Novel genetic loci of inhibitory control in ADHD and healthy children and genetic correlations with ADHD

Cumulative evidence has showed the deficits of inhibitory control in patients with attention deficit hyperactivity disorder (ADHD), which is considered as an endophenotype of ADHD. Genetic study of inhibitory control could advance gene discovery and further facilitate the understanding of ADHD genetic basis, but the studies were limited in both the general population and ADHD patients. To reveal genetic risk variants of inhibitory control and its potential genetic relationship with ADHD, we conducted genome-wide association studies (GWAS) on inhibitory control using three datasets, which included 783 and 957 ADHD patients and 1350 healthy children. Subsequently, we employed polygenic risk scores (PRS) to explore the association of inhibitory control with ADHD and related psychiatric disorders. Firstly, we identified three significant loci for inhibitory control in the healthy dataset, two loci in the case dataset, and one locus in the meta-analysis of three datasets. Besides, we found more risk genes and variants by applying transcriptome-wide association study (TWAS) and conditional FDR method. Then, we constructed a network by connecting the genes identified in our study, leading to the identification of several vital genes. Lastly, we identified a potential relationship between inhibitory control and ADHD and autism by PRS analysis and found the direct and mediated contribution of the identified genetic loci on ADHD symptoms by mediation analysis. In conclusion, we revealed some genetic risk variants associated with inhibitory control and elucidated the benefit of inhibitory control as an endophenotype, providing valuable insights into the mechanisms underlying ADHD.

A variant in the 5'UTR of ERBB4 is associated with lifespan in Golden Retrievers

Genome-wide association studies (GWAS) in long-lived human populations have led to identification of variants associated with Alzheimer's disease and cardiovascular disease, the latter being the most common cause of mortality in people worldwide. In contrast, naturally occurring cancer represents the leading cause of death in pet dogs, and specific breeds like the Golden Retriever (GR) carry up to a 65% cancer-related death rate. We hypothesized that GWAS of long-lived GRs might lead to the identification of genetic variants capable of modifying longevity within this cancer-predisposed breed. A GWAS was performed comparing GR dogs ≥ 14 years to dogs dying prior to age 12 which revealed a significant association to ERBB4, the only member of the epidermal growth factor receptor family capable of serving as both a tumor suppressor gene and an oncogene. No coding variants were identified, however, distinct haplotypes in the 5'UTR were associated with reduced lifespan in two separate populations of GR dogs. When all GR dogs were analyzed together (n = 304), the presence of haplotype 3 was associated with shorter survival (11.8 years vs. 12.8 years, p = 0.024). GRs homozygous for haplotype 3 had the shortest survival, and GRs homozygous for haplotype 1 had the longest survival (11.6 years vs. 13.5 years, p = 0.0008). Sub-analyses revealed that the difference in lifespan for GRs carrying at least 1 copy of haplotype 3 was specific to female dogs (p = 0.009), whereas survival remained significantly different in both male and female GRs homozygous for haplotype 1 or haplotype 3 (p = 0.026 and p = 0.009, respectively). Taken together, these findings implicate a potential role for ERBB4 in GR longevity and provide evidence that within-breed canine lifespan studies could serve as a mechanism to identify favorable or disease-modifying variants important to the axis of aging and cancer.

Genomic insights into glume pubescence in durum wheat: GWAS and haplotype analysis implicates TdELD1-1A as a candidate gene

Glume pubescence is an important morphological trait for the characterization of wheat cultivars. It shows tolerance to biotic and abiotic stresses to some extent. Hg1 (formerly named Hg) locus on chromosome 1AS controls glume pubescence in wheat. Its genetic analysis, fine-mapping and candidate gene analysis have been widely studied recently, however, the cloning of Hg1 has not yet been reported. Here, we conducted a GWAS between a dense panel of 171,103 SNPs and glume pubescence (Gp) in a durum wheat population of 145 lines, and further analyzed the candidate genes of Hg1 combined with the gene expression, functional annotation, and haplotype analysis. As a results, TRITD0Uv1G104670 (TdELD1-1A), encoding glycosyltransferase-like ELD1/KOBITO 1, was detected as the most promising candidate gene of Hg1 for glume pubescence in durum wheat. Our findings not only contribute to a deeper understanding of its cloning and functional validation but also underscore the significance of accurate genome sequences and annotations. Additionally, our study highlights the relevance of unanchored sequences in chrUn and the application of bioinformatics analysis for gene discovery in durum wheat.

Circulating cytokines and vascular dementia: A bi-directional Mendelian randomization study

Inflammatory responses are associated with the development of vascular dementia (VaD). Circulating cytokines modulate the inflammatory response and are important for the immune system. To further elucidate the role of the immune system in VaD, we used Mendelian randomization (MR) to comprehensively and bi-directionally assess the role of circulating cytokines in VaD. Using state-of-the-art genome-wide association studies, we primarily assessed whether different genetic levels of 41 circulating cytokines affect the risk of developing VaD and, in turn, whether the genetic risk of VaD affects these circulating cytokines. We used inverse variance weighting (IVW) and several other MR methods to assess the bidirectional causality between circulating cytokines and VaD, and performed sensitivity analyses. Tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) was inversely associated with VaD risk [odds ratio (OR): 0.74, 95 % confidence interval (CI): 0.60-0.92, P = 0.007, 0.007]. VaD was associated with seven circulating cytokines: macrophage inflammatory protein 1b (MIP-1 beta) [OR: 1.05, 95 % CI: 1.01-1.08, P = 0.009], Interleukin-12p70 (IL-12) [OR: 1.04, 95 % CI: 1.00-1.08, P = 0.047], Interleukin-17 (IL-17) [OR: 1.04, 95 % CI: 1.00-1.07, P = 0.038], Interleukin-7 (IL-7) [OR: 1.07, 95 % CI: 1.02-1.12, P = 0.009], Interferon gamma (IFN-γ) [OR: 1.03, 95 % CI: 1.00-1.07, P = 0.046], Granulocyte-colony stimulating factor (GCSF) [OR: 1.06, 95 % CI: 1.02-1.09, P = 0.001], Fibroblast growth factor (FGF) [P = 0.001], and Fibroblast growth factor (FGF) [P = 0.001]. Fibroblast growth factor basic (FGF-Basic) [OR: 1.04, 95 % CI: 1.01-1.08, P = 0.02] were positively correlated. Circulating cytokines are associated with VaD, and further studies are needed to determine whether they are effective targets for intervention to prevent or treat VaD.

Causal relationships between circulating inflammatory cytokines and diabetic neuropathy: A Mendelian Randomization study

BACKGROUND

Emerging evidence suggests systemic inflammation as a critical mechanism underlying diabetic neuropathy. This study aimed to investigate the causal relationship between 41 circulating inflammatory cytokines and diabetic neuropathy.

METHODS

Summary statistics from previous Genome-Wide Association studies (GWAS) included pooled data on 41 inflammatory cytokines and diabetic neuropathy. A two-sample Mendelian Randomization (MR) design was employed, and the robustness of the results was confirmed through comprehensive sensitivity analyses.

RESULTS

Our study reveals that the linkage between increased levels of IFN_G (OR = 1.31, 95 %CI: 1.06-1.63; P = 0.014), IP_10 (OR = 1.18, 95 %CI: 1.01-1.36; P = 0.031) and an elevated risk of diabetic neuropathy. Conversely, higher levels of IL_9 (OR = 0.86, 95 %CI: 0.75-1.00; P = 0.048) and SCF (OR = 0.83, 95 %CI: 0.73-0.94; P = 0.003) are genetically determined to protect against diabetic neuropathy. Furthermore, the sensitivity analysis affirmed the results' dependability, revealing no heterogeneity or pleiotropy.

CONCLUSION

Our MR research identified four upstream inflammatory cytokines implicated in diabetic neuropathy. Overall, these findings suggest the potential for innovative therapeutic strategies. Further large-scale cohort studies are required for validation.

Genome-Wide Analyses of Vocabulary Size in Infancy and Toddlerhood: Associations With Attention-Deficit/Hyperactivity Disorder, Literacy, and Cognition-Related Traits

BACKGROUND

The number of words children produce (expressive vocabulary) and understand (receptive vocabulary) changes rapidly during early development, partially due to genetic factors. Here, we performed a meta-genome-wide association study of vocabulary acquisition and investigated polygenic overlap with literacy, cognition, developmental phenotypes, and neurodevelopmental conditions, including attention-deficit/hyperactivity disorder (ADHD).

METHODS

We studied 37,913 parent-reported vocabulary size measures (English, Dutch, Danish) for 17,298 children of European descent. Meta-analyses were performed for early-phase expressive (infancy, 15-18 months), late-phase expressive (toddlerhood, 24-38 months), and late-phase receptive (toddlerhood, 24-38 months) vocabulary. Subsequently, we estimated single nucleotide polymorphism-based heritability (SNP-h2) and genetic correlations (rg) and modeled underlying factor structures with multivariate models.

RESULTS

Early-life vocabulary size was modestly heritable (SNP-h2 = 0.08-0.24). Genetic overlap between infant expressive and toddler receptive vocabulary was negligible (rg = 0.07), although each measure was moderately related to toddler expressive vocabulary (rg = 0.69 and rg = 0.67, respectively), suggesting a multifactorial genetic architecture. Both infant and toddler expressive vocabulary were genetically linked to literacy (e.g., spelling: rg = 0.58 and rg = 0.79, respectively), underlining genetic similarity. However, a genetic association of early-life vocabulary with educational attainment and intelligence emerged only during toddlerhood (e.g., receptive vocabulary and intelligence: rg = 0.36). Increased ADHD risk was genetically associated with larger infant expressive vocabulary (rg = 0.23). Multivariate genetic models in the ALSPAC (Avon Longitudinal Study of Parents and Children) cohort confirmed this finding for ADHD symptoms (e.g., at age 13; rg = 0.54) but showed that the association effect reversed for toddler receptive vocabulary (rg = -0.74), highlighting developmental heterogeneity.

CONCLUSIONS

The genetic architecture of early-life vocabulary changes during development, shaping polygenic association patterns with later-life ADHD, literacy, and cognition-related traits.

Genome-wide association study (GWAS) identified PCOS susceptibility variants and replicates reported risk variants

BACKGROUND

Genetic predisposition and environmental factors are considered risk factors for polycystic ovary syndrome (PCOS). Genome-wide association studies (GWAS) have been reported from various subpopulations to evaluate SNPs associated with PCOS risk. No PCOS-associated GWAS study has been reported from India so far.

PURPOSE

The current study was conducted to identify the PCOS-susceptible loci among the North Indian population and to validate the significant loci reported by previous GWAS studies.

METHODS

A total of 272 participants with 134 PCOS patients and 138 age-matched healthy controls were recruited. Genomic DNA was isolated and genotyped by using Infinium Global Screening Array v3.0 microchip considering HWE 10e-5 statistically significant.

RESULTS

A total of fifteen markers have been identified as candidate PCOS risk factors. Only two SNPs, namely rs17186366 and rs11171739 have been identified through replication analysis while comparing the previously reported PCOS GWAS data. In-silico analysis was performed to study the functional impact of identified significant genes for gene ontology, pathways related to gene set, and cluster analysis to determine protein-protein interaction among genes or gene products.

CONCLUSION

The study suggests that multiple variants play an important role in PCOS pathogenesis and emphasizes the importance of further genetic studies among Indian subpopulations. The study also validates two previously reported SNPs in the Indian population. What this study adds to clinical work Study summarizes the importance of candidate gene markers validated by replication and in-silico functional study, significantly involved in PCOS pathogenesis in the studied population. These markers can be used in the future as diagnostic markers for clinical phenotype identification.

Natural variation in CYCLIC NUCLEOTIDE-GATED ION CHANNEL 4 reveals a novel role of calcium signaling in vegetative phase change in Arabidopsis

The timing of vegetative phase change (VPC) in plants is regulated by a temporal decline in the expression of miR156. Both exogenous cues and endogenous factors, such as temperature, light, sugar, nutrients, and epigenetic regulators, have been shown to affect VPC by altering miR156 expression. However, the genetic basis of natural variation in VPC remains largely unexplored. Here, we conducted a genome-wide association study on the variation of the timing of VPC in Arabidopsis. We identified CYCLIC NUCLEOTIDE-GATED ION CHANNEL 4 (CNGC4) as a significant locus associated with the diversity of VPC. Mutations in CNGC4 delayed VPC, accompanied by an increased expression level of miR156 and a corresponding decrease in SQUAMOSA PROMOTER BINDING-LIKE (SPL) gene expression. Furthermore, mutations in CNGC2 and CATION EXCHANGER 1/3 (CAX1/3) also led to a delay in VPC. Polymorphisms in the CNGC4 promoter contribute to the natural variation in CNGC4 expression and the diversity of VPC. Specifically, the early CNGC4 variant promotes VPC and enhances plant adaptation to local environments. In summary, our findings offer genetic insights into the natural variation in VPC in Arabidopsis, and reveal a previously unidentified role of calcium signaling in the regulation of VPC.

Using the Bayesian variational spike and slab model in a genome-wide association study for finding associated loci with bipolar disorder

OBJECTIVE

The genome-wide association studies (GWAS) analysis, the most successful technique for discovering disease-related genetic variation, has some statistical concerns, including multiple testing, the correlation among variants (single-nucleotide polymorphisms) based on linkage disequilibrium and omitting the important variants when fitting the model with just one variant. To eliminate these problems in a small sample-size study, we used a sparse Bayesian learning model for finding bipolar disorder (BD) genetic variants.

METHODS

This study used the Wellcome Trust Case Control Consortium data set, including 1998 BD cases and 1500 control samples, and after quality control, 380,628 variants were analysed. In this GWAS, a Bayesian logistic model with hierarchical shrinkage spike and slab priors was used, with all variants considered simultaneously in one model. In order to decrease the computational burden, an alternative inferential method, Bayesian variational inference, has been used.

RESULTS

Thirteen variants were selected as associated with BD. The three of them (rs7572953, rs1378850 and rs4148944) were reported in previous GWAS. Eight of which were related to hemogram parameters, such as lymphocyte percentage, plateletcrit and haemoglobin concentration. Among selected related genes, GABPA, ELF3 and JAM2 were enriched in the platelet-derived growth factor pathway. These three genes, along with APP, ARL8A, CDH23 and GPR37L1, could be differential diagnostic variants for BD.

CONCLUSIONS

By reducing the statistical restrictions of GWAS analysis, the application of the Bayesian variational spike and slab models can offer insight into the genetic link with BD even with a small sample size. To uncover related variations with other traits, this model needs to be further examined.

The effects of case/control ratio and sample size on genome-wide association studies: A simulation study

BACKGROUND

Genome-wide association studies (GWAS) is a useful tool for the detection of disease or quantitative trait-related genetic variations in the veterinary field. For a binary trait, a case/control experiment is designed in GWAS. However, there is limited information on the optimal case/control and sample size in GWAS.

OBJECTIVES

In this study, it was aimed to detect the effects of case/control ratio and sample size for GWAS using computer simulation under certain assumptions.

METHOD

Using the PLINK software, we simulated three different disease scenarios. In scenario 1, we simulated 10 different case/control ratios with increasing ratio of cases to controls. In scenario 2, we did versa of scenario 1 with the increasing ratio of controls to cases. In scenarios 1 and 2, sample size gradually was increased with the change case/control ratios. In scenario 3, the total sample size was fixed to 2000 to see real effects of case/control ratio on the number of disease-related single nucleotide polymorphisms (SNPs).

RESULTS

The results showed that the number of disease-related SNPs were the highest when the case/control ratio is close to 1:1 in scenarios 1 and 2 and did not change with an increase in sample size. Similarly, the number of disease-related SNPs was the highest in case/control ratios 1:1 in scenario 3. However, unbalanced case/control ratio caused the detection of lower number of disease-related SNPs in scenario 3. The estimated average power of SNPs was highest when case/control ratio is 1:1 in all scenarios.

CONCLUSIONS

All findings led to the conclusion that an increase in sample size may enhance the statistical power of GWAS when the number of cases is small. In addition, case/control ratio 1:1 may be the optimal ratio for GWAS. These findings may be valuable not only for veterinary field but also for human clinical experiments.

Genetics may affect the risk of undergoing surgery for rhizarthrosis

Osteoarthritis is a prevalent and severe disease. Involvement of the trapeziometacarpal joint is common and can lead to both pain and disability. Genetics are known to affect the risk of osteoarthritis, but it remains unclear how genetics affect disease trajectories. In this study, we investigated whether the genetic associations of trapeziometacarpal osteoarthritis (rhizarthrosis) vary with the need for surgical treatment. The study was conducted as a case-control genome-wide association study using individuals from the Copenhagen Hospital Biobank pain and degenerative musculoskeletal disease study and the Danish Blood Donor Study (N = 208,342). We identified patients diagnosed with rhizarthrosis and grouped them by treatment status, resulting in two case groups: surgical (N = 1083) and nonsurgical (N = 1888). The case groups were tested against osteoarthritis-free controls in two genome-wide association studies. We then compared variants suggestive of association (p < 10-6) in either of these analyses directly between the treatment groups (surgical vs. nonsurgical rhizarthrosis). We identified 10 variants suggestive of association with either surgical (seven variants) or nonsurgical (three variants) rhizarthrosis. None of the variants reached nominal significance in the opposite treatment group (p ≥ 0.14), and all 10 variants were significantly different between the treatment groups at a false discovery rate of 5%. These results suggest possible differences in the genetic associations of rhizarthrosis depending on surgical treatment. Clinical significance: Uncovering genetic differences between clinically distinct patient groups can reveal biological determinants of disease trajectories.

Multi-omics identification of a key glycosyl hydrolase gene FtGH1 involved in rutin hydrolysis in Tartary buckwheat (Fagopyrum tataricum)

Rutin, a flavonoid rich in buckwheat, is important for human health and plant resistance to external stresses. The hydrolysis of rutin to quercetin underlies the bitter taste of Tartary buckwheat. In order to identify rutin hydrolysis genes, a 200 genotypes mini-core Tartary buckwheat germplasm resource was re-sequenced with 30-fold coverage depth. By combining the content of the intermediate metabolites of rutin metabolism with genome resequencing data, metabolite genome-wide association analyses (GWAS) eventually identified a glycosyl hydrolase gene FtGH1, which could hydrolyse rutin to quercetin. This function was validated both in Tartary buckwheat overexpression hairy roots and in vitro enzyme activity assays. Mutation of the two key active sites, which were determined by molecular docking and experimentally verified via overexpression in hairy roots and transient expression in tobacco leaves, exhibited abnormal subcellular localization, suggesting functional changes. Sequence analysis revealed that mutation of the FtGH1 promoter in accessions of two haplotypes might be necessary for enzymatic activity. Co-expression analysis and GWAS revealed that FtbHLH165 not only repressed FtGH1 expression, but also increased seed length. This work reveals a potential mechanism behind rutin metabolism, which should provide both theoretical support in the study of flavonoid metabolism and in the molecular breeding of Tartary buckwheat.

Are some children genetically predisposed to poor sleep? A polygenic risk study in the general population

BACKGROUND

Twin studies show moderate heritability of sleep traits: 40% for insomnia symptoms and 46% for sleep duration. Genome-wide association studies (GWAS) have identified genetic variants involved in insomnia and sleep duration in adults, but it is unknown whether these variants affect sleep during early development. We assessed whether polygenic risk scores for insomnia (PRS-I) and sleep duration (PRS-SD) affect sleep throughout early childhood to adolescence.

METHODS

We included 2,458 children of European ancestry (51% girls). Insomnia-related items of the Child Behavior Checklist were reported by mothers at child's age 1.5, 3, and 6 years. At 10-15 years, the Sleep Disturbance Scale for Children and actigraphy were assessed in a subsample (N = 975). Standardized PRS-I and PRS-SD (higher scores indicate genetic susceptibility for insomnia and longer sleep duration, respectively) were computed at multiple p-value thresholds based on largest GWAS to date.

RESULTS

Children with higher PRS-I had more insomnia-related sleep problems between 1.5 and 15 years (BPRS-I < 0.001 = .09, 95% CI: 0.05; 0.14). PRS-SD was not associated with mother-reported sleep problems. A higher PRS-SD was in turn associated with longer actigraphically estimated sleep duration (BPRS-SD < 5e08 = .05, 95% CI: 0.001; 0.09) and more wake after sleep onset (BPRS-SD < 0.005 = .25, 95% CI: 0.04; 0.47) at 10-15 years, but these associations did not survive multiple testing correction.

CONCLUSIONS

Children who are genetically predisposed to insomnia have more insomnia-like sleep problems, whereas those who are genetically predisposed to longer sleep have longer sleep duration, but are also more awake during the night in adolescence. This indicates that polygenic risk for sleep traits, based on GWAS in adults, affects sleep already in children.

Bone health index in the assessment of bone health: The Generation R Study

Bone Health Index (BHI) has been proposed as a useful instrument for assessing bone health in children. However, its relationship with fracture risk remains unknown. We aimed to investigate whether BHI is associated with bone mineral density (BMD) and prevalent fracture odds in children from the Generation R Study. We also implemented genome-wide association study (GWAS) and polygenic score (PGS) approaches to improve our understanding of BHI and its potential. In total, 4150 children (49.4 % boys; aged 9.8 years) with genotyped data and bone assessments were included in this study. BMD was measured across the total body (less head following ISCD guidelines) using a GE-Lunar iDXA densitometer; and BHI was determined from the hand DXA scans using BoneXpert®. Fractures were self-reported collected with home questionnaires. The association of BHI with BMD and fractures was evaluated using linear models corrected for age, sex, ethnicity, height, and weight. We observed a positive correlation between BHI and BMD (ρ = 0.32, p-value<0.0001). Further, every SD decrease in BHI was associated with an 11 % increased risk of prevalent fractures (OR:1.11, 95 % CI 1.00-1.24, p-value = 0.05). Our BHI GWAS identified variants (lead SNP rs1404264-A, p-value = 2.61 × 10-14) mapping to the ING3/CPED1/WNT16 locus. Children in the extreme tails of the BMD PGS presented a difference in BHI values of -0.10 standard deviations (95% CI -0.14 to -0.07; p-value<0.0001). On top of the demonstrated epidemiological association of BHI with both BMD and fracture risk, our results reveal a partially shared biological background between BHI and BMD. These findings highlight the potential value of using BHI to screen children at risk of fracture.

Cerebral small vessel disease increases risk for epilepsy: a Mendelian randomization study

BACKGROUND

Despite previous research suggesting a potential association between cerebral small vessel disease (CSVD) and epilepsy, the precise causality and directionality between cerebral small vessel disease (CSVD) and epilepsy remain incompletely understood. We aimed to investigate the causal link between CSVD and epilepsy.

METHOD

A bidirectional two-sample Mendelian randomization (MR) analysis was performed to evaluate the causal relationship between CSVD and epilepsy. The analysis included five dimensions of CSVD, namely small vessel ischemic stroke (SVS), intracerebral hemorrhage (ICH), white matter damage (including white matter hyperintensity [WMH], fractional anisotropy, and mean diffusivity), lacunar stroke, and cerebral microbleeds. We also incorporated epilepsy encompassing both focal epilepsy and generalized epilepsy. Inverse variance weighted (IVW) was used as the primary estimate while other four MR techniques were used to validate the results. Pleiotropic effects were controlled by adjusting vascular risk factors through multivariable MR.

RESULT

The study found a significant association between SVS (odds ratio [OR] 1.117, PFDR = 0.022), fractional anisotropy (OR 0.961, PFDR = 0.005), mean diffusivity (OR 1.036, PFDR = 0.004), and lacunar stroke (OR 1.127, PFDR = 0.007) with an increased risk of epilepsy. The aforementioned correlations primarily occurred in focal epilepsy rather than generalized epilepsy on subgroup analysis and retained their significance in the multivariable MR analysis.

CONCLUSION

Our study demonstrated that genetic susceptibility to CSVD independently elevates the risk of epilepsy, especially focal epilepsy. Diffusion tensor imaging may help screen patients at high risk for epilepsy in CSVD. Improved management of CSVD may be a significant approach in reducing the overall prevalence of epilepsy.

Genetics of immune response to Epstein-Barr virus: prospects for multiple sclerosis pathogenesis

Epstein-Barr virus (EBV) infection has been advocated as a prerequisite for developing multiple sclerosis (MS) and possibly the propagation of the disease. However, the precise mechanisms for such influences are still unclear. A large-scale study investigating the host genetics of EBV serology and related clinical manifestations, such as infectious mononucleosis (IM), may help us better understand the role of EBV in MS pathogenesis. This study evaluates the host genetic factors that influence serological response against EBV and history of IM and cross-evaluates them with MS risk and genetic susceptibility in the Swedish population. Plasma IgG antibody levels against EBV nuclear antigen-1 (EBNA-1, truncated=aa[325-641], peptide=aa[385-420]) and viral capsid antigen p18 (VCAp18) were measured using bead-based multiplex serology for 8744 MS cases and 7229 population-matched controls. The MS risk association for high/low EBV antibody levels and history of IM was compared to relevant clinical measures along with sex, age at sampling, and associated HLA allele variants. Genome-wide and HLA allele association analyses were also performed to identify genetic risk factors for EBV antibody response and IM history. Higher antibody levels against VCAp18 (OR=1.74, 95% CI=1.60-1.88) and EBNA-1, particularly the peptide (OR=3.13, 95% CI=2.93-3.35), were associated with an increased risk for MS. The risk increased with higher anti-EBNA-1 IgG levels up to twelve times the reference risk. We also identified several independent HLA haplotypes associated with EBV serology overlapping with known MS risk alleles (e.g., DRB1*15:01). Although there were several candidates, no variants outside the HLA region reached genome-wide significance. Cumulative HLA risk for anti-EBNA-1 IgG levels, particularly the peptide fragment, was strongly associated with MS. In contrast, the genetic risk for high anti-VCAp18 IgG levels was not as strongly associated with MS risk. IM history was not associated with class II HLA genes but negatively associated with A*02:01, which is protective against MS. Our findings emphasize that the risk association between anti-EBNA-1 IgG levels and MS may be partly due to overlapping HLA associations. Additionally, the increasing MS risk with increasing anti-EBNA-1 levels would be consistent with a pathogenic role of the EBNA-1 immune response, perhaps through molecular mimicry. Given that high anti-EBNA-1 antibodies may reflect a poorly controlled T-cell defense against the virus, our findings would be consistent with DRB1*15:01 being a poor class II antigen in the immune defense against EBV. Lastly, the difference in genetic control of IM supports the independent roles of EBNA-1 and IM in MS susceptibility.

Assessing causal relationships between gut microbiota and psoriasis: evidence from two sample Mendelian randomization analysis

Mounting data hints that the gut microbiota's role may be pivotal in understanding the emergence of psoriasis. However, discerning a direct causal link is yet elusive. In this exploration, we adopted a Mendelian randomization (MR) strategy to probe the prospective causal interplay between the gut's microbial landscape and the predisposition to psoriasis. Genetic markers acting as instrumental variables for gut microbiota were extrapolated from a genome-wide association study (GWAS) encompassing 18,340 individuals. A separate GWAS yielded summary data for psoriasis, which covered 337,159 patients and 433,201 control subjects. The primary analysis hinged on inverse variance weighting (IVW). Additional methods like the weighted median approach and MR-Egger regression were employed to validate the integrity of our findings. Intriguing correlations emerged between psoriasis risk and eight specific bacterial traits. To illustrate: Mollicutes presented an odds ratio (OR) of 1.003 with a 95% confidence interval (CI) spanning 1.001-1.005 (p = 0.016), while the family. Victivallaceae revealed an OR of 0.998 with CI values between 0.997 and 0.999 (p = 0.023). Eubacterium (coprostanoligenes group) revealed an OR of 0.997 with CI values between 0.994 and 0.999 (p = 0.027). Eubacterium (fissicatena group) revealed an OR of 0.997 with CI values between 0.996 and 0.999 (p = 0.005). Holdemania revealed an OR of 1.001 with CI values 1-1.003 (p = 0.034). Lachnospiraceae (NK4A136 group) revealed an OR of 0.997 with CI values between 0.995 and 0.999 (p = 0.046). Lactococcus revealed an OR of 0.998 with CI values between 0.996 and 0.999 (p = 0.008). Tenericutes revealed an OR of 1.003 with CI values between 1.001 and 1.006 (p = 0.016). Sensitivity analysis for these bacterial features yielded congruent outcomes, reinforcing statistically significant ties between the eight bacterial entities and psoriasis. This comprehensive probe underscores emerging evidence pointing towards a plausible causal nexus between diverse gut microbiota and the onset of psoriasis. It beckons further research to unravel the intricacies of how the gut's microbial constituents might sway psoriasis's pathogenesis.

Multi-trait GWAS for diverse ancestries: mapping the knowledge gap

BACKGROUND

Approximately 95% of samples analyzed in univariate genome-wide association studies (GWAS) are of European ancestry. This bias toward European ancestry populations in association screening also exists for other analyses and methods that are often developed and tested on European ancestry only. However, existing data in non-European populations, which are often of modest sample size, could benefit from innovative approaches as recently illustrated in the context of polygenic risk scores.

METHODS

Here, we extend and assess the potential limitations and gains of our multi-trait GWAS pipeline, JASS (Joint Analysis of Summary Statistics), for the analysis of non-European ancestries. To this end, we conducted the joint GWAS of 19 hematological traits and glycemic traits across five ancestries (European (EUR), admixed American (AMR), African (AFR), East Asian (EAS), and South-East Asian (SAS)).

RESULTS

We detected 367 new genome-wide significant associations in non-European populations (15 in Admixed American (AMR), 72 in African (AFR) and 280 in East Asian (EAS)). New associations detected represent 5%, 17% and 13% of associations in the AFR, AMR and EAS populations, respectively. Overall, multi-trait testing increases the replication of European associated loci in non-European ancestry by 15%. Pleiotropic effects were highly similar at significant loci across ancestries (e.g. the mean correlation between multi-trait genetic effects of EUR and EAS ancestries was 0.88). For hematological traits, strong discrepancies in multi-trait genetic effects are tied to known evolutionary divergences: the ARKC1 loci, which is adaptive to overcome p.vivax induced malaria.

CONCLUSIONS

Multi-trait GWAS can be a valuable tool to narrow the genetic knowledge gap between European and non-European populations.

Human genetic associations of the airway microbiome in chronic obstructive pulmonary disease

Little is known about the relationships between human genetics and the airway microbiome. Deeply sequenced airway metagenomics, by simultaneously characterizing the microbiome and host genetics, provide a unique opportunity to assess the microbiome-host genetic associations. Here we performed a co-profiling of microbiome and host genetics with the identification of over 5 million single nucleotide polymorphisms (SNPs) through deep metagenomic sequencing in sputum of 99 chronic obstructive pulmonary disease (COPD) and 36 healthy individuals. Host genetic variation was the most significant factor associated with the microbiome except for geography and disease status, with its top 5 principal components accounting for 12.11% of the microbiome variability. Within COPD individuals, 113 SNPs mapped to candidate genes reported as genetically associated with COPD exhibited associations with 29 microbial species and 48 functional modules (P < 1 × 10-5), where Streptococcus salivarius exhibits the strongest association to SNP rs6917641 in TBC1D32 (P = 9.54 × 10-8). Integration of concurrent host transcriptomic data identified correlations between the expression of host genes and their genetically-linked microbiome features, including NUDT1, MAD1L1 and Veillonella parvula, TTLL9 and Stenotrophomonas maltophilia, and LTA4H and Haemophilus influenzae. Mendelian randomization analyses revealed a potential causal link between PARK7 expression and microbial type III secretion system, and a genetically-mediated association between COPD and increased relative abundance of airway Streptococcus intermedius. These results suggest a previously underappreciated role of host genetics in shaping the airway microbiome and provide fresh hypotheses for genetic-based host-microbiome interactions in COPD.

The genomic basis of nitrogen utilization efficiency and trait plasticity to improve nutrient stress tolerance in cultivated sunflower

Maintaining crop productivity is challenging as population growth, climate change, and increasing fertilizer costs necessitate expanding crop production to poorer lands whilst reducing inputs. Enhancing crops' nutrient use efficiency is thus an important goal, but requires a better understanding of related traits and their genetic basis. We investigated variation in low nutrient stress tolerance in a diverse panel of cultivated sunflower genotypes grown under high and low nutrient conditions, assessing relative growth rate (RGR) as performance. We assessed variation in traits related to nitrogen utilization efficiency (NUtE), mass allocation, and leaf elemental content. Across genotypes, nutrient limitation generally reduced RGR. Moreover, there was a negative correlation between vigor (RGR in control) and decline in RGR in response to stress. Given this trade-off, we focused on nutrient stress tolerance independent of vigor. This tolerance metric correlated with the change in NUtE, plasticity for a suite of morphological traits, and leaf element content. Genome-wide associations revealed regions associated with variation and plasticity in multiple traits, including two regions with seemingly additive effects on NUtE change. Our results demonstrate potential avenues for improving sunflower nutrient stress tolerance independent of vigor, and highlight specific traits and genomic regions that could play a role in enhancing tolerance.

Pharmacogenomics-based systematic review of coronary artery disease based on personalized medicine procedure

Background

Coronary artery disease (CAD) is the most common reason for mortality and disability-adjusted life years (DALYs) lost globally. This study aimed to suggest a new gene list for the treatment of CAD by a systematic review of bioinformatics analyses of pharmacogenomics impacts of potential genes and variants.

Methods

PubMed search was filtered by the title including Coronary Artery Disease during 2020-2023. To find the genes with pharmacogenetic impact on the CAD, additional filtrations were considered according to the variant annotations. Protein-Protein Interactions (PPIs), Gene-miRNA Interactions (GMIs), Protein-Drug Interactions (PDIs), and variant annotation assessments (VAAs) performed by STRING-MODEL (ver. 12), Cytoscape (ver. 3.10), miRTargetLink.2., NetworkAnalyst (ver 0.3.0), and PharmGKB.

Results

Results revealed 5618 publications, 1290 papers were qualified, and finally, 650 papers were included. 4608 protein-coding genes were extracted, among them, 1432 unique genes were distinguished and 530 evidence-based repeated genes remained. 71 genes showed a pharmacogenetics-related variant annotation in at least (entirely 6331 annotations). Variant annotation assessment (VAA) showed 532 potential variants for the final report, and finally, the concluding PGs list represented 175 variants. Based on the function and MAF, 57 nonsynonymous variants of 29 Pharmacogenomics-related genes were associated with CAD.

Conclusion

Conclusively, evaluating circulating miR33a in individuals' plasma with CAD, and genotyping of rs2230806, rs2230808, rs2487032, rs12003906, rs2472507, rs2515629, and rs4149297 (ABCA1 variants) lead to precisely prescribing of well-known drugs. Also, the findings of this review can be used in both whole-genome sequencing (WGS) and whole-exome sequencing (WES) analysis in the prognosis and diagnosis of CAD.

Genome-wide association study identified five quantitative trait loci and two candidate genes for digestive traits in Suhuai pigs

This work aimed to identify markers and candidate genes underlying porcine digestive traits. In total, 331 pigs were genotyped by 80 K Chip data or 50 K Chip data. For apparent neutral detergent fiber digestibility, a total of 19 and 21 candidate single nucleotide polymorphisms (SNP) were respectively identified using a genome-wide efficient mixed-model association algorithm and linkage-disequilibrium adjusted kinship. Among them, three quantitative trait locus (QTL) regions were identified. For apparent acid detergent fiber digestibility, a total of 16 and 17 SNPs were identified by these two methods, respectively. Of these, three QTL regions were also identified. Moreover, two candidate genes (MST1 and LATS1), which are functionally related to intestinal homeostasis and health, were detected near these significant SNPs. Taken together, our results could provide a basis for deeper research on digestive traits in pigs.

Hierarchical joint analysis of marginal summary statistics-Part I: Multipopulation fine mapping and credible set construction

Recent advancement in genome-wide association studies (GWAS) comes from not only increasingly larger sample sizes but also the shift in focus towards underrepresented populations. Multipopulation GWAS increase power to detect novel risk variants and improve fine-mapping resolution by leveraging evidence and differences in linkage disequilibrium (LD) from diverse populations. Here, we expand upon our previous approach for single-population fine-mapping through Joint Analysis of Marginal SNP Effects (JAM) to a multipopulation analysis (mJAM). Under the assumption that true causal variants are common across studies, we implement a hierarchical model framework that conditions on multiple SNPs while explicitly incorporating the different LD structures across populations. The mJAM framework can be used to first select index variants using the mJAM likelihood with different feature selection approaches. In addition, we present a novel approach leveraging the ideas of mediation to construct credible sets for these index variants. Construction of such credible sets can be performed given any existing index variants. We illustrate the implementation of the mJAM likelihood through two implementations: mJAM-SuSiE (a Bayesian approach) and mJAM-Forward selection. Through simulation studies based on realistic effect sizes and levels of LD, we demonstrated that mJAM performs well for constructing concise credible sets that include the underlying causal variants. In real data examples taken from the most recent multipopulation prostate cancer GWAS, we showed several practical advantages of mJAM over other existing multipopulation methods.

Scoary2: rapid association of phenotypic multi-omics data with microbial pan-genomes

Unraveling bacterial gene function drives progress in various areas, such as food production, pharmacology, and ecology. While omics technologies capture high-dimensional phenotypic data, linking them to genomic data is challenging, leaving 40-60% of bacterial genes undescribed. To address this bottleneck, we introduce Scoary2, an ultra-fast microbial genome-wide association studies (mGWAS) software. With its data exploration app and improved performance, Scoary2 is the first tool to enable the study of large phenotypic datasets using mGWAS. As proof of concept, we explore the metabolome of yogurts, each produced with a different Propionibacterium reichii strain and discover two genes affecting carnitine metabolism.

A noncoding regulatory variant in IKZF1 increases acute lymphoblastic leukemia risk in Hispanic/Latino children

Hispanic/Latino children have the highest risk of acute lymphoblastic leukemia (ALL) in the US compared to other racial/ethnic groups, yet the basis of this remains incompletely understood. Through genetic fine-mapping analyses, we identified a new independent childhood ALL risk signal near IKZF1 in self-reported Hispanic/Latino individuals, but not in non-Hispanic White individuals, with an effect size of ∼1.44 (95% confidence interval = 1.33-1.55) and a risk allele frequency of ∼18% in Hispanic/Latino populations and <0.5% in European populations. This risk allele was positively associated with Indigenous American ancestry, showed evidence of selection in human history, and was associated with reduced IKZF1 expression. We identified a putative causal variant in a downstream enhancer that is most active in pro-B cells and interacts with the IKZF1 promoter. This variant disrupts IKZF1 autoregulation at this enhancer and results in reduced enhancer activity in B cell progenitors. Our study reveals a genetic basis for the increased ALL risk in Hispanic/Latino children.

Genetic correlation and Mendelian randomization analyses support causal relationships between dietary habits and age at menarche

Dietary habits are essential in the mean age at menarche (AAM). However, the causal relationship between these factors remains unclear. Therefore, this study aimed to elucidate the genetic relationship between dietary habits and AAM. Genetic summary statistics for dietary habits were obtained from the UK Biobank. GWAS summary data for AAM was obtained from the ReproGen Consortium. Linkage disequilibrium score regression was used to test genetic correlations between dietary habits and AAM. The Mendelian randomization (MR) analyses used the inverse-variance weighted method. Genetic correlations with AAM were identified for 29 candi-date dietary habits, such as milk type (skimmed, semi-skimmed, full cream; coefficient = 0.2704, Pldsc = 1.13 × 10-14). MR evaluations revealed that 19 dietary habits were associated with AAM, including bread type (white vs. any other; OR 1.71, 95% CI 1.28-2.29, Pmr = 3.20 × 10-4), tablespoons of cooked vegetables (OR 0.437, 95% CI 0.29-0.67; Pmr = 1.30 × 10-4), and cups of coffee per day (OR 0.72, 95% CI 0.57-0.92, Pmr = 8.31 × 10-3). These results were observed to be stable under the sensitivity analysis. Our study provides potential insights into the genetic mechanisms underlying AAM and evidence that dietary habits are associated with AAM.

Identifying BMI-associated genes via a genome-wide multi-omics integrative approach using summary data

OBJECTIVE

This study aims to identify BMI-associated genes by integrating aggregated summary information from different omics data.

METHODS

We conducted a meta-analysis to leverage information from a genome-wide association study (n = 339 224), a transcriptome-wide association study (n = 5619), and an epigenome-wide association study (n = 3743). We prioritized the significant genes with a machine learning-based method, netWAS, which borrows information from adipose tissue-specific interaction networks. We also used the brain-specific network in netWAS to investigate genes potentially involved in brain-adipose interaction.

RESULTS

We identified 195 genes that were significantly associated with BMI through meta-analysis. The netWAS analysis narrowed down the list to 21 genes in adipose tissue. Among these 21 genes, six genes, including FUS, STX4, CCNT2, FUBP1, NDUFS3, and RAPSN, were not reported to be BMI-associated in PubMed or GWAS Catalog. We also identified 11 genes that were significantly associated with BMI in both adipose and whole brain tissues.

CONCLUSION

This study integrated three types of omics data and identified a group of genes that have not previously been reported to be associated with BMI. This strategy could provide new insights for future studies to identify molecular mechanisms contributing to BMI regulation.

Genetic dissection of green pod yield in dolichos bean, an orphan vegetable legume, using new molecular markers

In the era of genomic-assisted breeding for crop improvement, developing new molecular markers and validating them for use in breeding programs are the prelude. Dolichos bean is one of the most important vegetable legume crops owing to its nutrient-rich green pods used as vegetables. Limitations in genomic resources, including molecular markers, restrict the accelerated improvement of the crop. In the present investigation, a set of 430 new simple sequence repeat markers was developed from sequence information of a reference variety. These markers included di- and tri-nucleotide repeats. The markers were assayed on an association panel, which was evaluated for green pod yield over 5 years. A multi-locus model, FarmCPU, was used to assess the marker-trait association analysis. A total of 106 marker-trait associations were identified using an efficient mixed-model approach. Tri-nucleotide repeats were more informative and predominantly associated with trait. Among these markers, 17 were associated with a high level of significance. Markers LP-D-68 and LP-D-14 were identified with a high level of significance in 5-year pooled data and explained 12.70% and 12% of the phenotypic variance, respectively. These markers associated with a high level of confidence have significant scope for use in marker-assisted selection programmes. Other associated markers may be utilized for improving parents through marker-assisted recurrent selection or genomic selection programs.

Oryza CLIMtools: A genome-environment association resource reveals adaptive roles for heterotrimeric G proteins in the regulation of rice agronomic traits

Modern crop varieties display a degree of mismatch between their current distributions and the suitability of the local climate for their productivity. To address this issue, we present Oryza CLIMtools (https://gramene.org/CLIMtools/oryza_v1.0/), the first resource for pan-genome prediction of climate-associated genetic variants in a crop species. Oryza CLIMtools consists of interactive web-based databases that enable the user to (1) explore the local environments of traditional rice varieties (landraces) in South-East Asia and (2) investigate the environment by genome associations for 658 Indica and 283 Japonica rice landrace accessions collected from georeferenced local environments and included in the 3K Rice Genomes Project. We demonstrate the value of these resources by identifying an interplay between flowering time and temperature in the local environment that is facilitated by adaptive natural variation in OsHD2 and disrupted by a natural variant in OsSOC1. Prior quantitative trait locus analysis has suggested the importance of heterotrimeric G proteins in the control of agronomic traits. Accordingly, we analyzed the climate associations of natural variants in the different heterotrimeric G protein subunits. We identified a coordinated role of G proteins in adaptation to the prevailing potential evapotranspiration gradient and revealed their regulation of key agronomic traits, including plant height and seed and panicle length. We conclude by highlighting the prospect of targeting heterotrimeric G proteins to produce climate-resilient crops.

A novel QTL region for pH and meat color in Duroc pigs

One of the most important processes that occur during the transformation of muscle to meat is the pH decline as a consequence of the post-mortem metabolism of muscle tissue. Abnormal pH declines lead to pork defects such as pale, soft, and exudative meat. There is genetic variance for ultimate pH and the role of some genes on this phenotype is well established. After conducting a genome-wide association study on ultimate pH using 526 purebred Duroc pigs, we identified associated regions on Sus scrofa chromosomes (SSC) 3, 8, and 15. Functional candidate genes in these regions included PRKAG3 and PHKG1. The SSC8 region, at 71.6 Mb, was novel and, although no candidate causative gene could be identified, it may have regulatory effects. Subsequent analysis on 828 pigs from the same population confirmed the impact of the three associated regions on pH and meat color. We detected no interaction between the three regions. Further investigations are necessary to unravel the functional significance of the novel genomic region at SSC8. These variants could be used as markers in marker-assisted selection for improving meat quality.

Studies on Candidate Genes Related to Flowering Time in a Multiparent Population of Maize Derived from Tropical and Temperate Germplasm

A comprehensive study on maize flowering traits, focusing on the regulation of flowering time and the elucidation of molecular mechanisms underlying the genes controlling flowering, holds the potential to significantly enhance our understanding of the associated regulatory gene network. In this study, three tropical maize inbreds, CML384, CML171, and CML444, were used, along with a temperate maize variety, Shen137, as parental lines to cross with Ye107. The resulting F1s underwent seven consecutive generations of self-pollination through the single-seed descent (SSD) method to develop a multiparent population. To investigate the regulation of maize flowering time-related traits and to identify loci and candidate genes, a genome-wide association study (GWAS) was conducted. GWAS analysis identified 556 SNPs and 12 candidate genes that were significantly associated with flowering time-related traits. Additionally, an analysis of the effect of the estimated breeding values of the subpopulations on flowering time was conducted to further validate the findings of the present study. Collectively, this study offers valuable insights into novel candidate genes, contributing to an improved understanding of maize flowering time-related traits. This information holds practical significance for future maize breeding programs aimed at developing high-yielding hybrids.

Investigating genetic links between blood metabolites and preeclampsia

BACKGROUND

Observational studies have revealed that metabolic disorders are closely related to the development of preeclampsia (PE). However, there is still a research gap on the causal role of metabolites in promoting or preventing PE. We aimed to systematically explore the causal association between circulating metabolites and PE.

METHODS

Single nucleotide polymorphisms (SNPs) from genome-wide association study (GWAS) of 486 blood metabolites (7,824 participants) were extracted as instrumental variables (P < 1 × 10- 5), GWAS summary statistics for PE were obtained from FinnGen consortium (7,212 cases and 194,266 controls) as outcome, and a two-sample Mendelian randomization (MR) analysis was conducted. Inverse variance weighted (IVW) was set as the primary method, with MR-Egger and weighted median as auxiliary methods; the instrumental variable strength and confounding factors were also assessed. Sensitivity analyses including MR-Egger, Cochran's Q test, MR-PRESSO and leave-one-out analysis were performed to test the robustness of the MR results. For significant associations, repeated MR and meta-analysis were performed by another metabolite GWAS (8,299 participants). Furthermore, significantly associated metabolites were subjected to a metabolic pathway analysis.

RESULTS

The instrumental variables for the metabolites ranged from 3 to 493. Primary analysis revealed a total of 12 known (e.g., phenol sulfate, citrulline, lactate and gamma-glutamylglutamine) and 11 unknown metabolites were associated with PE. Heterogeneity and pleiotropy tests verified the robustness of the MR results. Validation with another metabolite GWAS dataset revealed consistency trends in 6 of the known metabolites with preliminary analysis, particularly the finding that genetic susceptibility to low levels of arachidonate (20:4n6) and citrulline were risk factors for PE. The pathway analysis revealed glycolysis/gluconeogenesis and arginine biosynthesis involved in the pathogenesis of PE.

CONCLUSIONS

This study identifies a causal relationship between some circulating metabolites and PE. Our study presented new perspectives on the pathogenesis of PE by integrating metabolomics with genomics, which opens up avenues for more accurate understanding and management of the disease, providing new potential candidate metabolic molecular markers for the prevention, diagnosis and treatment of PE. Considering the limitations of MR studies, further research is needed to confirm the causality and underlying mechanisms of these findings.

Multidimensional data analysis revealed thyroiditis-associated TCF19 SNP rs2073724 as a highly ranked protective variant in thyroid cancer

BACKGROUND

Thyroid cancer represents the most prevalent malignant endocrine tumour, with rising incidence worldwide and high mortality rates among patients exhibiting dedifferentiation and metastasis. Effective biomarkers and therapeutic interventions are warranted in aggressive thyroid malignancies. The transcription factor 19 (TCF19) gene has been implicated in conferring a malignant phenotype in cancers. However, its contribution to thyroid neoplasms remains unclear.

RESULTS

In this study, we performed genome-wide and phenome-wide association studies to identify a potential causal relationship between TCF19 and thyroid cancer. Our analyses revealed significant associations between TCF19 and various autoimmune diseases and human cancers, including cervical cancer and autoimmune thyroiditis, with a particularly robust signal for the deleterious missense variation rs2073724 that is associated with thyroid function, hypothyroidism, and autoimmunity. Furthermore, functional assays and transcriptional profiling in thyroid cancer cells demonstrated that TCF19 regulates important biological processes, especially inflammatory and immune responses. We demonstrated that TCF19 could promote the progression of thyroid cancer in vitro and in vivo and the C>T variant of rs2073724 disrupted TCF19 protein binding to target gene promoters and their expression, thus reversing the effect of TCF19 protein.

CONCLUSIONS

Taken together, these findings implicate TCF19 as a promising therapeutic target in aggressive thyroid malignancies and designate rs2073724 as a causal biomarker warranting further investigation in thyroid cancer.

Genetic influences on testosterone and PTSD

Females are twice as likely to experience PTSD as compared to males. Although sex differences in prevalence are well-established, little is known about why such sex differences occur. Biological factors that vary with sex, including sex hormone production, may contribute to these differences. Considerable evidence links sex hormones, such as testosterone, to PTSD risk though less is known about the shared genetic underpinnings. The objective of the present study was to test for genetic relationships between testosterone and PTSD. To do so, we used summary statistics from large, publicly available genetic consortia to conduct linkage disequilibrium score regression to estimate the genetic correlations between PTSD and testosterone in males and females, and two-sample, bi-directional Mendelian randomization to examine potential causal relationships of testosterone on PTSD and the reverse. Heritability estimates of testosterone were significantly higher in males (0.17, SE = 0.02) than females (0.11, SE = 0.01; z = 2.46, p = 00.01). The correlation between testosterone and PTSD was negative in males (rg = -0.11, SE = 0.02, p = 6.7 x 10-6), but not significant in females (rg = 0.002, SE = 0.03, p = 0.95). MR analyses found no evidence of a causal effect of testosterone on PTSD or the reverse. Findings are consistent with phenotypic literature suggesting a relationship between testosterone and PTSD that may be sex-specific. This work provides early evidence of a relationship between testosterone and PTSD genotypically and suggests an avenue for future research that will enable a better understanding of disparities in PTSD.

Estimating disease heritability from complex pedigrees allowing for ascertainment and covariates

We propose TetraHer, a method for estimating the liability heritability of binary phenotypes. TetraHer has five key features. First, it can be applied to data from complex pedigrees that contain multiple types of relationships. Second, it can correct for ascertainment of cases or controls. Third, it can accommodate covariates. Fourth, it can model the contribution of common environment. Fifth, it produces a likelihood that can be used for significance testing. We first demonstrate the validity of TetraHer on simulated data. We then use TetraHer to estimate liability heritability for 229 codes from the tenth International Classification of Diseases (ICD-10). We identify 107 codes with significant heritability (p < 0.05/229), which can be used in future analyses for investigating the genetic architecture of human diseases.

GWAS supported by computer vision identifies large numbers of candidate regulators of in planta regeneration in Populus trichocarpa

Plant regeneration is an important dimension of plant propagation and a key step in the production of transgenic plants. However, regeneration capacity varies widely among genotypes and species, the molecular basis of which is largely unknown. Association mapping methods such as genome-wide association studies (GWAS) have long demonstrated abilities to help uncover the genetic basis of trait variation in plants; however, the performance of these methods depends on the accuracy and scale of phenotyping. To enable a large-scale GWAS of in planta callus and shoot regeneration in the model tree Populus, we developed a phenomics workflow involving semantic segmentation to quantify regenerating plant tissues over time. We found that the resulting statistics were of highly non-normal distributions, and thus employed transformations or permutations to avoid violating assumptions of linear models used in GWAS. We report over 200 statistically supported quantitative trait loci (QTLs), with genes encompassing or near to top QTLs including regulators of cell adhesion, stress signaling, and hormone signaling pathways, as well as other diverse functions. Our results encourage models of hormonal signaling during plant regeneration to consider keystone roles of stress-related signaling (e.g. involving jasmonates and salicylic acid), in addition to the auxin and cytokinin pathways commonly considered. The putative regulatory genes and biological processes we identified provide new insights into the biological complexity of plant regeneration, and may serve as new reagents for improving regeneration and transformation of recalcitrant genotypes and species.

Genetic Determinants of Vascular Dementia

Vascular dementia (VaD) is a prevalent form of cognitive impairment with underlying vascular etiology. In this review, we examine recent genetic advancements in our understanding of VaD, encompassing a range of methodologies including genome-wide association studies (GWAS), polygenic risk scores (PRS), heritability estimates, and family studies for monogenic disorders revealing the complex and heterogeneous nature of the disease. We report well-known genetic associations and highlight potential pathways and mechanisms implicated in VaD and its pathological risk factors, including stroke, cerebral small vessel diseases and cerebral amyloid angiopathy. Moreover, we discuss important modifiable risk factors such as hypertension, diabetes, and dyslipidemia, emphasizing the importance of a multifactorial approach in prevention, treatment, and understanding the genetic basis of VaD. Lastly, we outline several areas of scientific advancements to improve clinical care, highlighting that large-scale collaborative efforts, together with an integromics approach can enhance the robustness of genetic discoveries. Indeed, understanding the genetics of VaD and its pathophysiological risk factors hold the potential to redefine VaD based on molecular mechanisms and generate novel diagnostic, prognostic, and therapeutic tools.

Colocalization analysis of 3' UTR alternative polyadenylation quantitative trait loci reveals novel mechanisms underlying associations with lung function

While many disease-associated single nucleotide polymorphisms (SNPs) are expression quantitative trait loci (eQTLs), a large proportion of genome-wide association study (GWAS) variants are of unknown function. Alternative polyadenylation (APA) plays an important role in posttranscriptional regulation by allowing genes to shorten or extend 3' untranslated regions (UTRs). We hypothesized that genetic variants that affect APA in lung tissue may lend insight into the function of respiratory associated GWAS loci. We generated alternative polyadenylation (apa) QTLs using RNA sequencing and whole genome sequencing on 1241 subjects from the Lung Tissue Research Consortium (LTRC) as part of the NHLBI TOPMed project. We identified 56 179 APA sites corresponding to 13 582 unique genes after filtering out APA sites with low usage. We found that a total of 8831 APA sites were associated with at least one SNP with q-value < 0.05. The genomic distribution of lead APA SNPs indicated that the majority are intronic variants (33%), followed by downstream gene variants (26%), 3' UTR variants (17%), and upstream gene variants (within 1 kb region upstream of transcriptional start site, 10%). APA sites in 193 genes colocalized with GWAS data for at least one phenotype. Genes containing the top APA sites associated with GWAS variants include membrane associated ring-CH-type finger 2 (MARCHF2), nectin cell adhesion molecule 2 (NECTIN2), and butyrophilin subfamily 3 member A2 (BTN3A2). Overall, these findings suggest that APA may be an important mechanism for genetic variants in lung function and chronic obstructive pulmonary disease (COPD).

Association between gut microbiota and gastric cancers: a two-sample Mendelian randomization study

Background

Gastric cancer (GC) is the fifth most commonly diagnosed cancer worldwide, with its etiology attributed to a complex interplay of genetic, dietary, environmental factors, and infections such as Helicobacter pylori. Despite the known risk factors, the role of gut microbiota in the development of gastric cancer remains insufficiently explored. This study aims to elucidate the causal relationship between gut microbiota and gastric cancer using a two-sample Mendelian Randomization (MR) approach.

Methods

Utilizing genome-wide association study (GWAS) summary data from the MiBioGen consortium and gastric cancer datasets, we selected instrumental variables for MR analysis based on their association with specific microbiota. We employed several MR methods, including inverse variance weighted (IVW), MR-Egger, weighted median, and others, to estimate the causal effects of gut microbiota diversity on the risk of developing gastric cancer.

Results

Our analysis identified significant associations between certain gut microbiota and gastric cancer risk. Specifically, taxa such as Clostridium sensustricto1 (OR = 0.540, 95%CI: 0.354-0.823, p = 0.004), Actinomycetales (OR = 0.756, 95%CI: 0.613-0.932, p = 0.009), Selenomonadales (OR = 0.816, 95%CI: 0.666-1.000, p < 0.05), Negativicutes (OR = 0.816, 95%CI: 0.666-1.000, p < 0.05), Rikenellaceae (OR = 0.863, 95%CI: 0.746-0.999, p = 0.048) were found to have a protective effect against gastric cancer. Conversely, an increased risk of gastric cancer was associated with the abundance of Roseburia (OR = 1.342, 95%CI: 1.071-1.681, p = 0.011), Family XI (OR = 1.132, 95%CI: 1.012-1.267, p = 0.030), and Eubacterium brachy group (OR = 1.207, 95%CI: 1.074-1.355, p = 0.002). The findings were robust across various MR methods and were not driven by any single SNP, indicating a genuine causal relationship.

Conclusion

Our studies have shown that there is a causal relationship between intestinal flora and gastric cancer at the genetic level. Clostridium sensustricto1, Actinomycetales, Rikenellaceae, Selenomonadales, Negativicutes, and Actinomycetaceae as having a protective role against GC, while Roseburia, Family XI, and Eubacterium brachy group were associated with an increased risk.

Smartphone-based digital phenotyping for genome-wide association study of intramuscular fat traits in longissimus dorsi muscle of pigs

Intramuscular fat (IMF) content and distribution significantly contribute to the eating quality of pork. However, the current methods used for measuring these traits are complex, time-consuming and costly. To simplify the measurement process, this study developed a smartphone application (App) called Pork IMF. This App serves as a rapid and portable phenotyping tool for acquiring pork images and extracting the image-based IMF traits through embedded deep-learning algorithms. Utilizing this App, we collected the IMF traits of the longissimus dorsi muscle in a crossbred population of Large White × Tongcheng pigs. Genome-wide association studies detected 13 and 16 SNPs that were significantly associated with IMF content and distribution, respectively, highlighting NR2F2, MCTP2, MTLN, ST3GAL5, NDUFAB1 and PID1 as candidate genes. Our research introduces a user-friendly digital phenotyping technology for quantifying IMF traits and suggests candidate genes and SNPs for genetic improvement of IMF traits in pigs.

Genetic patterns and genome-wide association analysis of eggshell quality traits of egg-type chicken across an extended laying period

The industry of egg-type chicken has shown a trend of extending the rearing period, with the goal of breeding chicken breeds capable of producing 500 qualified eggs by 700 d of age. However, the rapid decline in eggshell quality during the late laying period is one of the major challenges. In this study, a total of 3,261 Rhode Island Red chickens were used to measure eggshell quality traits including eggshell strength (ESS), eggshell thickness (EST), eggshell color (ESC) and eggshell gloss (ESG) at seven age points ranging from 36 to 90 wk of age. Phenotypic variations increased with the aging process, especially during the late laying period (> 55 wk), and the heritability during this period decreased by 22.7 to 81.4% compared to the initial and peak laying periods. Then we performed genome-wide association study (GWAS) to identify the genomic variants that associated with eggshell quality, with a custom Illumina 50K BeadChip, named PhenoixChip-I. The results indicated that 2 genomic regions on GGA1(23.24-25.15Mb; 175.95-176.05 Mb) were significantly (P < 4.48E-06) or suggestively (P < 8.97E-05) associated with ESS, which can explain 9.59% and 0.48% of the phenotypic variations of ESS46 and ESS36, respectively. Three genes, FRY, PCNX2, and ENSGALG00000052468, were considered to be the candidate genes for ESS. For other traits, the genome-wide suggestive SNPs were identified at each age point, exhibiting a certain trend with aging process. Additionally, SNP enrichment analysis and functional annotation of cross-tissue regulatory elements to ESS36 revealed a high concentration of enhancer elements specific to shell gland and kidney tissues. This study, deepened our knowledge of eggshells and laying a valued scientific foundation for chicken molecular breeding.

Genome-wide association studies for the number of piglets born alive and dead in Dongliao black pigs

Litter size (total number born) trait has a great impact on the economic success of pork production. The total number born consists of the number of piglets born alive and dead. To clarify the genetic background of litter size, genome-wide association studies were undertaken in the present study. Samples of DNA were collected and genotyped using the Porcine 50K BeadChip from 723 Dongliao Black sows. Using three different models (BLINK, FarmCPU, and MLM), a total of 155 significant SNPs were discovered, six of which had been reported in previous pig reproduction association studies. We suggest that rs81318434, located in the GLI3 gene, might be the promising candidate affecting litter size trait. Our findings may provide insights for uncovering the genetic mechanisms for the litter size of pigs.

Evaluating three strategies of genome-wide association analysis for integrating data from multiple populations

In livestock, genome-wide association studies (GWAS) are usually conducted in a single population (single-GWAS) with limited sample size and detection power. To enhance the detection power of GWAS, meta-analysis of GWAS (meta-GWAS) and mega-analysis of GWAS (mega-GWAS) have been proposed to integrate data from multiple populations at the level of summary statistics or individual data, respectively. However, there is a lack of comparison for these different strategies, which makes it difficult to guide the best practice of GWAS integrating data from multiple study populations. To maximize the comparison of different association analysis strategies across multiple populations, we conducted single-GWAS, meta-GWAS, and mega-GWAS for the backfat thickness of 100 kg (BFT_100) and days to 100 kg (DAYS_100) within each of the three commercial pig breeds (Duroc, Yorkshire, and Landrace). Based on controlling the genome inflation factor to one, we calculated corrected p-values (pC ). In Yorkshire, with the largest sample size, mega-GWAS, meta-GWAS and single-GWAS detected 149, 38 and 20 significant SNPs (pC  < 1E-5) associated with BFT_100, as well as 26, four, and one QTL, respectively. Among them, pC of SNPs from mega-GWAS was the lowest, followed by meta-GWAS and single-GWAS. The correlation of pC among the three GWAS strategies ranged from 0.60 to 0.75 and the correlation of SNP effect values between meta-GWAS and mega-GWAS was 0.74, all showing good agreement. Collectively, even though there are differences in the integration of individual data or summary statistics, integrating data from multiple populations is an effective means of genetic argument for complex traits, especially mega-GWAS versus single-GWAS.

Elucidating the causal landscape: Mendelian randomization analysis of lifestyle and physiological factors in stress urinary incontinence

PURPOSE

To explore the potential causal links between obesity, type 2 diabetes (T2D), and lifestyle choices (such as smoking, alcohol and coffee consumption, and vigorous physical activity) on stress urinary incontinence (SUI), this study employs a Mendelian Randomization approach. This research aims to clarify these associations, which have been suggested but not conclusively established in prior observational studies.

METHODS

Genetic instruments associated with the exposures at the genome-wide significance (p < 5 × 10-8) were selected from corresponding genome-wide association studies. Summary-level data for SUI, was obtained from the UK Biobank. A two-sample MR analysis was employed to estimate causal effects, utilizing the inverse-variance weighted (IVW) method as the primary analytical approach. Complementary sensitivity analyses including MR-PRESSO, MR-Egger, and weighted median methods were performed. The horizontal pleiotropy was detected by using MR-Egger intercept and MR-PRESSO methods, and the heterogeneity was assessed using Cochran's Q statistics.

RESULTS

Our findings demonstrate a significant causal relationship between higher body mass index (BMI) and the risk of SUI, with increased abdominal adiposity (WHRadjBMI) similarly linked to SUI. Smoking initiation is also causally associated with an elevated risk. However, our analysis did not find definitive causal connections for other factors, including T2D, alcohol consumption, coffee intake, and vigorous physical activity.

CONCLUSIONS

These findings provide valuable insights for clinical strategies targeting SUI, suggesting a need for heightened awareness and potential intervention in individuals with higher BMI, WHR, and smoking habits. Further research is warranted to explore the complex interplay between genetic predisposition and lifestyle choices in the pathogenesis of SUI.

Whole genome resequencing reveals candidate genes for postaxial polydactyly in Large White pigs

Polydactyly is a genetic abnormality that affects both pig welfare and industry profits. Despite efforts to explore the genetic basis of pig polydactyly, progress remains limited. In this study, we analyzed a group of Large White pigs with postaxial polydactyly, including 29 cases and 79 controls from 24 families. High-depth sequencing was performed on 20 pigs, while low-depth sequencing was improved through imputation for the remaining pigs. A genome-wide association study (GWAS) and genetic differentiation were conducted using the resequencing dataset, resulting in the identification of 48 significantly associated SNPs and 27 candidate regions. The genetic differentiation regions on chromosomes 5 and 18, which harbored GWAS-identified SNPs, were delineated as confidence regions. The confidence region at Chr18: 1.850-1.925 Mb covers the fifth intron of LMBR1, a gene that contains an important regulatory element for SHH, known as ZRS. Mutations in this ZRS have been found to cause polydactyly in animals and humans. Therefore, we propose LMBR1 as a prospective candidate gene for postaxial polydactyly. These findings emphasize the importance of exploring the role of ZRS within LMBR1 in the pathogenesis of polydactyly in pigs.

Identification of candidate genes affecting the tibia quality in Nonghua duck

The skeleton is a vital organ providing structural support in poultry. Weakness in bone structure can lead to deformities, osteoporosis, cage fatigue, and fractures, resulting in economic losses. Research has substantiated that genetic factors play a significant role in influencing bone quality. The discovery of genetic markers associated with bone quality holds paramount importance for enhancing genetic traits related to the skeletal system in poultry. This study analyzed nine phenotypic indicators of tibia quality in 120-day-old ducks. The phenotypic correlation revealed a high correlation among diameter, Perimeter, and weight (0.69-0.78), and a strong correlation was observed between toughness and breaking strength (0.62). Then, we conducted a genome-wide association analysis of the phenotypic indicators to elucidate the genetic basis of tibial quality in Nonghua ducks. Among the 11 candidate genes that were annotated, TAPT1, BST1, and STIM2 were related to the diameter indicator, ZNF652, IGF2BP1, CASK, and GREB1L were associated with the weight and toughness indicators. RFX8, GLP1R, and DNAAF5 were identified for ash, calcium, and phosphorus content, respectively. Finally, KEGG and GO analysis for annotated genes were performed. STIM2 and BST1 were enriched into the Calcium signalling pathway and Niacin and nicotinamide metabolic pathway, which may be key candidate genes affecting bone quality phenotypes. Gene expression analysis of the candidate genes, such as STIM2, BST1, TAPT1, and CASK showed higher expression levels in bones compared to other tissues. The obtained results can contribute to new insights into tibial quality and provide new genetic biomarkers that can be employed in duck breeding.

Genetically determined metabolites in allergic conjunctivitis: A Mendelian randomization study

Background

Allergic conjunctivitis (AC) afflicts a significant portion of the global populace. Yet, its metabolic foundations remain largely unexplored.

Methods

We applied Mendelian Randomization (MR) and Linkage Disequilibrium Score Regression (LDSC) to scrutinize a cohort comprising 20 958 AC cases and 356 319 controls. Data were amalgamated from the metabolomics GWAS server and the FinnGen project, under strict quality control protocols.

Results

Using two-sample MR analysis, 486 blood metabolites were investigated in relation to AC. The IVW approach highlighted 18 metabolites as closely tied to AC risk; of these, 16 retained significance post sensitivity assessments for heterogeneity and horizontal pleiotropy. LDSC analysis, adopted to bolster our findings and negate confounders from shared genetic markers, revealed 8 metabolites with marked heritability, including: palmitate (OR = 0.614), 3-methoxytyrosine (OR = 0.657), carnitine (OR = 1.368), threonate (OR = 0.828), N-[3-(2-Oxopyrrolidin-1-yl)propyl]acetamide (OR = 1.257), metoprolol acid metabolite (OR = 0.982), oleoylcarnitine (OR = 0.635), and 2-palmitoylglycerophosphocholine (OR = 1.351).

Conclusion

AC is precipitated by ocular responses to environmental allergens. Our study unveils a causal link between 8 blood metabolites and AC. This insight accentuates the role of metabolites in AC onset, suggesting novel avenues for its early prediction, targeted prevention, and tailored therapeutic interventions.

Genetic variation drives differences in obesity-related gene regulation

Heikkinen and colleagues recently demonstrated that genetic variation, rather than dietary changes, governs gene regulation in liver. This finding highlights the impact of noncoding variants on chromatin accessibility, histone modifications, transcription factor binding, and gene expression and has implications for future research directions in understanding the genetic basis of disease.

A dual-subcellular localized β-glucosidase confers pathogen and insect resistance without a yield penalty in maize

Maize is one of the most important crops for food, cattle feed and energy production. However, maize is frequently attacked by various pathogens and pests, which pose a significant threat to maize yield and quality. Identification of quantitative trait loci and genes for resistance to pests will provide the basis for resistance breeding in maize. Here, a β-glucosidase ZmBGLU17 was identified as a resistance gene against Pythium aphanidermatum, one of the causal agents of corn stalk rot, by genome-wide association analysis. Genetic analysis showed that both structural variations at the promoter and a single nucleotide polymorphism at the fifth intron distinguish the two ZmBGLU17 alleles. The causative polymorphism near the GT-AG splice site activates cryptic alternative splicing and intron retention of ZmBGLU17 mRNA, leading to the downregulation of functional ZmBGLU17 transcripts. ZmBGLU17 localizes in both the extracellular matrix and vacuole and contribute to the accumulation of two defence metabolites lignin and DIMBOA. Silencing of ZmBGLU17 reduces maize resistance against P. aphanidermatum, while overexpression significantly enhances resistance of maize against both the oomycete pathogen P. aphanidermatum and the Asian corn borer Ostrinia furnacalis. Notably, ZmBGLU17 overexpression lines exhibited normal growth and yield phenotype in the field. Taken together, our findings reveal that the apoplastic and vacuolar localized ZmBGLU17 confers resistance to both pathogens and insect pests in maize without a yield penalty, by fine-tuning the accumulation of lignin and DIMBOA.

Genetic basis of sow hyperprolificacy and litter size optimization based on a genome-wide association study

Over the last few decades, there has been a constant increase in sow litter size, the consequences of which include parturition duration extension, an increase in the percentage of stillborn and hypoxic piglets, and increased variation in piglet birth weight, which reduces their vitality. As such, it seems clear that further increasing sow fertility will generate difficulties and costs in rearing numerous litters with low birth weights. Therefore, the current study aimed to analyze the genetic background of sow hyperprolifcacy using a genome-wide association study (GWAS). The research included 144 sows in the maternal component, divided into two equal groups. The first group (control) consisted of females giving birth to the optimal number of piglets in their third and fourth litters (14-16), while the second group (cases) included those with excessive litter size (>16). The analyzed sows were genotyped using Illumina's PorcineSNP60v2 BeadChip microarray, comprising 64,232 single nucleotide polymorphisms (SNPs). Statistical analysis using R included quality control of genotyping data and GWAS analysis based on five logistic regression models (dominant, codominant, overdominant, recessive, and log-additive) with a single SNP marker as the explanatory variable. On this basis, one SNP (SIRI0000069) was identified on chromosome seven within the EFCAB11 (EF-hand calcium binding domain 11) gene that had a statistically significant effect on sow hyperprolificacy. Additionally, ten SNPs (INRA0007631, ALGA0011600, ALGA0043433, ALGA0043428, M1GA0010535 ALGA00443338, ALGA0087116, MARC0056787, ALGA0112928, and ALGA0089047) had a relationship with the analyzed feature at a level close to significance, set at 1-5. These SNPs appear important since they are located on chromosomes on which a large number of quantitative trait loci (QTLs) and SNPs associated with reproductive characteristics, including litter size, have been identified.