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

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

Humans↗

Integrated Genome-Wide Association Studies and Selection Signature Analysis Reveal the Genetic Architecture of the Wattle Trait in Goats.

Wattles are finger-like appendages on the ventral neck of goats, serving as a distinctive morphological marker for breed identification that serves potential implications for production performance. However, their genetic basis remains incompletely characterized. Here, we integrated a genome-wide association study (GWAS) and selection signature analysis to identify candidate genes and genomic regions associated with the wattle trait in goats. Using a linear mixed model, GWAS on 463 goats (23 wattled and 440 non-wattled) identified 385 quantitative trait loci (QTLs) at a 5% false discovery rate, yielding 346 candidate genes. The most significant association signal was observed on chromosome 10 (72.61-73.48 Mb), where the lead SNP (rs636481767) is located within a region containing GJD2, GREM1, and FMN1, showing strong linkage disequilibrium (r2 > 0.6) with surrounding loci. Subsequent selection signature analysis (23 wattled and 23 non-wattled) identified 83 genomic regions harboring 119 candidate genes. The strongest signals were detected at MFSD14B on chromosome 8 (FST = 0.154, log2π-ratio = 2.611) and PDLIM7 on chromosome 7 (FST = 0.144, log2π-ratio = 0.806). KEGG pathway enrichment analysis revealed that GWAS-associated genes were involved in glycosylation and immune responses, whereas selection-signature genes were enriched in DNA repair and the Hippo, Notch, and Wnt pathways. Furthermore, cross-species PheWAS revealed that human FMN1 is associated with dermatological, skeletal, and metabolic phenotypes, while porcine FMN1 is associated with backfat thickness and loin muscle depth. Overall, this study provides molecular markers of potential value for goat breeding and pinpoints key candidate genes for future functional validation of wattle development.

Animals↗

A Guide for Exploring Pleiotropic Associations in Genome-Wide Association Studies Using Summary Statistics.

Genome-wide association studies (GWAS) have shown that pleiotropy, whereby a single genetic variant or gene influences multiple traits, is common in complex human diseases. Detecting cross-phenotype associations from GWAS summary statistics remains challenging because of small effect sizes, extensive multiple testing, heterogeneous effects, and possible differences in effect direction across traits. Methods that jointly analyze multiple traits can improve the ability to detect pleiotropic signals while retaining the practical advantages of summary statistic-based analyses. Although a range of statistical approaches has been developed for this purpose, practical guidance on their application, assumptions, and interpretation remains limited. This tutorial reviews several widely used methods for pleiotropy detection from GWAS summary statistics, including ASSET, PLACO, GPA, CPBayes, and GCPBayes, and demonstrates their application using breast and thyroid cancer datasets. We also highlight the importance of accounting for effect heterogeneity, correlation, and biological group structure at the gene and pathway levels in the detection and interpretation of pleiotropic association signals.

Genome-Wide Association Study↗

Genome-wide association study reveals two novel genetic loci associated with chronic lung allograft dysfunction.

BACKGROUND: Chronic lung allograft dysfunction (CLAD) leads to declining respiratory function and high mortality, representing the main barrier to long-term survival in lung transplantation (LT). We performed the first genome-wide association study (GWAS) investigating donor's and recipient's genetic factors associated with CLAD. METHOD: We genotyped 392 donor-recipient pairs from the multicentric Cohort in Lung Transplantation. We tested 4.5 million SNPs for association with CLAD using multivariable logistic regression models corrected for age, sex, initial disease and genetic ancestry. Three levels of explanatory variables were separately considered to conduct GWAS: donors-only, recipients-only, and donor-recipient mismatches. We also ran HLA-centric analyses using the same models. RESULTS: Our analysis confirmed the deleterious impact of HLA allelic and epitopic mismatches on CLAD risk, mostly driven by class I HLA (p=0.004). No significant associations with CLAD were found for donors' genotypes or donor-recipient non-HLA mismatches. We highlighted two independent recipient's loci associated with CLAD, including one protective signal (0.39 in CLAD vs 0.66 in non-CLAD recipients, p-value=5.05×10-7, q-value=0.017, OR=0.35) encompassing the PLXDC2 gene, and one risk signal (0.66 in CLAD vs 0.38 in non-CLAD recipients, p-value=9.86×10-7, q-value=0.017, OR=2.83) encompassing the ZNF518A/BLNK genes. These non-coding SNPs are putative regulatory variants of gene expression. Importantly, our single-cell RNA-sequencing showed a down-regulation of PLXDC2 in fibroblasts and lung epithelium in CLAD vs healthy controls. CONCLUSION: This first LT GWAS revealed two candidate loci from the recipient's genome, both biologically relevant for CLAD pathogenesis. Our study calls for larger LT genomic initiatives to increase power for signal discovery.

Humans↗

Multi-ancestral genome-wide association study of chronic pain reveals widespread genetic correlations with mental and physical health traits.

Chronic pain (CP) is common and debilitating, affecting 12-40% of people worldwide. In this study, we conducted a genome-wide association study (GWAS) of CP in the All of Us Research Program across six genetic ancestries (Ntotal = 313 931, Ncase = 64 894, Ncontrol = 249 037). In the cross-ancestral meta-analysis, one locus on chromosome 3 reached genome-wide (GW) significance (&#x3b1; = 5E-08; lead SNP: rs3849410, p = 2.64E-08,). This same lead SNP, rs3849410, also reached GW significance in the European subsample (p = 7.45E-10) and in European females (p = 4.25E-08). Two additional loci, with lead SNPs rs7652179 and rs4760489, reached GW significance (p = 8.57E-09, and 3.07E-08, respectively) in European ancestry. Sex-stratified analyses revealed one locus on chromosome 11 (lead SNP: rs77607049) in males (p = 1.13E-08); in females, two other loci on chromosomes 11 (lead SNP: rs368001205) and 12 were also identified (lead SNP: rs80043169; p = 1.58E-08, 9.14E-09, respectively; p < 2.5E-08). CP was genetically correlated with psychiatric, physical, and immune traits, including anxiety (rg = 0.72, p = 2.00E-46), generalized addiction risk (rg = 0.38, p = 2.08E-17), higher C-reactive protein levels (rg = 0.36, p = 6.38E-22) and greater body mass index (rg = 0.43, p = 8.03E-47). This study represents one of the largest cross-ancestral investigations of the genetics of CP to date and demonstrates shared genetic effects between CP and multiple health conditions. PERSPECTIVE: This article presents multi-ancestral cross-sex and sex-stratified GWAS of chronic pain (CP). One significant cross-ancestral locus and 3 sex-specific loci were identified; a previously published locus for multisite CP met traditional genome-wide significance in the current European ancestry GWAS. This study identifies 4 novel genetic loci associated with CP.

Chronic pain↗

Exploring genomic regions and genes modulating plant height and flag leaf morphology in rice.

Plant height and flag leaf morphology critically affect plant yield because they determine above-ground plant biomass and photosynthate production. However, few genetic basis analyses and gene mining studies on plant height, flag leaf length, and flag leaf width have been performed, and there is little available information about the evolution and utilization of the underlying natural alleles. This study conducted a genome-wide association study (GWAS) using 689 rice accessions collected from diverse regions across the globe. The GWAS identified 73, 159, and 158 significant loci associated with plant height, flag leaf length, and flag leaf width, respectively. SD1HAP1 and NAL1A were also identified as superior alleles that could be used to improve plant architecture by reducing plant height and increasing flag leaf width, respectively. LEAF1 and its elite allele LEAF1G, which simultaneously modulated plant height and flag leaf morphology, were isolated, and the LEAF1 knockout lines showed reduced flag leaf length and plant height, whereas LEAF1G-complementary lines in the LEAF1A background had the opposite phenotypes. The results also showed that LEAF1G and SD1HAP1 evolved directly from wild rice and were mainly found in the Xian subgroup, whereas NAL1A might have originated from de novo mutation during domestication and was mainly found in the Geng subgroup. A joint haplotype analysis revealed that pyramiding SD1HAP1, NAL1A, and LEAF1G in Type I accessions optimized plant architecture, reduced plant height, and enlarged the flag leaves. In addition, genomic regions and genes that had been convergently selected for these traits were identified by combining a population genetics analysis with a GWAS. These findings provide valuable genetic targets for molecular breeding that will improve plant height and flag leaf morphology in rice.

Oryza↗

Genetic variants in migraine: a field synopsis and systematic re-analysis of meta-analyses.

OBJECTIVE: Numerous genetic variants from meta-analyses of observational studies and GWAS were reported to be associated with migraine susceptibility. However, due to the random errors in meta-analyses, the noteworthiness of the results showing statistically significant remains doubtful. Thus, we performed this field synopsis and re-analysis study to evaluate the noteworthiness using a Bayesian approach in hope of finding true associations. METHODS: Relevant meta-analyses from observational studies and GWAS examining correlation between all genetic variants and migraine risk were included in our study by a PubMed search. Identification of noteworthy associations were analyzed by false-positive rate probability (FPRP) and Bayesian false discovery probability (BFDP). Using noteworthy variants, GO enrichment analysis were conducted through DAVID online tool. Then, the PPI network and hub genes were performed using STRING database and CytoHubba software. RESULTS: As for 8 significant genetic variants from observational studies, none of which showed noteworthy at prior probability of 0.001. Out of 47 significant genetic variants in GWAS, 36 were noteworthy at prior probability of 0.000001 via FPRP or BFDP. We further found the pathways "positive regulation of cytosolic calcium ion concentration" and "inositol phosphate-mediated signaling" and hub genes including MEF2D, TSPAN2, PHACTR1, TRPM8 and PRDM16 related to migraine susceptibility. CONCLUSION: Herein, we have identified several noteworthy variants for migraine susceptibility in this field synopsis. We hope these data would help identify novel genetic biomarkers and potential therapeutic target for migraine.

Bayes Theorem↗

Development and validation of a high-density 'Amahysnp' genotyping array in grain amaranth (Amaranthus hypochondriacus).

BACKGROUND: Grain amaranth has recently gained global attention as a promising crop alternative to traditional cereals due to its nutritional value and adaptability to various growing conditions. Although gene banks conserve extensive collections of amaranth germplasm, the genomic and phenotypic characterization of these resources is limited, which hinders their full utilization in breeding programs. A major challenge is the lack of high-throughput genotyping assays essential for comprehensive genomic characterization and trait mapping. High-density SNP arrays have become standard tools for genome-wide analysis across multiple loci, enabling molecular breeding across a range of crop species. RESULTS: In this study, we developed a 64&#xa0;K high-throughput SNP genotyping array named "AmahySNP", using Affymetrix&#xae; Axiom&#xae; technology. The array contains 64,069 high-density SNPs distributed across both genic (55.17%) and non-genic (44.83%) regions of the Amaranthus hypochondriacus genome. The genic region includes 8,879 genes, which consist of 4,830 single-copy genes and 4,049 multi-copy genes distributed across 16 scaffolds. These genes cover various functional regions, including exons (10.5%), introns (40.1%), 5'UTRs (1.6%), and 3'UTRs (2.9%), respectively. The AmahySNP array was effectively utilized for population structure analysis, genetic diversity studies, core development, and genome wide association studies (GWAS) in amaranth germplasm. A representative core set of 112 accessions was identified, which includes two released varieties (Annapurna and Suvarna) and 100 diverse accessions from 12 different regions, representing 12% of the total 917 accessions evaluated. Phylogenetic analysis revealed three major genetic clusters, independent of their geographical origins. GWAS conducted using 22,763 polymorphic SNPs from 540 genotypes identified 13 novel loci associated days to flowering (DTF) trait, seven of which were located within annotated genes. CONCLUSIONS: The AmahySNP 64&#xa0;K SNP chip a valuable genomic tool for amaranth research and breeding with a strong potential to accelerate its genetic improvement. It enables high-throughput genotyping for a wide range of applications, including GWAS and other genomic studies, and will significantly advance the exploration of natural genetic variations. Ultimately, this resource will empower amaranth breeders to develop improved amaranth cultivars with enhanced crop yield, resilience, and nutritional quality, contributing to global food security and sustainable agriculture.

Amaranthus↗

Dissecting the genetic basis underlying drought tolerance at different development stages in soybean.

INTRODUCTION: Soybean is an indispensable crop supplying protein and oil for humans and animals, and playing an essential role in global food security. Drought represses soybean seed germination, reducing biomass accumulation and even inhibiting yield. METHODS: In order to dissect the genetic components underlying soybean drought tolerance during different development stage, a natural population containing 140 accessions was employed to evaluate seven drought tolerance-related traits under water-welled and drought stress conditions. Subsequently, genome-wide association study (GWAS) was conducted based on 150K single nucleotide polymorphism (SNP) markers of "Zhongdouxin-1". And the drought tolerance coefficient of seven different traits were analyzed with seven GWAS models. RESULTS: A total of 1807 significant SNPs were detected across 20 chromosome, including 569 SNPs for germination stage, and 1242 SNPs for seedling stage. Of 569 SNPs identified in germination stage, 354 SNPs on chromosomes 2, 7, 13, 14, and 17 accounting for 62.21%. Among 1242 SNPs found in seedling stage, 869 SNPs on chromosomes 11, 14, 15, 17 and 18 accounting for 69.97%. Moreover, among 1807 significant SNPs, 163 SNPs exhibited pleiotropic effects, of which 23 were located in exon, 21 in intron, 12 in 5'UTR or 3'UTR and 11 in upstream or downstream. Furthermore, 249 stable SNPs were detected by more than four GWAS models. According to these stable SNPs, RNA expression levels and gene annotations, four causal genes (Glyma.02G080200, Glyma.11G056200, Glyma.12G188900, and Glyma.18G110200) conferring soybean drought tolerance were detected, which participated in ethylene stimulus response, water deprivation response, and proteolysis. DISCUSSION: Collectively, 249 stable SNPs, 163 pleiotropic SNPs and four candidate genes identified in present study provided promising molecular resources and reliable foundation for drought resistance improvement and marker-assisted selective breeding in soybean.

GWAS↗

Genome-Wide Association Analysis for Growth-Related Traits in Indoor- and Outdoor-Cultured Juvenile Grass Carp (Ctenopharyngodon idella).

Grass carp is a key herbivorous freshwater fish, yet long-term inbreeding reduces growth rates. Current genome-wide association studies (GWAS) primarily focus on a limited range of growth traits, while intestinal morphology is likely to emerge as a promising new proxy for both growth performance and health status. We reared juvenile grass carp from one batch in indoor vs. natural aquatic vegetation groups for 100 days, measuring body weight (BW), length (BL), height (BH), and intestinal length (IL) in 200 individuals (100/group). Phenotypic differences were significant for all traits, with IL most variable. GWAS identified 95 significant SNPs, among which 21 were related to multiple traits. Candidate gene and KEGG pathway analyses linked these SNPs to myogenesis, skeletal development, immunity, calcium signaling, and stress resistance. Twelve SNPs were found to be associated with IL, including 8 multi-trait-related and 4 trait-specific ones. This suggests that IL can serve as a supplementary growth trait. There was no overlap with prior GWAS, but recurrent signals on chromosomes 1, 2, 14 (BW) and 2, 3, 14, 24 (BH) merit further study. Our findings enrich molecular resources for grass carp and highlight IL's potential for marker-assisted breeding.

Ctenopharyngodon idella↗

Systematic Approach for Compound Angus Populations Revealing Positional Candidate Genes and Improving Prediction Accuracy in Carcass Traits.

Carcass traits, which reflect growth performance and muscle development, are economically important in beef cattle, yet their genetic determinants remain poorly characterized. Both single-population Genome-wide association studies (GWAS) methods, such as BLINK, and cross-population meta-analysis approaches are widely used to identify genetic variants, yet their comparative performance in genomic prediction for complex traits in structured populations remains underexplored. Few studies have directly compared these methods in genomic prediction. To address this gap, this study aims to (i) identify positional candidate genes associated with carcass traits and (ii) evaluate the context-dependent advantages of Covariate Adjustment (CA) and meta in genomic prediction. In this study, we analyzed carcass weight (CW), live weight (LW), and dressing percentage (DP) in 279 crossbred Angus cattle genotyped with the PHR0105_Bt140K_v1.0 SNP chip. GWAS was performed on the full population using BLINK, and results from three subpopulations were combined via meta-analysis, with significance thresholds for both approaches determined by a shuffle-based method. Candidate genes located within &#xb1;10 kb of significant SNPs were associated with different carcass traits, including STRIT1, SEL1L3, NOC4L and ANK1 for DP; SNCA and DNAH5 for CW; and GYPC, GPR158, and GUCY1A1 for LW. Prediction accuracy under MAS and MABLUP showed meta slightly outperformed BLINK in MAS, while BLINK was better with covariate adjustment; after incorporating kinship in MABLUP, meta achieved higher accuracy and population partitioning was negligible. Overall, MABLUP yielded the highest accuracy (0.52-0.79) versus MAS (0.37-0.54) in all traits. These findings provide a methodological basis for selecting appropriate GWAS strategies in structured populations and highlight candidate genes.

GS↗

Cross-Phenotype Genome-Wide Association Study on the Shared Genetic Susceptibility to Systemic Sclerosis and Primary Biliary Cholangitis.

OBJECTIVE: An increased risk of primary biliary cholangitis (PBC) has been reported in patients with systemic sclerosis (SSc). Our study aims to investigate the shared genetic susceptibility between the two disorders and to define candidate causal genes using cross-phenotype genome-wide association study (GWAS) meta-analysis. METHODS: We performed cross-phenotype GWAS meta-analysis and Bayesian colocalization analysis for patients with SSc and patients with PBC. We performed both genome-wide and locus-based analysis, including tissue and pathway enrichment analyses, fine-mapping, Bayesian colocalization analyses with expression quantitative trait loci and protein quantitative trait loci (pQTL) datasets, and phenome-wide association studies. Finally, we used an integrative approach to prioritize candidate causal genes from the novel loci. RESULTS: We detected a strong genetic correlation between SSc and PBC (global genetic correlation = 0.84, P = 1.7 &#xd7; 10-6). In the cross-phenotype GWAS meta-analysis, we identified 44 nonhuman leukocyte antigens loci that reached genome-wide significance (P < 5 &#xd7; 10-8). Evidence of shared causal variants between patients with SSc and patients with PBC was found for nine loci, five of which were novel. Integrating multiple sources of evidence, we prioritized CD40, ERAP1, PLD4, SPPL3, and CCDC113 as novel candidate causal genes. The CD40 risk locus colocalized with trans-pQTLs of multiple plasma proteins involved in B cell function. CONCLUSION: Our study supports a strong shared genetic susceptibility between SSc and PBC. Using cross-phenotype analyses, we have prioritized several novel candidate causal genes and pathways for these disorders.

Humans↗

Revealing the Shared Genetic Architecture of Metabolic Dysfunction-Associated Steatotic Liver Disease-Related Traits Through Genomic Structural Equation Modeling.

Although individual traits related to metabolic dysfunction-associated steatotic liver disease (MASLD) have been investigated through large-scale genome-wide association studies (GWASs), the shared genetic susceptibility across these traits remains unclear. We therefore conducted a multivariate GWAS of key MASLD-related traits to elucidate their common genetic architecture. We applied genomic structural equation modeling to model a latent genetic factor (MASLD-F) underlying genetically correlated MASLD-related traits, leveraging their GWAS-derived genetic correlations. We then performed functional annotations, including fine-mapping, transcriptome-wide association study, and cell- and tissue-type-specific enrichment analyses, and conducted Mendelian randomization analyses to identify modifiable risk factors. Our multivariate MASLD-F GWAS identified 50 independent variants across 48 genomic loci. Transcriptomic imputation identified several MASLD-F-associated genes, including ARNTL, NPC1, BTBD10, VDAC2, TSKU, SFMBT1, and ABHD17C. We observed significant enrichment of MASLD-F-related genetic signals predominantly in brain tissues, pancreatic islets, and the adrenal gland. Additionally, six modifiable risk factors and four modifiable protective factors for MASLD-F were identified. These findings reveal a complex shared genetic architecture underlying MASLD components, thereby expanding our understanding of disease pathogenesis and providing novel insights for precision medicine and public health interventions.

Humans↗

Foliar disease resistance phenomics of fungal pathogens: image-based approaches for mapping quantitative resistance in cereal germplasm.

Host plant resistance is the most effective and environmentally sustainable means of reducing yield losses caused by fungal foliar pathogens of cereal species. Cereal genebank collections hold diverse pools of potentially underutilized disease resistance alleles, and cereal genomic resources are well advanced due to large-scale sequencing and genotyping efforts. Genome-Wide Association Studies (GWAS) have emerged as the predominant association genetics technique to initially discover novel disease resistance loci or alleles in these diverse collections. Traditional disease resistance phenotyping methods are reliant on visual estimation of disease symptom severity and have successfully supported genetic mapping studies either via GWAS or QTL mapping in biparental populations facilitating both marker development and gene cloning efforts. Due to foliar pathogens having a high capacity to evolve, there is a need to pyramid disease resistance genes with diverse mechanisms for durable control. Resistance expressed as a quantitative trait, known as quantitative resistance (QR), is hypothesized to be more durable, unlike major R-gene resistance that is race-specific and can be vulnerable to breaking down without gene stewardship. However, assessing QR visually is challenging, particularly when complicated by complex genotype&#x2009;&#xd7;&#x2009;environment (G&#x2009;&#xd7;&#x2009;E) effects in the field. High-throughput image-based phenotyping provides accurate and unbiased data that can support foliar disease resistance screening efforts of genebank collections using GWAS. In this review, we discuss image-based disease phenotyping based on macroscopic (visible symptoms) and microscopic features during the host-pathogen interaction. Quantitative image analysis approaches using conventional and artificial intelligence (AI) algorithms are also discussed.

Disease Resistance↗

Genome wide association study unveils the genetic basis of Orobanche crenata resistance in pea.

GWAS using DArTseq markers identified novel resistance sources against parasitic broomrape in pea, elucidating candidate genes for marker-selected breeding as leverage for cultivar development and efficient disease control to enhance food security. Crenate broomrape (Orobanche crenata) is an important obligate root parasitic weed that causes severe yield losses in pea (Pisum sativum) production. O. crenata is difficult to eradicate in pea fields due to its high resilience and prolific seed boom capable of hibernating in soils for decades. Existing control strategies are not cost effective in low input legumes like pea. The most efficient ecofriendly mode of control is using resistant cultivars. Quantitative trait loci (QTL) studies based on bi-parental mapping has guided O. crenata resistance discovery, albeit their deployment in pea breeding is hindered by low marker resolution and large genetic distance. This study presents the first genome-wide association study (GWAS) on O. crenata resistance in pea, utilizing 324 diverse accessions and 26,045 diversity array technology sequence (DArTseq) markers. Phenotyping was performed over four seasons under field conditions using alpha lattice design. Results showed a strong phenotypic variation with an environmental influence on O. crenata infection. Novel resistance sources were identified mainly within the wild Pisum fulvum and P. sativum subsp. elatius. GWAS with two models yielded a total of 73 marker-trait associations with Chromosome 5 as major hotspot. Interestingly, some linked markers were detected in close proximity to four previous O. crenata resistance QTL. DArTseq markers identified 24 putative candidate genes participating in different cellular processes, including vesicle trafficking and transports, deoxyribonucleic acid transcription regulation, and defense including some leucine rich repeat receptor-like kinases. These results provide a valuable genetic resource for O. crenata resistance and a step toward its effective sustainable management-to enhance genetic diversity and cultivar improvement for food security.

Pisum sativum↗

Sex-specific genetic predictors of Alzheimer's disease biomarkers.

Cerebrospinal fluid (CSF) levels of amyloid-&#x3b2; 42 (A&#x3b2;42) and tau have been evaluated as endophenotypes in Alzheimer's disease (AD) genetic studies. Although there are sex differences in AD risk, sex differences have not been evaluated in genetic studies of AD endophenotypes. We performed sex-stratified and sex interaction genetic analyses of CSF biomarkers to identify sex-specific associations. Data came from a previous genome-wide association study (GWAS) of CSF A&#x3b2;42 and tau (1527 males, 1509 females). We evaluated sex interactions at previous loci, performed sex-stratified GWAS to identify sex-specific associations, and evaluated sex interactions at sex-specific GWAS loci. We then evaluated sex-specific associations between prefrontal cortex (PFC) gene expression at relevant loci and autopsy measures of plaques and tangles using data from the Religious Orders Study and Rush Memory and Aging Project. In A&#x3b2;42, we observed sex interactions at one previous and one novel locus: rs316341 within SERPINB1 (p&#x2009;=&#x2009;0.04) and rs13115400 near LINC00290 (p&#x2009;=&#x2009;0.002). These loci showed stronger associations among females (&#x3b2;&#x2009;=&#x2009;-&#x2009;0.03, p&#x2009;=&#x2009;4.25&#x2009;&#xd7;&#x2009;10-8; &#x3b2;&#x2009;=&#x2009;0.03, p&#x2009;=&#x2009;3.97&#x2009;&#xd7;&#x2009;10-8) than males (&#x3b2;&#x2009;=&#x2009;-&#xa0;0.02, p&#x2009;=&#x2009;0.009; &#x3b2;&#x2009;=&#x2009;0.01, p&#x2009;=&#x2009;0.20). Higher levels of expression of SERPINB1, SERPINB6, and SERPINB9 in PFC was associated with higher levels of amyloidosis among females (corrected p values&#x2009;<&#x2009;0.02) but not males (p&#x2009;>&#x2009;0.38). In total tau, we observed a sex interaction at a previous locus, rs1393060 proximal to GMNC (p&#x2009;=&#x2009;0.004), driven by a stronger association among females (&#x3b2;&#x2009;=&#x2009;0.05, p&#x2009;=&#x2009;4.57&#x2009;&#xd7;&#x2009;10-10) compared to males (&#x3b2;&#x2009;=&#x2009;0.02, p&#x2009;=&#x2009;0.03). There was also a sex-specific association between rs1393060 and tangle density at autopsy (pfemale&#x2009;=&#x2009;0.047; pmale&#x2009;=&#x2009;0.96), and higher levels of expression of two genes within this locus were associated with lower tangle density among females (OSTN p&#x2009;=&#x2009;0.006; CLDN16 p&#x2009;=&#x2009;0.002) but not males (p&#x2009;&#x2265;&#x2009;0.32). Results suggest a female-specific role for SERPINB1 in amyloidosis and for OSTN and CLDN16 in tau pathology. Sex-specific genetic analyses may improve understanding of AD's genetic architecture.

Aged, 80 and over↗

Glutaryl-CoA dehydrogenase (GCDH) enhances renal malignancy risk via modulating glutarylcarnitine levels.

BACKGROUND: Crotonylation, a recently identified lysine acylation, plays a critical role in post-translational modifications [1]. It has been implicated in tumorigenesis by modulating metabolic reprogramming [2], DNA repair, immune evasion [3], and oncogenic signaling pathways, including PKA-FAK-AKT and androgen receptor signaling [4]. The specific role of crotonylation in renal malignancy (RM) remains poorly understood, especially in interaction with gene expression and metabolic pathway interactions. METHODS: This study integrates genome-wide association study (GWAS) summary statistics for RM from the FinnGen database, data on crotonylation-associated gene expression obtained from the eQTLGen consortium, and metabolite GWAS data obtained from the GWAS Catalog. A combined two-sample Mendelian randomization (MR), summary data-based Mendelian randomization (SMR), and mediation analyses were performed to investigate the causal link between Glutaryl-CoA dehydrogenase (GCDH) and RM, with a specific focus on glutarylcarnitine metabolism. RESULTS: MR analysis demonstrated a significant association; increased expression of GCDH is likely to increase the risk of RM (OR&#x2009;=&#x2009;1.25, P&#x2009;=&#x2009;0.0045). Mediation analysis revealed that elevated GCDH expression significantly reduced glutarylcarnitine (C5-DC) levels, which in turn was inversely associated with RM risk. A three-step MR-based mediation confirmed a significant mediating effect of glutarylcarnitine (&#x3b2;&#x2081;&#x2082; = 0.0680, P&#x2009;=&#x2009;0.002), with 30.25% of the total effect attributable to it. The robustness of these findings was further demonstrated by sensitivity analyses and SMR results. CONCLUSION: This study represents the first evidence that GCDH might exert an indirect pro-RM effect via the downregulation of glutarylcarnitine, thus providing new insights into tumor metabolic pathways and positioning glutarylcarnitine as a potentially diagnostic biomarker and therapeutic target for RM.

GCDH↗

Beyond ion channel dysfunction: Integration of the transcriptome and proteome from patient-specific re-engineered cardiac cells, and population-level QT genome-wide association study reveals broad cellular dysfunction.

BACKGROUND: Congenital long QT syndrome (LQTS) is a cardiac channelopathy with increased risk of cardiac-triggered syncope/seizures, sudden cardiac arrest, and sudden cardiac death. OBJECTIVE: This study aimed to describe the transcriptomic and proteomic profiles in patient-derived inducible pluripotent stem cell-derived cardiomyocyte (iPSC-CM) models of the 3 canonical genotypes of congenital LQTS: LQT1, LQT2, and LQT3 and integrate these omics-level findings with each other and with population/clinical level QT-genome-wide association study (GWAS) data. METHODS: LQT1, LQT2, LQT3 and respective isogenic control iPSC-CMs were cultured, and RNA and protein samples were collected. RNA sequencing and mass spectrometry-enabled proteomic analysis was performed. PrediXcan analysis was performed using QT GWAS summary statistics and transcriptome expression data. Differential gene and protein expression and ingenuity pathway analysis (IPA) was performed comparing each LQT genotype with its respective isogenic control. RESULTS: 1645 differentially expressed genes (DEGs) were identified; 13 were altered in all 3 LQTS genotypes. IPA analysis of DEGs revealed 301 altered pathways; 47 were altered in all LQTS genotypes. Proteomic analysis identified 2561 differentially expressed proteins (DEPs); 30 were altered in all 3 genotypes. IPA analysis of DEPs identified 646 altered pathways. 306 genes/proteins were identified as significantly altered in both the transcriptome and proteome; pathway analysis of these 301 genes identified 201 altered pathways. 7 pathways were altered in all 3 LQTS genotypes in both the transcriptome and proteome. Integration of the population-level PrediXcan results and the cardiomyocyte-derived omics results identified multiple shared pathways. CONCLUSION: Multi-omics analysis of LQTS and integration of omics results with QT GWAS data reveals that primary LQTS-causative ion channel defects precipitate secondary alterations in a wide range of cellular pathways. Our findings suggest more broad molecular level changes throughout the cell. This study lays the foundation for further exploration of broad cellular changes resulting from ion channel disturbances and how they contribute to disease mechanism.

Humans↗