conclusions of this study.

Humans↗

PubMed2022

Genetically predicted on-statin LDL response is associated with higher intracerebral haemorrhage risk.

Statins lower low-density lipoprotein cholesterol and are widely used for the prevention of atherosclerotic cardiovascular disease. Whether statin-induced low-density lipoprotein reduction increases risk of intracerebral haemorrhage has been debated for almost two decades. Here, we explored whether genetically predicted on-statin low-density lipoprotein response is associated with intracerebral haemorrhage risk using Mendelian randomization. Using genomic data from randomized trials, we derived a polygenic score from 35 single nucleotide polymorphisms of on-statin low-density lipoprotein response and tested it in the population-based UK Biobank. We extracted statin drug and dose information from primary care data on a subset of 225 195 UK Biobank participants covering a period of 29 years. We validated the effects of the genetic score on longitudinal low-density lipoprotein measurements with generalized mixed models and explored associations with incident intracerebral haemorrhage using Cox regression analysis. Statins were prescribed at least once to 75 973 (31%) of the study participants (mean 57 years, 55% females). Among statin users, mean low-density lipoprotein decreased by 3.45 mg/dl per year [95% confidence interval (CI): (-3.47, -3.42)] over follow-up. A higher genetic score of statin response [1 standard deviation (SD) increment] was associated with significant additional reductions in low-density lipoprotein levels [-0.05 mg/dl per year, (-0.07, -0.02)], showed concordant lipidomic effects on other lipid traits as statin use and was associated with a lower risk for incident myocardial infarction [hazard ratio per SD increment 0.98 95% CI (0.96, 0.99)] and peripheral artery disease [hazard ratio per SD increment 0.93 95% CI (0.87, 0.99)]. Over a 11-year follow-up period, a higher genetically predicted statin response among statin users was associated with higher intracerebral haemorrhage risk in a model adjusting for statin dose [hazard ratio per SD increment 1.16, 95% CI (1.05, 1.28)]. On the contrary, there was no association with intracerebral haemorrhage risk among statin non-users (P = 0.89). These results provide further support for the hypothesis that statin-induced low-density lipoprotein reduction may be causally associated with intracerebral haemorrhage risk. While the net benefit of statins for preventing vascular disease is well-established, these results provide insights about the personalized response to statin intake and the role of pharmacological low-density lipoprotein lowering in the pathogenesis of intracerebral haemorrhage.

Cerebral Hemorrhage↗

PubMed2026

High-Density Genome-Wide Association Mapping Identifies Candidate Loci Associated with Maize Stalk Cell Wall Composition.

Maize (Zea mays L.) stalk cell wall composition is a key determinant of forage digestibility, lodging resistance, and biomass utilization efficiency. Although previous genome-wide association studies (GWAS) have identified loci associated with lignin (LIG), cellulose (CEL), and hemicellulose (HC), advances in genomic resources provide an opportunity to revisit existing phenotypic datasets at substantially higher resolution. Here, we re-analyzed a maize association panel consisting of 341 diverse inbred lines using an expanded genotype dataset containing 10.77 million SNPs, two derived compositional indices (CEL/HC and [LIG/(CEL + HC)], and six complementary GWAS models. Across all traits and models, we identified 855 unique significant SNPs associated with 579 candidate genes. Among the traits examined, LIG/(CEL + HC) yielded the greatest number of associations, suggesting that indices representing the relative balance among cell wall components may better capture the genetic architecture of cell wall composition than individual component measurements alone. Integration of multiple GWAS models with functional enrichment, haplotype, and selective sweep analyses prioritized three biologically relevant candidate genes encoding a MYB58 transcription factor, the glycosyltransferase Xt9, and a putative xyloglucan 6-xylosyltransferase. Haplotype analysis revealed significant effects of Xt9 and the xyloglucan 6-xylosyltransferase on cell wall composition, while selective sweep analysis identified Xt9 as a target of repeated selection during maize domestication, ecological adaptation, and modern breeding. Although these candidate genes provide promising targets for future investigation, the associations identified here are based on a single association panel and require functional and independent population validation. Collectively, our results demonstrate how high-density genotyping combined with complementary GWAS models can refine candidate associations and generate testable hypotheses from existing phenotypic datasets.

cell wall composition↗

PubMed2026

Genome-wide subgenome-resolved analysis validates chromosome 4 differentiation and prioritizes introgressed Coffea arabica accessions.

Chromosome 4 introgression in Timor hybrid-derived Coffea arabica is established, but the robustness of accession prioritization and the relative strength of cultivated-introgressed differentiation across the canephora-derived (sgC) and eugenioides-derived (sgE) subgenomes remained unclear under explicit subgenome filtering. We reanalyzed public genomic resources from 44 coffee accessions using strict contig-level subgenome filtering, Arabica-only population-structure analysis, SNP-panel sensitivity testing, genome-wide differentiation scans, permutation testing, and direct sequence alignment. Population structure and accession rankings were stable across marker densities and random seeds, and the same six introgressed references were retained throughout. Chromosome 4 ranked first in both subgenomes, with a strong sgC signal and a markedly weaker sgE signal; independent baseline-panel permutation tests supported both chromosome 4-associated signals. Direct alignment supported correspondence to the expected chromosome 4 pseudomolecules while showing incomplete source coverage and unresolved exact boundaries. Alignment-supported blocks contained 88 sgC and 62 sgE provisional defense-, signaling-, and regulatory-associated annotations. These results provide a genome-wide, quantitatively validated framework for prioritizing introgressed germplasm and candidate chromosome 4 regions for phenotype-linked coffee research without implying equivalent introgression, exact liftover, or causal resistance genes.

Coffea arabica↗

PubMed2025

Association Between Ratio of Triglycerides to HDL-C and Cognitive Impairment: A Longitudinal Population-Based Analysis and Mendelian Randomization Study.

OBJECTIVES: This study aimed to explore the longitudinal association between the triglyceride to high-density lipoprotein cholesterol (TG/HDL-C) ratio and cognitive impairment in older adults and further assess potential causality using Mendelian randomization (MR). DESIGN: Longitudinal population-based analysis combined with two-sample MR. Data from Waves 6-8 (2015-2019) of the Survey of Health, Ageing, and Retirement in Europe (SHARE) were analyzed using hierarchical regression models and mixed linear effects models. MR utilized genome-wide association studies (GWAS) summary data. PARTICIPANTS: 11,444 adults aged ≥60 years from SHARE Wave 6, with longitudinal follow-up in Waves 7 (N = 2,775) and 8 (N = 5,469). MEASUREMENTS: TG/HDL-C ratio, cognitive function (orientation, immediate/delayed recall, verbal fluency, numeracy), and cognitive impairment (defined as scores >1.5 SD below age-group mean). Covariates included socio-demographics, health behaviors, comorbidities, and national-level factors. MR employed genetic variants associated with TG/HDL-C as instrumental variables. RESULTS: Higher TG/HDL-C ratios were negatively associated with total cognitive scores (β = -0.115, χ² = 15.44, df = 1, p < 0.001), immediate recall (β = -0.029, χ² = 12.34, df = 1, p < 0.001), delayed recall (β = -0.028, χ² = 7.33, df = 1, p < 0.001), verbal fluency (β = -0.038, χ² = 11.53, df = 1, p < 0.001), and numeracy (β = -0.019, χ² = 4.55, df = 1, p < 0.05) in fully adjusted models. Longitudinal analysis revealed increased cognitive impairment risk in the highest TG/HDL-C quartile (OR=1.43, 95% CI:1.01-2.03, χ² = 9.24, df = 1) over 4 years. MR supported a causal link between elevated TG/HDL-C and cognitive decline. CONCLUSIONS: Elevated TG/HDL-C ratios are longitudinally associated with cognitive decline in older adults. Managing lipid metabolism may mitigate cognitive impairment, highlighting the importance of TG/HDL-C as a modifiable risk factor in aging populations.

Humans↗

PubMed2026

Genetic Evidence Links Sex Hormone-binding Globulin to Total Body Bone Mineral Density at Age 45-60 Years: A Two-sample Mendelian Randomization Study.

The menopausal transition and early postmenopause represent important periods for women's skeletal health, but the genetic relevance of metabolic, behavioral, and hormone-related factors to bone mineral density during midlife remains incompletely understood. This study used publicly available genome-wide association study summary statistics to examine associations between body mass index, 25-hydroxyvitamin D, sex hormone-binding globulin, high-density lipoprotein cholesterol, smoking initiation, and alcohol intake frequency and total body bone mineral density at ages 45-60 years. Exposure genome-wide association study summary statistics were derived from large European-ancestry populations and were not restricted to midlife women, whereas the outcome genome-wide association study captured an age-stratified total body bone mineral density phenotype at age 45-60 years. This age range overlaps with the menopausal transition and early postmenopause in women. Univariable, reverse, and multivariable Mendelian randomization analyses were performed, with inverse-variance weighting as the primary method and complementary sensitivity analyses used to assess heterogeneity, pleiotropy, and result stability. Genetically predicted higher sex hormone-binding globulin was associated with lower total body bone mineral density (β = -0.111, 95% CI: -0.170 to -0.051; P = 0.0003). Reverse Mendelian randomization did not support reverse causation from bone mineral density to sex hormone-binding globulin. Multivariable analyses suggested that this association persisted after adjustment for selected metabolic biomarkers. The other examined exposures did not show consistent evidence of association. These findings provide genetic evidence linking sex hormone-binding globulin to total-body bone mineral density at ages 45-60 years. Further prospective and predictive studies are needed to evaluate its clinical relevance beyond established bone health assessment tools.

Humans↗

PubMed2026

Effect of founder breeds on genotype imputation accuracy in Canchim cattle.

UNLABELLED: Genotype imputation is a technique used to infer unobserved genotypes based on reference panels, allowing increased marker density and cost-effective optimization for genomic selection. This study aimed to evaluate whether the inclusion of genotypes from the founder breeds Nelore (NE) and Charolais (CH) improves the imputation accuracy in the composite beef cattle breed Canchim (CA). The populations studied consisted of 804 NE, 897 CH, and 392 CA animals, all genotyped using high-density panels (777,962 SNP – single nucleotide polymorphisms). CA animals had their genotypes masked to simulate a medium-density panel (54,609 SNP). Fourteen imputation scenarios were evaluated, varying according to breed, sex, year of birth, and lineage. Imputation accuracy was determined based on the percentage of correctly imputed genotypes (PERC) and the squared Pearson’s correlation between observed and imputed genotypes (R2). PERC values ranged from 66.52% to 97.39% and R² from 0.6352 to 0.9780. The scenarios that included NE, CH, and CA (males or animals born before 2004) as the reference population for imputing CA females or CA animals born after 2004 showed the highest imputation accuracies. Therefore, the use of founder breeds in the reference population improves the accuracy of genotype imputation in CA cattle. The results indicate that a multibreed reference population, incorporating founder breeds, could provide a more robust and informative genetic basis for imputing composite cattle. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at https://doi.org/10.1007/s13353-026-01060-z.

Animal breeding↗