Quantitative Genetic Studies Research Articles

Deep Learning Sequence Models for Transcriptional Regulation.

Deciphering the regulatory code of gene expression and interpreting the transcriptional effects of genome variation are critical challenges in human genetics. Modern experimental technologies have resulted in an abundance of data, enabling the development of sequence-based deep learning models that link patterns embedded in DNA to the biochemical and regulatory properties contributing to transcriptional regulation, including modeling epigenetic marks, 3D genome organization, and gene expression, with tissue and cell-type specificity. Such methods can predict the functional consequences of any noncoding variant in the human genome, even rare or never-before-observed variants, and systematically characterize their consequences beyond what is tractable from experiments or quantitative genetics studies alone. Recently, the development and application of interpretability approaches have led to the identification of key sequence patterns contributing to the predicted tasks, providing insights into the underlying biological mechanisms learned and revealing opportunities for improvement in future models.

Development and characterization of novel EST-SSR markers for Gentiana straminea Maxim., a traditional Tibetan herb in China and cross-amplification in related species

Abstract Gentiana straminea Maxim. (Gentianaceae) is an important traditional Tibetan herb that is mainly distributed on the Qinghai-Tibetan Plateau. Despite its agricultural and pharmacological importance, there remains a paucity of microsatellite markers, particularly expressed sequence tag-simple sequence repeat (EST-SSR) markers, available for this local endemic species. In this study, based on previous Illumina transcriptome data of G. straminea, a total of 96 EST-SSR markers were initially designed and tested. Thirty-two of 96 loci (33.33%) were successfully amplified and verified for validation. Among them, 10 were polymorphic and had clear bands. The polymorphism information content values were 0.09–0.799, the number of alleles per locus ranged from 3 to 14, and the levels of observed and expected heterozygosity were 0.078–0.722 and 0.238–0.884, respectively, which suggested a high level of information. Moreover, cross-amplification was successful for 10 loci in two other related species, Gentiana macrophylla Pallas and Gentiana dahurica Fischer. These EST-SSR markers provide a valuable tool for investigating the genetic diversity related to quantitative traits and population genetic studies on G. straminea and related species in sect. Cruciata Gaudin.

Heritability of nervous system tumors: a sibling-based design.

The contribution of genetic and environmental factors to susceptibility to nervous system tumors remains unclear. We performed a quantitative genetic study using a sibling design to estimate the heritability of nervous system tumors, as well as the proportion of the risk of these tumors, which is attributable to environmental factors. We conducted a population-based cohort study using Swedish National Register data. All individuals born in Sweden during 1950-2010 with available information on both biological parents were included. A Multi-Generation Register was used to identify family clusters, including both full- and half-siblings. Initially, one index person was randomly selected from each cluster containing only full siblings and one sibling was randomly assigned to this index person. Subsequently, within each of the remaining clusters of full- and half-siblings, an index person was randomly selected, and a half-sibling was randomly assigned to this index person. Among the randomly selected siblings, cases of nervous system tumors were identified using the cancer registry. Quantitative genetic models were used to estimate the proportion of the variance in nervous system tumors attributable to additive genetic factors, shared environment, and individual-specific environment. The heritability of nervous system tumors was estimated to be 29% (95% confidence interval (CI) = 19%-39%), while the contribution of the non-shared environment to the variance of nervous system tumors was estimated to be 71% (95% CI = 61%-81%). The shared environmental parameter was estimated as zero in the full model. The variation in susceptibility to nervous system tumors is predominantly attributable to non-shared environmental factors, followed by genetic factors.

DArTseq-based SNP markers reveal high genetic diversity among early generation fall armyworm tolerant maize inbred lines.

Diversity analysis using molecular markers serves as a powerful tool in unravelling the intricacies of inclusivity within various populations and is an initial step in the assessment of populations and the development of inbred lines for host plant resistance in maize. This study was conducted to assess the genetic diversity and population structure of 242 newly developed S3 inbred lines using 3,305 single nucleotide polymorphism (SNP) markers and to also assess the level of homozygosity achieved in each of the inbred lines. A total of 1,184 SNP markers were found highly informative, with a mean polymorphic information content (PIC) of 0.23. Gene diversity was high among the inbred lines, ranging from 0.04 to 0.50, with an average of 0.27. The residual heterozygosity of the 242 S3 inbred lines averaged 8.8%, indicating moderately low heterozygosity levels among the inbred lines. Eighty-four percent of the 58,322 pairwise kinship coefficients among the inbred lines were near zero (0.00-0.05), with only 0.3% of them above 0.50. These results revealed that many of the inbred lines were distantly related, but none were redundant, suggesting each inbred line had a unique genetic makeup with great potential to provide novel alleles for maize improvement. The admixture-based structure analysis, principal coordinate analysis, and neighbour-joining clustering were concordant in dividing the 242 inbred lines into three subgroups based on the pedigree and selection history of the inbred lines. These findings could guide the effective use of the newly developed inbred lines and their evaluation in quantitative genetics and molecular studies to identify candidate lines for breeding locally adapted fall armyworm tolerant varieties in Ghana and other countries in West and Central Africa.

A GENETICALLY INFORMED STUDY ON THE ETIOLOGICAL ASSOCIATIONS AMONG EPIGENETIC CLOCKS

Abstract Epigenetic clocks are believed to capture the molecular footprints of biological programs that subserve innate aging processes. Although epigenetic clocks can predict disease phenotypes and mortality with a high degree of accuracy, little is known about the extent to which they capture the same (or different) developmental and maintenance mechanisms. Quantitative genetic studies may provide useful information on the etiological links between epigenetic clocks, particularly pertaining to the question of whether they are influenced by a common set of genetic and environmental factors. Using preliminary data from the Louisville Twin Study, this study used a multivariate independent pathway model to examine the shared and unique genetic and environmental influences of three epigenetic clocks (GrimAge, HannumAge, PhenoAge). Participants consisted of 43 monozygotic pairs and 30 (18 same-sex) dizygotic twin pairs with a mean age of 54.5 years (sd = 5.27). Phenotypic analyses revealed significant correlations among the clocks (r = 0.63 - 0.78). Subsequent multivariate biometric analyses showed that there were common genetic and nonshared environmental influences across all three clocks (p < 0.001), with unique genetic and nonshared environmental influences specific to GrimAge and HannumAge (p < 0.001). To examine the sources of covariation between these variables, biometric regression models were used to decompose the covariance between each of the clocks (GrimAge and Hannum, Hannum and PhenoAge, PhenoAge and GrimAge) into genetic and environmental components. These analyses revealed large, significant genetic correlations (rg = 0.80-0.86) and medium to large, significant nonshared environmental correlations (re = 0.37-0.73) among the clocks.

Genetic and context-specific effects on individual inhibitory control performance in the guppy (Poecilia reticulata).

Among-individual variation in cognitive traits, widely assumed to have evolved under adaptive processes, is increasingly being demonstrated across animal taxa. As variation among individuals is required for natural selection, characterizing individual differences and their heritability is important to understand how cognitive traits evolve. Here, we use a quantitative genetic study of wild-type guppies repeatedly exposed to a 'detour task' to test for genetic variance in the cognitive trait of inhibitory control. We also test for genotype-by-environment interactions (GxE) by testing related fish under alternative experimental treatments (transparent vs. semi-transparent barrier in the detour-task). We find among-individual variation in detour task performance, consistent with differences in inhibitory control. However, analysis of GxE reveals that heritable factors only contribute to performance variation in one treatment. This suggests that the adaptive evolutionary potential of inhibitory control (and/or other latent variables contributing to task performance) may be highly sensitive to environmental conditions. The presence of GxE also implies that the plastic response of detour task performance to treatment environment is genetically variable. Our results are consistent with a scenario where variation in individual inhibitory control stems from complex interactions between heritable and plastic components.

CaeNDR, the Caenorhabditis Natural Diversity Resource.

Studies of model organisms have provided important insights into how natural genetic differences shape trait variation. These discoveries are driven by the growing availability of genomes and the expansive experimental toolkits afforded to researchers using these species. For example, Caenorhabditis elegans is increasingly being used to identify and measure the effects of natural genetic variants on traits using quantitative genetics. Since 2016, the C. elegans Natural Diversity Resource (CeNDR) has facilitated many of these studies by providing an archive of wild strains, genome-wide sequence and variant data for each strain, and a genome-wide association (GWA) mapping portal for the C. elegans community. Here, we present an updated platform, the Caenorhabditis Natural Diversity Resource (CaeNDR), that enables quantitative genetics and genomics studies across the three Caenorhabditis species: C. elegans, C. briggsaeand C. tropicalis. The CaeNDR platform hosts several databases that are continually updated by the addition of new strains, whole-genome sequence dataand annotated variants. Additionally, CaeNDR provides new interactive tools to explore natural variation and enable GWA mappings. All CaeNDR data and tools are accessible through a freely available web portal located at caendr.org.

Dissecting the genetic architecture of root-related traits in a grafted wild Vitis berlandieri population for grapevine rootstock breeding

In woody perennial plants, quantitative genetics and association studies remain scarce for root-related traits, due to the time required to obtain mature plants and the complexity of phenotyping. In grapevine, a grafted cultivated plant, most of the rootstocks used are hybrids between American Vitis species (V. rupestris, V. riparia, and V. berlandieri). In this study, we used a wild population of an American Vitis species (V. berlandieri) to analyze the genetic architecture of the root-related traits of rootstocks in a grafted context. We studied a population consisting of 211 genotypes, with one to five replicates each (n = 846 individuals), plus four commercial rootstocks as control genotypes (110R, 5BB, Börner, and SO4). After two independent years of experimentation, the best linear unbiased estimates method revealed root-related traits with a moderate-to-high heritability (0.36–0.82) and coefficient of genetic variation (0.15–0.45). A genome-wide association study was performed with the BLINK model, leading to the detection of 11 QTL associated with four root-related traits (one QTL was associated with the total number of roots, four were associated with the number of small roots (< 1 mm in diameter), two were associated with the number of medium-sized roots (1 mm < diameter < 2 mm), and four were associated with mean diameter) accounting for up to 25.1% of the variance. Three genotypes were found to have better root-related trait performances than the commercial rootstocks and therefore constitute possible new candidates for use in grapevine rootstock breeding programs.

When will a changing climate outpace adaptive evolution?

AbstractDecades of research have illuminated the underlying ingredients that determine the scope of evolutionary responses to climate change. The field of evolutionary biology therefore stands ready to take what it has learned about influences upon the rate of adaptive evolution—such as population demography, generation time, and standing genetic variation—and apply it to assess if and how populations can evolve fast enough to “keep pace” with climate change. Here, our review highlights what the field of evolutionary biology can contribute and what it still needs to learn to provide more mechanistic predictions of the winners and losers of climate change. We begin by developing broad predictions for contemporary evolution to climate change based on theory. We then discuss methods for assessing climate‐driven contemporary evolution, including quantitative genetic studies, experimental evolution, and space‐for‐time substitutions. After providing this mechanism‐focused overview of both the evidence for evolutionary responses to climate change and more specifically, evolving to keep pace with climate change, we next consider the factors that limit actual evolutionary responses. In this context, we consider the dual role of phenotypic plasticity in facilitating but also impeding evolutionary change. Finally, we detail how a deeper consideration of evolutionary constraints can improve forecasts of responses to climate change and therefore also inform conservation and management decisions.This article is categorized under: Climate, Ecology, and Conservation &gt; Observed Ecological Changes Climate, Ecology, and Conservation &gt; Extinction Risk Assessing Impacts of Climate Change &gt; Evaluating Future Impacts of Climate Change

Single-Cell RNA Sequencing Reveals Microevolution of the Stickleback Immune System.

The risk and severity of pathogen infections in humans, livestock, or wild organisms depend on host immune function, which can vary between closely related host populations or even among individuals. This immune variation can entail between-population differences in immune gene coding sequences, copy number, or expression. In recent years, many studies have focused on population divergence in immunity using whole-tissue transcriptomics. But, whole-tissue transcriptomics cannot distinguish between evolved differences in gene regulation within cells, versus changes in cell composition within the focal tissue. Here, we leverage single-cell transcriptomic approaches to document signatures of microevolution of immune system structure in a natural system, the three-spined stickleback (Gasterosteus aculeatus). We sampled nine adult fish from three populations with variability in resistance to a cestode parasite, Schistocephalus solidus, to create the first comprehensive immune cell atlas for G. aculeatus. Eight broad immune cell types, corresponding to major vertebrate immune cells, were identified. We were also able to document significant variation in both abundance and expression profiles of the individual immune cell types among the three populations of fish. Furthermore, we demonstrate that identified cell type markers can be used to reinterpret traditional transcriptomic data: we reevaluate previously published whole-tissue transcriptome data from a quantitative genetic experimental infection study to gain better resolution relating infection outcomes to inferred cell type variation. Our combined study demonstrates the power of single-cell sequencing to not only document evolutionary phenomena (i.e., microevolution of immune cells) but also increase the power of traditional transcriptomic data sets.

MORF2-mediated plastidial retrograde signaling is involved in stress response and skotomorphogenesis beyond RNA editing.

Retrograde signaling modulates the expression of nuclear genome-encoded organelle proteins to adjust organelle function in response to environmental cues. MULTIPLE ORGANELLAR RNA EDITING FACTOR 2 (MORF2) was initially recognized as a plastidial RNA-editing factor but recently shown to interact with GUN1. Given the central role of GUN1 in chloroplast retrograde signaling and the unviable phenotype of morf2 mutants that is inconsistent with many viable mutants involved in RNA editing, we hypothesized that MORF2 has functions either dosage dependent or beyond RNA editing. Using an inducible Clustered Interspaced Short Palindromic Repeat interference (iCRISPRi) approach, we were able to reduce the MORF2 transcripts in a controlled manner. In addition to MORF2-dosage dependent RNA-editing errors, we discovered that reducing MORF2 by iCRISPRi stimulated the expression of stress responsive genes, triggered plastidial retrograde signaling, repressed ethylene signaling and skotomorphogenesis, and increased accumulation of hydrogen peroxide. These findings along with previous discoveries suggest that MORF2 is an effective regulator involved in plastidial metabolic pathways whose reduction can readily activate multiple retrograde signaling molecules possibly involving reactive oxygen species to adjust plant growth. In addition, our newly developed iCRISPRi approach provided a novel genetic tool for quantitative reverse genetics studies on hub genes in plants.

Theoretical Advances in the Ecology and Evolution of Mutualistic Interactions – Review of a Symposium (SYMP 14) Organized at ESA + CSEE 2022 Joint Meeting

Theoretical Advances in the Ecology and Evolution of Mutualistic Interactions – Review of a Symposium (<scp>SYMP</scp> 14) Organized at <scp>ESA</scp> + <scp>CSEE</scp> 2022 Joint Meeting

Integrating genealogy and dental variation: contributions to biological anthropology

AbstractGenealogical samples that couple dental data and documented relatedness information provide unique opportunities to examine the biological foundations of tooth variation. Over the past century, these resources have been critical for examining the various factors that influence dental phenotypes—the same traits that anthropologists regularly apply to reconstructions of past phenomena. Genealogical samples are uniquely suited to test long‐standing assumptions underlying bioanthropological practice, for example, biodistance and phylogenetic analysis, which commonly reference aspects of tooth size and form as proxies for latent genetic information. This article provides an overview of published genealogical research, with a focus on the practical implications of quantitative genetic and environmental studies of (non)human primate dentitions. To highlight the utility of genealogical samples for understanding the influence of specific non‐genetic factors on dental characters, we also present novel data on gestational hormone effects in opposite‐sex dizygotic twin pairs as a test of the twin testosterone transfer (TTT) hypothesis. This article discusses fruitful next steps in genealogical dental research, as well as important ethical considerations surrounding the use of associated datasets, which are sensitive in nature. As we forge ahead in an age of phenomics, genealogical samples are likely to play a key role in generating comprehensive genotype–phenotype maps of the dentition and in refining bioanthropological methods.

Discovery of malathion resistance QTL in Drosophila melanogaster using a bulked phenotyping approach.

Drosophila melanogaster has proved an effective system with which to understand the evolutionary genetics and molecular mechanisms of insecticide resistance. Insecticide use has left signatures of selection in the fly genome, and both functional and quantitative genetic studies in the system have identified genes and variants associated with resistance. Here, we use D. melanogaster and leverage a bulk phenotyping and pooled sequencing "extreme quantitative trait loci" approach to genetically dissect variation in resistance to malathion, an organophosphate insecticide. We resolve 2 quantitative trait loci, one of which implicates allelic variation at the cytochrome P450 gene Cyp6g1, a strong candidate based on previous work. The second shows no overlap with hits from a previous genome-wide association study for malathion resistance, recapitulating other studies showing that different strategies for complex trait dissection in flies can yield apparently different architectures. Notably, we see no genetic signal at the Ace gene. Ace encodes the target of organophosphate insecticide inhibition, and genome-wide association studies have identified strong Ace-linked associations with resistance in flies. The absence of quantitative trait locus implicating Ace here is most likely because our mapping population does not segregate for several of the known functional polymorphisms impacting resistance at Ace, perhaps because our population is derived from flies collected prior to the widespread use of organophosphate insecticides. Our fundamental approach can be an efficient, powerful strategy to dissect genetic variation in resistance traits. Nonetheless, studies seeking to interrogate contemporary insecticide resistance variation may benefit from deriving mapping populations from more recently collected strains.

Assisted migration is plausible for a boreal tree species under climate change: A quantitative and population genetics study of trembling aspen (Populus tremuloides Michx.) in western Canada.

A novel method was tested for improving tree breeding strategies that integrate quantitative and population genetics based on range‐wide reciprocal transplant experiments. Five reciprocal common garden tests of Populus tremuloides were investigated including 6450 trees across western Canada focusing on adaptation traits and growth. Both genetic parameters and home‐site transplant models were evaluated. We found a genetic trade‐off between growth and early spring leaf flush and late fall senescence. Coefficients of phenotypic variation (CVp) of cell lysis (CL), a measure of freezing injury, shrank from 0.28 to 0.10 during acclimation in the fall, and the CVp slope versus the freezing temperature was significantly different from zero (R 2 = 0.33, p = .02). There was more between‐population genetic variation in fall phenology than in spring leaf phenology. We suggest that P. tremuloides demonstrated a discrepancy between the ecological optimum and the physiological optimum minimum winter temperature. The sub‐optimal growing condition of P. tremuloides is potentially caused by the warmer ecological optimum than the physiological optimum. Assisted migration and breeding of fast growers to reforest cooler plantation sites can improve productivity. Transferring the study populations to less than 4°C of extreme minimum temperature appears safe for reforestation aligning with the historical recolonization direction of the species. This is equivalent to a 5–10° latitudinal northward movement. Fall frost hardiness is an effective criterion for family selection in the range tested in this study.

Genetic correlates of PCL-R psychopathy: A systematic review

Though it has been argued that courts should admit biogenetic evidence on psychopathy, no research to date has evaluated whether individuals with clinical psychopathy have consistent genetic correlates. The current study: 1) systematically reviewed all quantitative and molecular genetic studies of PCL-R psychopathy, and 2) assessed the quality and reproducibility of findings. Using PRISMA guidelines, we reviewed 1 heritability and 15 molecular genetic studies of PCL-R psychopathy. Sample characteristics, research design, and the main findings of each study were qualitatively synthesized according to candidate neurotransmitter systems. We also assessed broad metrics of study quality such as sample generalizability, accounting for environmental or clinical variability in analyses, and replication of effects. Heritability estimates for the facets of clinical psychopathy were low. Molecular genetic findings were inconsistent and mostly unreplicated. Further, replicated findings were contradictory; elevated dopamine metabolite levels observed in independent samples was qualified by a lack of association between a candidate dopamine polymorphism and PCL-R scores. Inconsistent findings may be related to issues with study quality. Though most studies had clear hypotheses and generalizable samples, few accounted for clinical complexity of those samples, environmental factors, or gene-environment interplay. The current review suggests that the genetic bases of PCL-R psychopathy are not robust enough for forensic application. Genetic findings in people with antisocial characteristics (violence, addiction, CU traits) may not generalize to those with PCL-R psychopathy. Though genetic bases for psychopathy are widely accepted, we found very little evidence for consistent genetic correlates when we systematically reviewed studies of legally relevant PCL-R psychopathy.

Association mapping across a multitude of traits collected in diverse environments in maize.

Classical genetic studies have identified many cases of pleiotropy where mutations in individual genes alter many different phenotypes. Quantitative genetic studies of natural genetic variants frequently examine one or a few traits, limiting their potential to identify pleiotropic effects of natural genetic variants. Widely adopted community association panels have been employed by plant genetics communities to study the genetic basis of naturally occurring phenotypic variation in a wide range of traits. High-density genetic marker data—18M markers—from 2 partially overlapping maize association panels comprising 1,014 unique genotypes grown in field trials across at least 7 US states and scored for 162 distinct trait data sets enabled the identification of of 2,154 suggestive marker-trait associations and 697 confident associations in the maize genome using a resampling-based genome-wide association strategy. The precision of individual marker-trait associations was estimated to be 3 genes based on a reference set of genes with known phenotypes. Examples were observed of both genetic loci associated with variation in diverse traits (e.g., above-ground and below-ground traits), as well as individual loci associated with the same or similar traits across diverse environments. Many significant signals are located near genes whose functions were previously entirely unknown or estimated purely via functional data on homologs. This study demonstrates the potential of mining community association panel data using new higher-density genetic marker sets combined with resampling-based genome-wide association tests to develop testable hypotheses about gene functions, identify potential pleiotropic effects of natural genetic variants, and study genotype-by-environment interaction.

Lipidomics-Assisted GWAS (lGWAS) Approach for Improving High-Temperature Stress Tolerance of Crops.

High-temperature stress (HT) over crop productivity is an important environmental factor demanding more attention as recent global warming trends are alarming and pose a potential threat to crop production. According to the Sixth IPCC report, future years will have longer warm seasons and frequent heat waves. Thus, the need arises to develop HT-tolerant genotypes that can be used to breed high-yielding crops. Several physiological, biochemical, and molecular alterations are orchestrated in providing HT tolerance to a genotype. One mechanism to counter HT is overcoming high-temperature-induced membrane superfluidity and structural disorganizations. Several HT lipidomic studies on different genotypes have indicated the potential involvement of membrane lipid remodelling in providing HT tolerance. Advances in high-throughput analytical techniques such as tandem mass spectrometry have paved the way for large-scale identification and quantification of the enormously diverse lipid molecules in a single run. Physiological trait-based breeding has been employed so far to identify and select HT tolerant genotypes but has several disadvantages, such as the genotype-phenotype gap affecting the efficiency of identifying the underlying genetic association. Tolerant genotypes maintain a high photosynthetic rate, stable membranes, and membrane-associated mechanisms. In this context, studying the HT-induced membrane lipid remodelling, resultant of several up-/down-regulations of genes and post-translational modifications, will aid in identifying potential lipid biomarkers for HT tolerance/susceptibility. The identified lipid biomarkers (LIPIDOTYPE) can thus be considered an intermediate phenotype, bridging the gap between genotype–phenotype (genotype–LIPIDOTYPE–phenotype). Recent works integrating metabolomics with quantitative genetic studies such as GWAS (mGWAS) have provided close associations between genotype, metabolites, and stress-tolerant phenotypes. This review has been sculpted to provide a potential workflow that combines MS-based lipidomics and the robust GWAS (lipidomics assisted GWAS-lGWAS) to identify membrane lipid remodelling related genes and associations which can be used to develop HS tolerant genotypes with enhanced membrane thermostability (MTS) and heat stable photosynthesis (HP).

Association and Familial Coaggregation of Childhood-Onset Type 1 Diabetes With Depression, Anxiety, and Stress-Related Disorders: A Population-Based Cohort Study.

OBJECTIVETo estimate the association and familial coaggregation of childhood-onset type 1 diabetes with depression, anxiety, and stress-related disorders.RESEARCH DESIGN AND METHODSThis was a population-based cohort study with use of data from Swedish nationwide registers. A total of ∼3.5 million individuals born in Sweden 1973–2007 were linked to their biological parents, full siblings and half-siblings, and cousins. Cox models were used to estimate the association and familial coaggregation of type 1 diabetes with depression, anxiety, and stress-related disorders.RESULTSIndividuals diagnosed with childhood-onset type 1 diabetes (n = 20,005) were found to be at greater risks of all outcomes: any psychiatric diagnosis (adjusted hazard ratio [aHR] 1.66 [95% CI 1.59–1.72]) or specific diagnoses of depression (1.85 [1.76–1.94]), anxiety (1.41[1.33–1.50]), and stress-related disorders (1.75 [1.62–1.89]), as well as use of antidepressants or anxiolytics (1.30 [1.26–1.34]), compared with individuals without type 1 diabetes. Overall, relatives of individuals with type 1 diabetes were at elevated risks of developing these outcomes, with the highest risks seen in parents (aHRs 1.18–1.25), followed by full siblings (aHRs 1.05–1.20), and the magnitudes of risk estimates appear proportional to familial relatedness.CONCLUSIONSThese results support existing evidence that children and adolescents with type 1 diabetes are at greater risks of developing depression, anxiety, and stress-related disorders and indicate that shared familial factors might contribute to these elevated risks. Our findings highlight the need for psychological consulting for children and their families in diabetes care. Quantitative and molecular genetic studies are warranted to further understand the etiology of these psychiatric disorders in type 1 diabetes.

Osteochondrosis (Osteochondritis Dissecans) in Lusitano Horses: Prevalence and Characteristics

Osteochondrosis (osteochondritis dissecans), OC(D), is an important joint disorder that has been studied through the years in different breeds but, to our knowledge, there are no reports of its prevalence in Lusitano horses. The aim of this study was to assess the prevalence of OC(D) in Lusitanos, define the characteristics of the disorder in this breed and compare with Spanish Purebred horses. This is a retrospective study that analysed the radiographs from the metacarpometatarsophalangeal, tarsocrural and femoropatellar joints that were taken in 302 Lusitano horses (1–12 years; obtained from 2007 until 2019). The classification of the radiographs for OC(D) was performed using a 0–4 scale and scored by three veterinarians. Radiographical evidence of OC(D) was diagnosed in 53.3% of the horses examined. Most of the findings were lesions of score 1 or 2 corresponding to flattening, (36.8%). The distal intermediate ridge of the tibia in the tarsocrural joint was the most affected predilection site (31.0%, n=187/604 joints assessed). Overall, the tarsocrural joints were more likely to be affected, followed by metatarso-metacarpophalangeal joints and finally the femoropatellar joints. The prevalence of horses with scores 3 or 4 (fragments) in any of the joints was 16.6%. A positive correlation was found between the scores of contralateral joints. We can conclude that the prevalence of OC(D) in Lusitano horses is similar to the prevalence in Spanish Purebred, but there is a lower percentage of fragmentation. The present phenotypic description can provide valuable information for further quantitative and molecular genetic studies.