Related Phenotypes Research Articles

Background: Vascular smooth muscle cells (SMC) contribute to heritable coronary artery disease (CAD) risk and undergo complex cell state transitions to multiple disease related phenotypes. To investigate the genetic basis of trajectories that underlie the SMC component of CAD causality we developed a dense timecourse single cell transcriptomic and epigenetic map of atherosclerosis in a murine disease animal model. Methods/Results: Deep multiomic profiling of aortic roots from control atherosclerosis model ( Myh11Cre ERT2 , ROSA tdT/+ , ApoE -/- ) mice with SMC specific lineage tracing on high fat diet were harvested for 7 scRNA and 6 scATAC timepoints across 16 weeks. Cellular trajectories were derived from the temporal data and probabilistic fate modeling with Waddington-Optimal Transport (WOT). We created transcription factor (TF) centered regulons mapped across the developmental timeline and through network-based prioritization with WOT predicted TFs and in silico TF perturbation, identified key drivers of cell state changes associated with epithelial-to-mesenchymal transition, vascular development, circadian clock, and hypoxia-inducible factor functions. This strategy nominated CAD gene Tcf21 as a top TF that drove early SMC transition. Parallel studies using Tcf21 SMC-knockout at 3 timepoints for scRNA and scATAC revealed the impact of Tcf21 on SMC transition molecular phenotypes and disease risk genes, due in part to a role regulating SMC cells in with secondary heart field origins and broadly altered TF accessibility. ChIPseq and proximity ligation assay in human coronary artery SMC showed TEAD1 colocalization with TCF21 across CAD risk loci to epigenetically regulate SMC transition functions, confirmed via dual luciferase reporter assays. Lastly, integration of mouse disease data with human CAD genetic findings identified the transition TF regulons that mediate disease risk and point to causal molecular mechanisms. Conclusion: We construct the first multimodal single cell course in a mouse atherosclerosis model to characterize SMC cell state changes in a disease setting. We validate the regulatory predictions from this model in vivo by perturbing CAD gene Tcf21 to discover novel epigenetic and transcriptional mechanisms which affect key SMC transition elements. Our study provides a comprehensive reference to advance our understanding of SMC cell state changes in a murine atherosclerosis model and enhance future gene regulation studies in vascular biology.

The phenotypic and genetic relationship between adolescent mental health and time spent on social media, gaming, and TV.

The distinct subpopulations in parafascicular thalamic nucleus encoding innate emotional valence.

Copy number variations (CNVs) affecting the chromosomal region 21q21.3–q22.13 are rare and have been increasingly associated with neurodevelopmental abnormalities and multisystemic manifestations. In this study, we aimed to characterize the clinical, genomic, and genotype–phenotype correlations of a Moroccan child carrying a de novo microdeletion in this region. Whole exome sequencing (WES) was performed using sequencing-by-synthesis technology on the GenoLab M platform, and CNV detection was achieved through the SeqOne platform. Variant interpretation was conducted using the Integrative Genomics Viewer (IGV), and a custom gene–phenotype heatmap was generated in R (ComplexHeatmap and pheatmap) based on OMIM, ClinVar, and DECIPHER databases to prioritize candidate genes within the deleted segment. The patient presented with global developmental delay, microcephaly, psychomotor and staturo-ponderal retardation, facial dysmorphism, epilepsy responsive to treatment, and cerebral anomalies, including passive biventricular hydrocephalus and diffuse cortical atrophy. WES-CNV analysis identified a heterozygous de novo microdeletion of approximately 8.2 Mb in 21q21.3–q22.13, encompassing 124 clinically relevant genes. Integrated analysis confirmed the pathogenicity of the deletion and highlighted genotype–phenotype correlations, particularly implicating dosage-sensitive genes such as SON and RUNX1. This case underlines the clinical utility of combining WES, CNV analysis, and phenotype-based bioinformatic tools for diagnosing complex microdeletion syndromes, contributes to understanding genotype–phenotype relationships in 21q21.3–q22.13 deletions, and supports improved clinical interpretation and patient management.

Predicting phenotypes from genomic data can significantly advance agriculture. Genomic selection, which uses genome-wide DNA markers to identify individuals with high genetic value, enhances the accuracy of breeding programs. While linear models are routinely used for genomic selection (GS), machine learning (ML) models offer complementary potential. In this study, robust ML-based models were developed to predict five phenotypic traits—three related to flowering time and two to leaf number—in Arabidopsis thaliana, a model plant with a fully sequenced genome. Using explainable artificial intelligence (XAI), specifically SHapley Additive exPlanations (SHAP) values, we identified SNPs that contributed most to trait prediction. Many of these SNPs were located in or near genes known to regulate flowering and stem elongation, such as DOG1 and VIN3, supporting the biological plausibility of the model. SHAP also enabled local interpretability at the single-plant level, revealing the genotypic basis of individual predictions. Our results indicate that integrating ML with XAI improves model interpretability and provides predictive performance comparable to traditional methods. This approach confirms known genotype–phenotype relationships and highlights new candidate loci, paving the way for functional validation. The proposed methodology offers promising applications in precision breeding and translation of insights from Arabidopsis to crop species.

Primary congenital glaucoma (PCG) is a rare genetic disorder affecting the ocular drainage system, accounting for only 0.01-0.04% blindness related cases. However, its prevalence varies significantly in ethnicities, being higher in populations that practice consanguinity, such as Pakistan where approximately 70% of marriages are consanguineous. This study aimed to investigate the genetic cause of PCG in a large Pakistani family with autosomal recessive inheritance. A large multigenerational family having multiple consanguineous marriages resulting in fifteen affected individuals was recruited for the current study. All relevant clinical information was collected and venous blood drawn for further genetic analysis. The family was subjected to direct sequencing of CYP1B1 which is the most plausible candidate of PCG. The resulting candidate variant was further confirmed using BanII restriction enzyme analysis. The sequence analysis revealed a novel indel (c.862delinsCC) in exon 2 of the CYP1B1 gene, resulting in a frameshift mutation (p.Ala288Profs*39) thereby creating a premature stop codon 39 amino acids downstream. BanII restriction enzyme analysis further confirmed this putative null mutation co-segregating with the disease trait in all the family members of the pedigree. The novel indel, putative null mutation causes PCG related disease phenotypes. This genetic variant has a high penetrance but shows variable expressivity among the affected members of the family. This putative null mutation enhances the mutation spectrum of CYP1B1 globally and from Pakistan in particular.

Abstract Background and Aims Autosomal recessive polycystic kidney disease (ARPKD) is a rare inherited disease that affects 1:20,000 children globally. The disease is characterised by progressive cystic kidney disease and liver fibrosis, with variable presentation even between related individuals. ARPKD is most commonly caused by mutations in polycystic kidney and hepatic disease 1 (PKHD1), with only a few familial cases being linked to other genes. Although most cases of ARPKD will feature mutations in PKHD1, there is considerable clinical variability in the presentation of the disease. Many patients will present with severe kidney and liver disease. Some patients will present with severe disease in one of the two organs or mild disease in both. Efforts to address relationships between genotype and phenotype have so far only highlighted a relationship between patients with dual stop gain variants and severe presentations of ARPKD, linked to perinatal/neonatal death. A complication of linking mutations to disease severity in ARPKD is that, outside of a few founder and hotspot mutations, most families have a unique combination of PKHD1 mutations. To elucidate relationships between genotype and phenotype, this project has sought to use machine learning to highlight relationships between variant position and disease presentation. It aims to predict disease outcomes in ARPKD patients, allowing for the prioritisation of high-risk candidates for limited resources, such as organ transplants. Method A database of patient variant combinations (genotype) and disease outcomes (phenotype) was created from existing literature on PKHD1 mutations using available resources and data from journals published in the period 2003 – 2022. Machine learning was applied to the disease outcomes to identify relationships between genotype and phenotype. Data from published resources (2010 – 2020) and the AregPKD database was used as test data. The program AlphaFold, developed by Google's DeepMind, was used to estimate the 3D structure of the PKHD1 protein Fibrocystin (FPC) using the UseGalaxy.eu servers. Domain predictions were performed using the FoldSeek webserver. Variant combinations from the genotype—phenotype database was compared to the 3D structure to highlight relationships between protein structure and disease outcomes. Results AlphaFold predicted the complete 4,074 amino acid protein Fibrocystin. Regions linked to the homology predicted structures (IPT, PA14, PBH and G8 domains) with high (pLDDT >70) confidence. The region encompassing the most prolific ARPKD mutation (T36M) and the intracellular tail were predicted with low confidence (pLDDT <50). Comparing the 3D structure to known protein structures suggests similarities to human Fibrillin-2 (E-value = 0.00e+0), Laminin subunit alpha-1 (E = 0.00e+0) and Nesprin-2 (E = 3.72e−76), two of which are proteins involved in either migration, cell organisation or the actin cytoskeleton. Other structural similarity involved the human TMEM2 ectodomains (E-value = 2.97e−21), calmodulin-binding transcription activator 1 (E = 2.79e−2) and mouse Plexin A1 extracellular domains (E = 5.27e−9). Conclusion AlphaFold has been useful in predicting the tertiary structure of FPC confirming the structural domains previously highlighted by homologous modelling. Additionally, AlphaFold has been useful in highlighting potential functional activities of FPC by comparing it to the tertiary structure of other known proteins. Future work will involve mapping previously reported disease-causing variants in PKHD1 to highlight a relationship between the tertiary structure of FPC and disease outcomes. Additionally, a categorical model will be trained on previously reported mutation combinations to further define genotype–phenotype relationships.

PITPNM3 has been identified as a crucial gene associated with various phenotypes of retinal disease in humans; however, detailed mechanisms through which PITPNM3 mutations result in these conditions are not fully understood. In this study, we aimed to generate such a preclinical mouse model and evaluate its relevance to human PITPNM3-related conditions. Heterozygous mice were bred to obtain a homozygous genotype, aiming to mimic the human genetic condition. Subsequent phenotyping and genetic segregation analyses were conducted along with electrophysiological studies and histological examinations. Full-field electroretinogram analysis revealed a reduced cone response although the severity was not as pronounced as observed in humans with PITPNM3-related conditions. Histologically, the retinal structure appeared largely unchanged, indicating a discordance between functional impairment and morphological changes. In our preclinical mouse model, the observed phenotypic changes were not as severe as those found in humans with PITPNM3-related conditions and this discrepancy points to a potentially different disease progression trajectory in the mouse model. These findings highlight the importance of longer follow-up periods in such studies and the need for further research to elucidate the genotype–phenotype relationship in PITPNM3.

Novelty-seeking (NS) refers to the tendency of humans and animals to explore novel and unfamiliar stimuli and environments. It is a core feature of Attention Deficit Hyperactivity Disorder (ADHD) and associated with multiple psychiatric disorders. Recent researches indicated that NS behavior has an effect on reward-related learning. The hippocampus is a core brain region linked to reward-related learning and memory. However, how the hippocampal proteome modulates NS behavior remain largely elusive. In current study, we identified 165 differentially expressed proteins in the hippocampus between high and low novelty response mice with mass-spectrometry-based proteomics. Among these proteins, the over-expression of Tenascin-R (TNR) in high novelty response mice was verified with Western Blot and Immunofluorescence imaging. Moreover, systematic genetic analysis based on the BXD strains showed the expression of TNR is genetically cis-regulation. Further, gene co-expression analysis revealed that TNR has a negative connection with the expression of dopamine receptor D2 (DRD2) (P = 0.003, r = -0.298). And the knockdown of TNR enhanced the expression of DRD2 in vitro. Finally, we constructed a correlation network to exhibit the links among TNR gene variant, expression of TNR and DRD2, and NS related behaviors. Our study provides a novel hippocampal biomarker with preliminary insights into its association with the dopaminergic synaptic pathway. ROC analysis further confirms TNR's robust discriminatory power for distinguishing novel open field behavior, a key NS - related phenotype, which may be a new strategy for diagnosis of NS-related traits.

BackgroundDiabetes mellitus (DM) and coronary artery disease (CAD) are closely interrelated clinical conditions. However, the combination analysis based on DM related CAD diagnostic model remains a gap. The primary objective of this study was to identify diagnostic models and diagnostic markers for CAD based on the association of diabetic phenotypes and attempt to explore them further in a mouse model.MethodsWe used data integration as well as multiple datasets for both coronary artery disease and diabetes to exclude bias as well as to improve reliability. We employed the least absolute shrinkage and selection operator (LASSO) regression algorithms to construct the CAD diagnostic model. Furthermore, we established mouse CAD model (low-density lipoprotein receptor deficient mice with high fat diet) to explore the crosstalk between the screened biomarkers and severe CAD progress.ResultsThe intersecting genes from differential analysis and weighted correlation network analysis (WGCNA) results yielded 32 diabetes-related biomarkers. We then identified two diabetes-related phenotypes through the consensus clustering in CAD patients. Microenvironmental analysis revealed that phenotype 1 exhibited higher expression of most cytokines, inflammatory factors, interleukins, and related receptors. Immune cell composition in phenotype 1 showed increased infiltration compared to phenotype 2. The LASSO regression identified 16 diabetes-related genes and we further constructed a diagnostic model based on these genes, which the area under the curve (AUC) reached 0.8. Additionally, single cell immune analysis exhibited the location of these genes. KCNQ1, ATP6V1B1, MTDH, and ITPK1 were predominantly located in macrophages, indicating their potential in regulating macrophage during myocardial injury. Furthermore, We elucidated that KCNQ1 and ITPK1 exhibited high expression level in mouse CAD model in tissue level. exhibited similar expression trends with macrophage biomarkers (CD31 and CD68). The result of qPCR also indicated the elevated level of KCNQ1 and ITPK1, which exhibited crosstalk with CD31 and CD68 in mouse CAD model.ConclusionThis study delves into the microenvironmental characteristics of diabetes-related phenotypes in CAD, constructing an optimal diagnostic model and validated the significance of diagnostic markers in mouse CAD model, which may offer insights that could be beneficial for clinical management in the near future.

The role of immune cells in diabetic retinopathy (DR) is unclear. This study aims to assess the causal effect of various immune cells on DR by Mendelian randomization (MR). Immune cell datasets were acquired from European Bioinformatics Institute, and a DR dataset was acquired in FinnGen. Single nucleotide polymorphisms were screened stepwise according to the assumptions of association, independence, and exclusivity. Inverse variance weighted was used as the main method for MR analysis. MR-Egger was used to assess the horizontal pleiotropy of the results. Cochran Q and leave-one-out methods were respectively used for heterogeneity and sensitivity of the results. MR analysis identified 11 immune cell phenotypes associated with an increased genetic susceptibility to DR: T cell related phenotypes included CD4 on resting Treg, CD4/CD8br, CD28+ CD45RA− CD8dim AC, and CD28− CD25++ CD8br %T cell; NKT cell related phenotypes included CD8br NKT AC and CD3 on NKT; Dendritic cell related phenotypes included CD80 on plasmacytoid DC, CD62L+ plasmacytoid DC, and myeloid DC; The monocyte related phenotype was HLA DR on CD33br HLA DR+ CD14−; and the myeloid cell related phenotype was CD33− HLA DR− AC. No horizontal pleiotropy was observed (P ≥ .05). Cochran Q showed no heterogeneity in the results except for CD8br NKT AC (P < .001) and HLA DR on CD33br HLA DR+ CD14− (P = .002). Sensitivity analysis showed the results were robust. The MR analysis revealed 11 immune cell phenotypes associated with an increased genetic susceptibility to DR. These findings provide a new perspective on the pathogenesis and drug development of DR.

BackgroundMitochondrial diseases are a group of serious inherited multisystem disorders caused by mutations in mitochondrial DNA (mtDNA) or nuclear DNA and still have faced a significant challenge to therapy due to their complicated genotype–phenotype relationships and diverse clinical manifestations. Human induced pluripotent stem cell (hiPSC) offered novel opportunities for cell-based modeling mitochondrial diseases in a patient-specific level. This study aims to explore possibility to potential strategy against mutation-associated oxidative damage through hiPSCs derived from mitochondrial diseases patients.MethodsA human induced pluripotent stem cell line (mt-hiPSCs) from a patient harboring 70.70% heteroplasmic m.3243A>G mutation was established and exposed to hydrogen peroxide (H₂O₂). The cell viability, apoptosis level and mitochondrial function were measured through CCK-8, western blot, flow cytometry, RT-qPCR, fluorescence staining and compared to wild-type hiPSCs. Thereafter, the participation of mitogen-activated protein kinases (MAPK) pathway in the melatonin-mediated protection against H₂O₂-induced oxidative injury was also evaluated.ResultsUnder prolonged low-dose hydrogen peroxide (H₂O₂) exposure, mt-hiPSCs showed significantly reduced viability, elevated apoptosis (52.13 vs. 25.62% in wild-type hiPSCs, P < 0.001), and exacerbated mitochondrial dysfunction, including superoxide accumulation and membrane potential depolarization. Melatonin pretreatment effectively mitigated H₂O₂-induced damage, restoring cell viability, reducing lactate dehydrogenase release, and suppressing apoptosis by normalizing BAX/BCL2 ratios and CASPASE-3 activation. Moreover, melatonin preserved mitochondrial fusion dynamics (MFN1) and respiratory chain integrity (COX IV), counteracting H₂O₂-induced abnormalities. Mechanistically, mt-hiPSCs displayed hyperactivation of MAPK signaling (p-p38, p-ERK, p-JNK) under oxidative stress, which was attenuated by melatonin. Consistently, administration of the MAPK inhibitor SB203580 further confirmed that melatonin’s protective effects are closely associated with modulation of MAPK pathway activity in mt-hiPSCs exposed to oxidative stress.ConclusionsThese findings highlight the vulnerability of m.3243A>G mutant cells to oxidative stress and demonstrate melatonin’s therapeutic potential in alleviating mitochondrial dysfunction via MAPK pathway modulation. This study provides a patient-derived model for exploring mitochondrial disorders and identifies melatonin as a promising cytoprotective agent against mutation-associated oxidative damage.Supplementary InformationThe online version contains supplementary material available at 10.1186/s13287-025-04666-y.

ABSTRACTIntroductionHaloacetic acids (HAAs) are water disinfection byproducts (DBPs) regulated as a mixture of five species (HAA5) in the United States and Canada. To date, two brominated HAAs (BrHAAs) in HAA5 (monobromoacetic acid [MBAA], dibromoacetic acid [DBAA]) have been associated with birth defects in some epidemiologic studies, but the other four unregulated BrHAAs remain understudied.MethodsWe analyzed registry‐based case–control data on 16 birth defect phenotypes in relation to temporally weighted first‐trimester exposures to the four unregulated BrHAAs (tribromoacetic acid [TBAA], bromochloroacetic acid [BCAA], bromodichloroacetic acid [BDCAA], chlorodibromoacetic acid [CDBAA]) and the sum of all six BrHAAs (HAA6 = TBAA + BCAA + BDCAA + CDBAA + MBAA + DBAA). We matched cases to controls 1:10 on the week of conception and estimated adjusted odds ratios (aORs) via conditional logistic regression.ResultsWe observed some elevated aORs for dichotomized BrHAA exposures with certain outcomes, such as cleft palate alone (BDCAA aOR = 1.75 [95% confidence interval: 1.15, 2.66]), ventricular septal defects (BDCAA aOR = 1.28 [0.97, 1.68]), tetralogy of Fallot (BDCAA OR = 1.57 [0.93, 2.64]), and obstructive genitourinary defects (CDBAA aOR = 1.65 [1.07, 2.53]), and reduced aORs for hypospadias (e.g., BCAA aOR = 0.58 [0.40, 0.84]). Most other associations were closer to the null, and many lacked precision.ConclusionOur observations warrant further investigation given their novelty and the paucity of data on health impacts of prenatal BrHAA exposures overall; ours is the first epidemiological study to investigate most of these exposure‐outcome relationships. Future work would benefit from a longer study period to ascertain additional birth defect cases and more direct exposure assessment in areas served by water systems with higher bromide levels.

Epigenetic mechanisms, including DNA methylation, histone modification, and activity of noncoding RNAs (nc RNAs), affect the regulation of gene expression. These mechanisms are regulated by numerous environmental factors and are critical at specific windows of biological development, when organs and systems plasticity is increased. Evidence suggests that exposure to factors influencing these mechanisms may have an effect on health, including the risk for obesity at early stages of life. This study analyzed published evidence on the association between epigenetic mechanisms and childhood obesity. We searched for studies using untargeted detection methods followed by validation of associations between epigenetic mechanisms and obesity in children. Fifteen studies were found: two meta-analyses on DNA methylation, seven original studies on DNA methylation, one systematic review on microRNAs, and five studies on nc RNA. No studies on histone modifications were identified. Most studies were conducted in blood cells or blood-derived fluids. DNA methylation in different tissues was associated with childhood and adolescent obesity or related phenotypes, although comparison across studies is difficult due to technical differences. Nc RNA differed between children with and without obesity. Research on the role of factors regulating epigenetic mechanisms associated with childhood obesity is highly needed.

ABSTRACTThis beginner's guide is intended for plant biologists new to network analysis. Here, we introduce key concepts and resources for researchers interested in incorporating network analysis into research, either as a stand‐alone component for generating hypotheses or as a framework for examining and visualizing experimental results. Network analysis provides a powerful tool to predict gene functions. Advances in and reduced costs for systems biology techniques, such as genomics, transcriptomics, and proteomics, have generated abundant omics data for plants; however, the functional annotation of plant genes lags. Therefore, predictions from network analysis can be a starting point to annotate genes and ultimately elucidate genotype–phenotype relationships. In this paper, we introduce networks and compare network‐building resources available for plant biologists, including databases and software for network analysis. We then compare four databases available for plant biologists in more detail: AraNet, GeneMANIA, ATTED‐II, and STRING. AraNet and GeneMANIA are functional association networks, ATTED‐II is a gene coexpression database, and STRING is a protein–protein interaction database. AraNet and ATTED‐II are plant‐specific databases that can analyze multiple plant species, whereas GeneMANIA builds networks for Arabidopsis thaliana and nonplant species and STRING for multiple species. Finally, we compare the performance of the four databases in predicting known and probable gene functions of the A. thaliana Nuclear Factor‐Y (NF‐Y) genes. We conclude that plant biologists have an invaluable resource in these databases and discuss how users can decide which type of database to use depending on their research question.

Glioblastoma (GBM) exhibits profound resistance to CD8⁺ T cell-mediated killing, yet the tumor-intrinsic mechanisms driving this immune evasion remain poorly defined. Our earlier study revealed Checkpoint Kinase 2 (Chek2) as the driver of CD8+ T cell resistance. This study investigates the immunomodulatory program exerted by the CHK2-YBX1&YBX3 regulatory hub. Protein-protein interactions were investigated through immunoprecipitation (IP) followed by mass spectrometry (MS) and phosphoproteomics. Single gene knockout of CHEK2, Y-box-binding protein 1 (YBX1), and Y-box-binding protein 3 (YBX3) were generated in human and mouse glioma cells. Transcriptomic and epigenetic alterations were characterized by bulk RNA sequencing and chromatin immunoprecipitation sequencing (ChIP-seq). Single-cell RNA sequencing and spatial transcriptomics analysis were performed to evaluate CHK2-YBX1&YBX3 related phenotype in human GBM tumors. In vivo survival studies were conducted to assess the therapeutic potential of CHK2-YBX1&YBX3 degradation and immune checkpoint blockade (ICB). CHK2, YBX1, and YBX3 exhibited reciprocal positive regulation and depletion of any of these genes resulted in derepression of pro-inflammatory gene expression. Pharmacological inhibition with the drug targeting YBX1 led to degradation of the CHK2-YBX1&YBX3 hub accompanied by enhanced antigen presentation and antigen-specific CD8⁺ T cell proliferation. Combination therapy targeting CHK2-YBX1&YBX3 hub and ICB significantly improved survival in preclinical glioma models. These findings define a novel glioma-intrinsic immunosuppressive program and proposes targeting the CHK2-YBX1&YBX3 hub to potentiate response to ICB in glioma.

BackgroundPathogenic variants of the bone morphogenetic protein receptor type 1 A (BMPR1A) gene underlie juvenile polyposis syndrome (JPS), a rare autosomal dominant condition characterized by multiple gastrointestinal hamartomatous polyps. Recent findings indicate that constitutional BMPR1A variants can also be associated with various non-JPS phenotypes without hamartomatous polyps. The basis of varying genotype - phenotype relationships is poorly understood.MethodsWe investigated four families with non-truncating variants of BMPR1A affecting different functional domains. Clinical presentation resembled familial colorectal cancer type X-like syndrome with dominantly inherited microsatellite-stable gastrointestinal adenomas and carcinomas. To gain insights into genotype-phenotype associations, exome sequencing was conducted on normal and tumor tissue DNAs. Constitutional BMPR1A variants underwent a thorough evaluation for clinical significance, by, e.g., co-segregation analyses and in silico modeling, supplemented by haplotyping and genealogical studies. All available tumors were examined for histology and molecularly for BMPR1A “second hits” and mutational signatures.ResultsTargeted sequencing of blood DNA revealed a three-nucleotide deletion (BMPR1A c.264_266 del) in one family, a three-nucleotide insertion (BMPR1A c.506_507insTCC) in two families, and a missense change (BMPR1A c.766G > A) in a fourth family. The two families with BMPR1A c.506_507insTCC had a shared ancestral origin. Co-segregation of the variants with colorectal cancer and/or polyps, in-silico modeling, and two hit inactivation by loss of heterozygosity or somatic point mutations in tumors, together with the absence of other possible predisposing variants by exome sequencing, supported the idea of tumor predisposition being attributable to the BMPR1A variants. Polyps examined from variant carriers had adenomatous histology, except for three polyps with hamartomatous features, originating from two BMPR1A carriers from two families. While no hamartoma samples were available for molecular investigation, somatic mutational profiles of colorectal adenomas and carcinomas resembled those of mismatch repair-proficient colorectal tumors in general.ConclusionsOur findings support the notion that the clinical phenotype of BMPR1A variants may extend beyond classical JPS. Genotype-phenotype correlations are complex, since molecular comparison of constitutional and tumor features of our families to those published from JPS families in the literature show a significant overlap. The variety of clinical phenotypes warrants recognition in the clinical management of BMPR1A carriers and their family members.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12885-025-14865-8.

Genetic association studies have demonstrated that partial loss of SLC30A8 Function protects against type 2 diabetes in humans. We investigated the impact of complete loss of SLC30A8 Function on type 2 diabetes risk and related phenotypes in humans. The Pakistan Genome Resource (PGR), a biobank comprising whole-exome and whole-genome sequences of 145,037 participants, was analysed for phenotypic associations with SLC30A8 loss-of-function (LoF) variants. To follow up on the observations in the PGR, we conducted recall-by-genotype analyses of SLC30A8 LoF heterozygotes and homozygotes, as well as their participating family members, using OGTTs. We identified 18 SLC30A8 knockouts, including homozygotes for a variant enriched in South Asians (Gln174Ter), and 1024 heterozygotes for LoF variants. Type 2 diabetes risk was lower in SLC30A8 LoF heterozygotes and homozygotes relative to non-carriers, and the protective effect strengthens in a gene dose-dependent manner (ORadditive=0.62; 95% CI 0.53, 0.72; p=1.1×10-9; ORrecessive=0.34; 95% CI 0.12, 0.93; p=0.04). OGTTs in recall-by-genotype studies showed a gene dose-dependent reduction in glucose levels, coupled with elevated insulin. The corrected insulin response, disposition index and insulin sensitivity index in LoF heterozygotes and homozygotes indicated higher glucose-stimulated insulin secretion with preserved beta cell function that was independent of BMI. These data suggest that therapeutic inhibition of SLC30A8, up to and including complete knockout, may treat type 2 diabetes safely and effectively.

BackgroundImproving immune competence (IC) in livestock could reduce the incidence of disease and reliance on the use of antibiotics. In Australian Angus cattle, IC is a measure of an animal’s combined ability to mount antibody and cell-mediated immune responses (AMIR and CMIR). Immune competence may affect traits such as growth and related phenotypes as well as the variability of such phenotypes. However, the genetic relationship between IC and genetic sensitivity to individual environments, measured as micro-genetic environmental sensitivity (GES), is yet to be reported. In this study the genetic parameters of, and correlations between, AMIR or CMIR and micro-GES of live weaning weight (WW) and ultrasound scan records of rib (RIB) and rump (RUMP) fat depth and eye muscle area (EMA) measured between 501 and 900 days of age were estimated. This was accomplished by fitting eight multivariate models with AMIR or CMIR and a double hierarchical generalised linear model on a production trait.ResultsThe heritabilities were 0.35 and 0.36 for AMIR and CMIR, respectively, and 0.25–0.70 for the production traits. The heritabilities and the genetic coefficient of variation of micro-GES of the production traits ranged from 0.01–0.04 and 18–82%, respectively, and were higher in RIB and RUMP than WW and EMA. The genetic correlations between AMIR and WW, RIB, RUMP, or EMA were -0.35 (SE 0.11), 0.11 (0.12), 0.06 (0.12) and -0.13 (0.12), respectively, while the genetic correlations between CMIR and WW, RIB, RUMP, or EMA were -0.26 (0.12), 0.15 (0.13), 0.16 (0.12) and 0.04 (0.13), respectively. The genetic correlations between IC and micro-GES of WW, RIB, RUMP or EMA were moderately negative to lowly positive and had large SEs rendering them non-significant.ConclusionsThe unfavourable genetic correlation between the IC traits and WW supports the hypothesis that mounting an effective immune response can direct resources away from growth when resources are limited. Based on the heritabilities and genetic coefficient of variation of micro-GES, selection to increase uniformity is possible for WW, RIB, RUMP and EMA. The standard errors of the genetic correlations between IC and micro-GES of the production traits were too large to draw any definite conclusions about their relationships. Standard errors are expected to reduce as more IC records are collected.Supplementary InformationThe online version contains supplementary material available at 10.1186/s12711-025-00998-8.

Suicidality phenotypes, consisting of suicidal ideation (SI), suicide attempt (SA), and suicide death (SD), are all heritable but present unique challenges in genome-wide association studies (GWAS) due to their individual complexity, overlap with each other and with related self-harm phenotypes, and varying associations with psychiatric disorders. GWAS have uncovered several loci associated with suicidality phenotypes by meta-analyzing data from multiple cohorts. However, combining datasets from many research groups, where each group may use different study designs, phenotyping instruments, and definitions of suicidality phenotypes, presents challenges. Heterogeneity resulting from these differences can limit genetic discovery; harmonizing phenotype definitions to ensure consistency will greatly improve results. Here, we describe a standardized phenotyping protocol that draws on the expertise of a subgroup of clinicians, researchers, and experts from the Psychiatric Genomics Consortium Suicide Working Group to propose consensus definitions for SI, SA, and SD for genetic studies.