Finding the missing heritability of complex diseases

Transgenerational epigenetic self-memory of Dio3 dosage is associated with Meg3 methylation and altered growth trajectories and neonatal hormones

Intergenerational and transgenerational epigenetic effects resulting from conditions in previous generations can contribute to environmental adaptation as well as disease susceptibility. Previous studies in rodent and human models have shown that abnormal developmental exposure to thyroid hormone affects endocrine function and thyroid hormone sensitivity in later generations. Since the imprinted type 3 deiodinase gene (Dio3) regulates sensitivity to thyroid hormones, we hypothesize its epigenetic regulation is altered in descendants of thyroid hormone overexposed individuals. Using DIO3-deficient mice as a model of developmental thyrotoxicosis, we investigated Dio3 total and allelic expression and growth and endocrine phenotypes in descendants. We observed that male and female developmental overexposure to thyroid hormone altered total and allelic Dio3 expression in genetically intact descendants in a tissue-specific manner. This was associated with abnormal growth and neonatal levels of thyroid hormone and leptin. Descendant mice also exhibited molecular abnormalities in the Dlk1-Dio3 imprinted domain, including increased methylation in Meg3 and altered foetal brain expression of other genes of the Dlk1-Dio3 imprinted domain. These molecular abnormalities were also observed in the tissues and germ line of DIO3-deficient ancestors originally overexposed to thyroid hormone in utero. Our results provide a novel paradigm of epigenetic self-memory by which Dio3 gene dosage in a given individual, and its dependent developmental exposure to thyroid hormone, influences its own expression in future generations. This mechanism of epigenetic self-correction of Dio3 expression in each generation may be instrumental in descendants for their adaptive programming of developmental growth and adult endocrine function.

Overview of role of survivin in cancer: expression, regulation, functions, and its potential as a therapeutic target

Survivin holds significant importance as a member of the inhibitor of apoptosis protein (IAP) family due to its predominant expression in tumours rather than normal terminally differentiated adult tissues. The high expression level of survivin in tumours is closely linked to chemotherapy resistance, heightened tumour recurrence, and increased tumour aggressiveness and serves as a negative prognostic factor for cancer patients. Consequently, survivin has emerged as a promising therapeutic target for cancer treatment. In this review, we delve into the various biological characteristics of survivin in cancers and its pivotal role in maintaining immune system homeostasis. Additionally, we explore different therapeutic strategies aimed at targeting survivin.

The utility of obesity polygenic risk scores from research to clinical practice: A review

Obesity represents a major public health emergency worldwide, and its etiology is shaped by a complex interplay of environmental and genetic factors. Over the last decade, polygenic risk scores (PRS) have emerged as a promising tool to quantify an individual's genetic risk of obesity. The field of PRS in obesity genetics is rapidly evolving, shedding new lights on obesity mechanisms and holding promise for contributing to personalized prevention and treatment. Challenges persist in terms of its clinical integration, including the need for further validation in large-scale prospective cohorts, ethical considerations, and implications for health disparities. In this review, we provide a comprehensive overview of PRS for studying the genetics of obesity, spanning from methodological nuances to clinical applications and challenges. We summarize the latest developments in the generation and refinement of PRS for obesity, including advances in methodologies for aggregating genome-wide association study data and improving PRS predictive accuracy, and discuss limitations that need to be overcome to fully realize its potential benefits of PRS in both medicine and public health.

Genome-wide selection signatures address trait specific candidate genes in cattle indigenous to arid regions of India

The peculiarity of Indian cattle lies in milk quality, resistance to diseases and stressors as well as adaptability. The investigation addressed selection signatures in Gir and Tharparkar cattle, belonging to arid ecotypes of India. Double digest restriction-site associated DNA sequencing (ddRAD-seq) yielded nearly 26 million high-quality reads from unrelated seven Gir and seven Tharparkar cows. In all, 19,127 high-quality SNPs were processed for selection signature analysis. An approach involving within-population composite likelihood ratio (CLR) statistics and between-population FST statistics was used to capture selection signatures within and between the breeds, respectively. A total of 191 selection signatures were addressed using CLR and FST approaches. Selection signatures overlapping 86 and 73 genes were detected as Gir- and Tharparkar-specific, respectively. Notably, genes related to production (CACNA1D, GHRHR), reproduction (ESR1, RBMS3), immunity (NOSTRIN, IL12B) and adaptation (ADAM22, ASL) were annotated to selection signatures. Gene pathway analysis revealed genes in insulin/IGF pathway for milk production, gonadotropin releasing hormone pathway for reproduction, Wnt signalling pathway and chemokine and cytokine signalling pathway for adaptation. This is the first study where selection signatures are identified using ddRAD-seq in indicine cattle breeds. The study shall help in conservation and leveraging genetic improvements in Gir and Tharparkar cattle.

SNP analysis of stress-related genes reveals significant correlations with drug addiction in Jordan

Objective

Drug addiction is a complex disorder caused by multiple factors, including environmental and genetic factors. Stress-related genes such as Galanin (GAL) and Oxytocin (OXT) have been linked to the reward pathways that contribute to the development and progression of substance addiction. This study aimed to explore the correlation between several polymorphisms of stress-related genes and drug addiction among Jordanian males.

Methods

The study included 500 participants, consisting of both healthy controls and drug-addicted Jordanian males. The genetic material and clinical data were collected, and 18 SNPs in four candidate genes were genotyped using the Sequenom MassARRAY® system. Statistical analyses were performed using the Statistical Package for the Social Sciences (SPSS) version 25.0 and the SNPStats website.

Results

The study identified a significant correlation between three SNPs of the GAL gene and drug addiction, specifically rs3136544, rs3136541, and rs694066. The study also found that different genotypes of these variants were significantly associated with drug addiction. Furthermore, different haplotypes of the GAL, GALR1, and OXTR polymorphisms were also significantly correlated with drug addiction. The study also identified a correlation between several drug addiction features and the studied variants, including the association of rs2717162 of Galanin receptor 1 (GALR1) with age at use onset and the association of rs3136541 of GAL with the type of substance and number of substances used.

Conclusion

Stress-related genes can play a significant role in the development and progression of addiction among the Jordanian population, and further investigations are necessary to understand the underlying mechanisms better and improve future treatment strategies.

Genetic liability to higher frailty index may increase the risk of ophthalmic disease

PURPOSE

Frailty and age-related eye diseases are common in older people; however, whether there is a causal link remains unknown. We aimed to explore the causal associations between the frailty index (FI) and ophthalmic traits and identify modifiable mediators.

METHODS

Linkage disequilibrium score regression and two-sample Mendelian randomization were applied to identify genetic correlations and causal associations between FI and ophthalmic traits. Summary data for FI was obtained from a genome-wide association study that included 175,226 individuals of European ancestry. Summary-level statistics for ophthalmic traits were obtained from relative GWASs. Summary-level data for cardiovascular risk factors, inflammatory biomarkers, and the central nervous system were used to identify the possible mediators.

RESULTS

FI had a significant genetic correlation with 10 ophthalmic traits. Per SD increment of FI, the odds ratio was 1.329 (95% CI, 1.123, 1.573; P = 9.5 × 10-4) for cataracts, 1.825 (95% CI, 1.115, 2.986; P = 0.016) for keratitis, 1.798 (95% CI, 1.039, 3.11; P = 0.036) for disorders of vitreous body and 1.478 (95% CI, 1.005, 2.173; P = 0.046) for disorders of sclera, cornea, iris and ciliary body. The MR effect estimates of FI on ophthalmic traits were attenuated after adjusting for mental disorders, type 2 diabetes, triglyceride, and interleukin-8 (IL-8) levels.

CONCLUSION

This study reports a genetic correlation and causal association between FI and ophthalmic traits, in which mental disorders, type 2 diabetes, triglycerides, and IL-8 may play a mediating role. These findings highlight a possible method to reduce the risk of FI-related ophthalmic diseases.

Genetic liability to higher frailty index may increase the risk of ophthalmic disease

PURPOSE

Frailty and age-related eye diseases are common in older people; however, whether there is a causal link remains unknown. We aimed to explore the causal associations between the frailty index (FI) and ophthalmic traits and identify modifiable mediators.

METHODS

Linkage disequilibrium score regression and two-sample Mendelian randomization were applied to identify genetic correlations and causal associations between FI and ophthalmic traits. Summary data for FI was obtained from a genome-wide association study that included 175,226 individuals of European ancestry. Summary-level statistics for ophthalmic traits were obtained from relative GWASs. Summary-level data for cardiovascular risk factors, inflammatory biomarkers, and the central nervous system were used to identify the possible mediators.

RESULTS

FI had a significant genetic correlation with 10 ophthalmic traits. Per SD increment of FI, the odds ratio was 1.329 (95% CI, 1.123, 1.573; P = 9.5 × 10-4) for cataracts, 1.825 (95% CI, 1.115, 2.986; P = 0.016) for keratitis, 1.798 (95% CI, 1.039, 3.11; P = 0.036) for disorders of vitreous body and 1.478 (95% CI, 1.005, 2.173; P = 0.046) for disorders of sclera, cornea, iris and ciliary body. The MR effect estimates of FI on ophthalmic traits were attenuated after adjusting for mental disorders, type 2 diabetes, triglyceride, and interleukin-8 (IL-8) levels.

CONCLUSION

This study reports a genetic correlation and causal association between FI and ophthalmic traits, in which mental disorders, type 2 diabetes, triglycerides, and IL-8 may play a mediating role. These findings highlight a possible method to reduce the risk of FI-related ophthalmic diseases.

Yield of genetic association signals from genomes, exomes and imputation in the UK Biobank

Whole-genome sequencing (WGS), whole-exome sequencing (WES) and array genotyping with imputation (IMP) are common strategies for assessing genetic variation and its association with medically relevant phenotypes. To date, there has been no systematic empirical assessment of the yield of these approaches when applied to hundreds of thousands of samples to enable the discovery of complex trait genetic signals. Using data for 100 complex traits from 149,195 individuals in the UK Biobank, we systematically compare the relative yield of these strategies in genetic association studies. We find that WGS and WES combined with arrays and imputation (WES + IMP) have the largest association yield. Although WGS results in an approximately fivefold increase in the total number of assayed variants over WES + IMP, the number of detected signals differed by only 1% for both single-variant and gene-based association analyses. Given that WES + IMP typically results in savings of lab and computational time and resources expended per sample, we evaluate the potential benefits of applying WES + IMP to larger samples. When we extend our WES + IMP analyses to 468,169 UK Biobank individuals, we observe an approximately fourfold increase in association signals with the threefold increase in sample size. We conclude that prioritizing WES + IMP and large sample sizes rather than contemporary short-read WGS alternatives will maximize the number of discoveries in genetic association studies.

Multi-step gene set analysis identified HTR3 family genes involving childhood acute lymphoblastic leukemia susceptibility

In our previous conventional genome-wide association study (GWAS), WWOX was a susceptibility gene associated with acute lymphoblastic leukemia (ALL) development. Nowadays, advancements in genetic association analyses promote an in-depth exploration of ALL genomics. We conducted a two-step enrichment analysis at both gene and pathway levels based on ALL GWAS data including 269 cases and 1039 controls of Chinese descent. The following functional prediction and experiments were used to evaluate the genetic biology of candidate variants and genes. The serotonin-activated cation-selective channel complex gene-set was a potential biological pathway involved in ALL occurrence. Of which, individuals carrying the T allele of rs33940208 exhibited a prominent reduced risk of ALL [odds ratio (OR) = 0.71, 95% confidence interval (CI) = 0.53 to 0.96, P = 2.81 × 10-2], whereas those with the A allele of rs6779545 demonstrated an increased risk (OR = 1.23, 95% CI = 1.01 to 1.51, P = 4.11 × 10-2). Notably, the two variants displayed a better prediction capability when combined, that the risk of developing childhood ALL increased by 131% in subjects with 2-4 risk alleles compared to those with 0-1 risk alleles (Ptrend = 2.05 × 10-3). In addition, the T allele of rs33940208 could reduce HTR3A mRNA level, while the A allele of rs6779545 increased HTR3D mRNA expression. In this study, we identified HTR3A rs33940208 and HTR3D rs6779545 as potential susceptibility loci for ALL in Chinese children. Future validation and functional research will elucidate the underlying molecular processes, refining preventive strategies for this disease.

[Genetic diagnostics of mental health disorders in adulthood]

This review article provides insights into the role of genetic diagnostics in adult mental health disorders. The importance of genetic factors in the development of mental illnesses, from rare genetic syndromes to common complex genetic disorders, is described. Current clinical characteristics that may warrant a genetic diagnostic work-up are highlighted, including intellectual disability, autism spectrum disorders and severe psychiatric conditions with specific comorbidities, such as organ malformations or epilepsy. The review discusses when genetic diagnostics are recommended according to current guidelines as well as situations where they might be considered even in the absence of explicit guideline recommendations. This is followed by an overview of the procedures and the currently used diagnostic methods. Current limitations and possible developments in the field of genetic diagnostics in psychiatry are discussed, including the fact that, for many mental health conditions, genetic testing is not yet part of standard clinical practice; however, in summary genetic causes should be considered more frequently in certain clinical constellations, and genetic diagnostics and counselling should be offered where appropriate.

A phenome-wide association study of methylated GC-rich repeats identifies a GCC repeat expansion in AFF3 associated with intellectual disability

GC-rich tandem repeat expansions (TREs) are often associated with DNA methylation, gene silencing and folate-sensitive fragile sites, and underlie several congenital and late-onset disorders. Through a combination of DNA-methylation profiling and tandem repeat genotyping, we identified 24 methylated TREs and investigated their effects on human traits using phenome-wide association studies in 168,641 individuals from the UK Biobank, identifying 156 significant TRE-trait associations involving 17 different TREs. Of these, a GCC expansion in the promoter of AFF3 was associated with a 2.4-fold reduced probability of completing secondary education, an effect size comparable to several recurrent pathogenic microdeletions. In a cohort of 6,371 probands with neurodevelopmental problems of suspected genetic etiology, we observed a significant enrichment of AFF3 expansions compared with controls. With a population prevalence that is at least fivefold higher than the TRE that causes fragile X syndrome, AFF3 expansions represent a major cause of neurodevelopmental delay.

Network medicine-based epistasis detection in complex diseases: ready for quantum computing

Most heritable diseases are polygenic. To comprehend the underlying genetic architecture, it is crucial to discover the clinically relevant epistatic interactions (EIs) between genomic single nucleotide polymorphisms (SNPs) (1-3). Existing statistical computational methods for EI detection are mostly limited to pairs of SNPs due to the combinatorial explosion of higher-order EIs. With NeEDL (network-based epistasis detection via local search), we leverage network medicine to inform the selection of EIs that are an order of magnitude more statistically significant compared to existing tools and consist, on average, of five SNPs. We further show that this computationally demanding task can be substantially accelerated once quantum computing hardware becomes available. We apply NeEDL to eight different diseases and discover genes (affected by EIs of SNPs) that are partly known to affect the disease, additionally, these results are reproducible across independent cohorts. EIs for these eight diseases can be interactively explored in the Epistasis Disease Atlas (https://epistasis-disease-atlas.com). In summary, NeEDL demonstrates the potential of seamlessly integrated quantum computing techniques to accelerate biomedical research. Our network medicine approach detects higher-order EIs with unprecedented statistical and biological evidence, yielding unique insights into polygenic diseases and providing a basis for the development of improved risk scores and combination therapies.

Validation of cross-progeny variance genomic prediction using simulations and experimental data in winter elite bread wheat

KEY MESSAGE

From simulations and experimental data, the quality of cross progeny variance genomic predictions may be high, but depends on trait architecture and necessitates sufficient number of progenies. Genomic predictions are used to select genitors and crosses in plant breeding. The usefulness criterion (UC) is a cross-selection criterion that necessitates the estimation of parental mean (PM) and progeny standard deviation (SD). This study evaluates the parameters that affect the predictive ability of UC and its two components using simulations. Predictive ability increased with heritability and progeny size and decreased with QTL number, most notably for SD. Comparing scenarios where marker effects were known or estimated using prediction models, SD was strongly impacted by the quality of marker effect estimates. We proposed a new algebraic formula for SD estimation that takes into account the uncertainty of the estimation of marker effects. It improved predictions when the number of QTL was superior to 300, especially when heritability was low. We also compared estimated and observed UC using experimental data for heading date, plant height, grain protein content and yield. PM and UC estimates were significantly correlated for all traits (PM: 0.38, 0.63, 0.51 and 0.91; UC: 0.45, 0.52, 0.54 and 0.74; for yield, grain protein content, plant height and heading date, respectively), while SD was correlated only for heading date and plant height (0.64 and 0.49, respectively). According to simulations, SD estimations in the field would necessitate large progenies. This pioneering study experimentally validates genomic prediction of UC but the predictive ability depends on trait architecture and precision of marker effect estimates. We advise the breeders to adjust progeny size to realize the SD potential of a cross.

BLUPmrMLM: A Fast mrMLM Algorithm in Genome-wide Association Studies

Multilocus genome-wide association study has become the state-of-the-art tool for dissecting the genetic architecture of complex and multiomic traits. However, most existing multilocus methods require relatively long computational time when analyzing large datasets. To address this issue, in this study, we proposed a fast mrMLM method, namely, best linear unbiased prediction multilocus random-SNP-effect mixed linear model (BLUPmrMLM). First, genome-wide single-marker scanning in mrMLM was replaced by vectorized Wald tests based on the best linear unbiased prediction (BLUP) values of marker effects and their variances in BLUPmrMLM. Then, adaptive best subset selection (ABESS) was used to identify potentially associated markers on each chromosome to reduce computational time when estimating marker effects via empirical Bayes. Finally, shared memory and parallel computing schemes were used to reduce the computational time. In simulation studies, BLUPmrMLM outperformed GEMMA, EMMAX, mrMLM, and FarmCPU as well as the control method (BLUPmrMLM with ABESS removed), in terms of computational time, power, accuracy for estimating quantitative trait nucleotide positions and effects, false positive rate, false discovery rate, false negative rate, and F1 score. In the reanalysis of two large rice datasets, BLUPmrMLM significantly reduced the computational time and identified more previously reported genes, compared with the aforementioned methods. This study provides an excellent multilocus model method for the analysis of large-scale and multiomic datasets. The software mrMLM v5.1 is available at BioCode (https://ngdc.cncb.ac.cn/biocode/tool/BT007388) or GitHub (https://github.com/YuanmingZhang65/mrMLM).

Ethnic and region-specific genetic risk variants of stroke and its comorbid conditions can define the variations in the burden of stroke and its phenotypic traits

Burden of stroke differs by region, which could be attributed to differences in comorbid conditions and ethnicity. Genomewide variation acts as a proxy marker for ethnicity, and comorbid conditions. We present an integrated approach to understand this variation by considering prevalence and mortality rates of stroke and its comorbid risk for 204 countries from 2009 to 2019, and Genome-wide association studies (GWAS) risk variant for all these conditions. Global and regional trend analysis of rates using linear regression, correlation, and proportion analysis, signifies ethnogeographic differences. Interestingly, the comorbid conditions that act as risk drivers for stroke differed by regions, with more of metabolic risk in America and Europe, in contrast to high systolic blood pressure in Asian and African regions. GWAS risk loci of stroke and its comorbid conditions indicate distinct population stratification for each of these conditions, signifying for population-specific risk. Unique and shared genetic risk variants for stroke, and its comorbid and followed up with ethnic-specific variation can help in determining regional risk drivers for stroke. Unique ethnic-specific risk variants and their distinct patterns of linkage disequilibrium further uncover the drivers for phenotypic variation. Therefore, identifying population- and comorbidity-specific risk variants might help in defining the threshold for risk, and aid in developing population-specific prevention strategies for stroke.

Comprehensive identification of genomic and environmental determinants of phenotypic plasticity in maize

Maize phenotypes are plastic, determined by the complex interplay of genetics and environmental variables. Uncovering the genes responsible and understanding how their effects change across a large geographic region are challenging. In this study, we conducted systematic analysis to identify environmental indices that strongly influence 19 traits (including flowering time, plant architecture, and yield component traits) measured in the maize nested association mapping (NAM) population grown in 11 environments. Identified environmental indices based on day length, temperature, moisture, and combinations of these are biologically meaningful. Next, we leveraged a total of more than 20 million SNP and SV markers derived from recent de novo sequencing of the NAM founders for trait prediction and dissection. When combined with identified environmental indices, genomic prediction enables accurate performance predictions. Genome-wide association studies (GWASs) detected genetic loci associated with the plastic response to the identified environmental indices for all examined traits. By systematically uncovering the major environmental and genomic factors underlying phenotypic plasticity in a wide variety of traits and depositing our results as a track on the MaizeGDB genome browser, we provide a community resource as well as a comprehensive analytical framework to facilitate continuing complex trait dissection and prediction in maize and other crops. Our findings also provide a conceptual framework for the genetic architecture of phenotypic plasticity by accommodating two alternative models, regulatory gene model and allelic sensitivity model, as special cases of a continuum.

The effect of family structure on the still-missing heritability and genomic prediction accuracy of type 2 diabetes

This study aims to assess the effect of familial structures on the still-missing heritability estimate and prediction accuracy of Type 2 Diabetes (T2D) using pedigree estimated risk values (ERV) and genomic ERV. We used 11,818 individuals (T2D cases: 2,210) with genotype (649,932 SNPs) and pedigree information from the ongoing periodic cohort study of the Iranian population project. We considered three different familial structure scenarios, including (i) all families, (ii) all families with ≥ 1 generation, and (iii) families with ≥ 1 generation in which both case and control individuals are presented. Comprehensive simulation strategies were implemented to quantify the difference between estimates of [Formula: see text] and [Formula: see text]. A proportion of still-missing heritability in T2D could be explained by overestimation of pedigree-based heritability due to the presence of families with individuals having only one of the two disease statuses. Our research findings underscore the significance of including families with only case/control individuals in cohort studies. The presence of such family structures (as observed in scenarios i and ii) contributes to a more accurate estimation of disease heritability, addressing the underestimation that was previously overlooked in prior research. However, when predicting disease risk, the absence of these families (as seen in scenario iii) can yield the highest prediction accuracy and the strongest correlation with Polygenic Risk Scores. Our findings represent the first evidence of the important contribution of familial structure for heritability estimations and genomic prediction studies in T2D.

Heritability and genetic correlations of obesity indices and cardiometabolic traits in the Northern Chinese families

OBJECTIVE

This study aimed to investigate the heritability of various obesity indices and their shared genetic factors with cardiometabolic traits in the Chinese nuclear family.

METHODS

A total of 1270 individuals from 538 nuclear families were included in this cross-sectional study. Different indices were used to quantify fat mass and distribution, including body index mass (BMI), visceral fat index (VFI), and body fat percent (BFP). Heritability and genetic correlations for all quantitative traits were estimated using variance component models. The susceptibility-threshold model was utilized to estimate the heritability for binary traits.

RESULTS

Heritability estimates for obesity indices were highest for BMI (59%), followed by BFP (49%), and VFI (40%). Heritability estimates for continuous cardiometabolic traits varied from 24% to 50%. All obesity measures exhibited consistently significant positive genetic correlations with blood pressure, fasting blood glucose, and uric acid (rG range: 0.26-0.57). However, diverse genetic correlations between various obesity indices and lipid profiles were observed. Significant genetic correlations were limited to specific pairs: BFP and total cholesterol (rG = 0.24), BFP and low-density lipoprotein cholesterol (rG = 0.25), and VFI and triglyceride (rG = 0.33).

CONCLUSION

The genetic overlap between various obesity indices and cardiometabolic traits underscores the importance of pleiotropic genes. Further studies are warranted to investigate specific shared genetic and environmental factors between obesity and cardiometabolic diseases.

The potential up-regulation risk of 3' UTR SNP (rs10787760 G > A) for the VAX1 gene is associated with NSCLP in the northwest Chinese population

AIMS

To investigate the association between single nucleotide polymorphisms (SNPs) in 3'UTR region of VAX1, SYT14 and PAX7 genes and the risk of non-syndromic cleft palate (NSCLP) in a northwest Chinese population.

MAIN METHODS

A case-control study was conducted in 406 normal controls and 399 NSCLP patients. Using iMLDRTM genotyping technology, eight SNPs of three genes ((rs10787760, rs7086344 at VAX1), (rs1010113, rs851114, and rs485874 at PAX7), and (rs61820397, rs4609425, rs12133399 at SYT14)) were genotyped to investigate the differences in alleles and genotype distribution frequencies between NSCLP patients and healthy controls. RNA Folding Form software was used to predict RNA secondary structure and expression vectors were constructed to explore the function of the relevant SNP. The effect of SNP polymorphism of gene transcription and translation was assessed using qPCR and Western blot analysis.

KEY FINDINGS

Among the eight SNPs of three genes, rs10787760 of VAX1 gene was found to be associated with an increased risk of NSCLP (OR = 1.341, CI = 1.004-1.790) and the GA genotype of rs10787760 increased the risk of cleft lip and/or palate (CL/P) about 1.42 times (p < 0.05), and carrying the A allele might increase the risk of NSCL/P in male (OR = 1.356, 95 % CI = 1.010-1.823). But there was no association observed with cleft palate only (CPO). Cell function experiments revealed that the G to A mutation in rs10787760 up-regulated GFP-VAX1 transcriptional level by 2.39 and 3.13 times in two cell lines respectively, and enhance the protein expression of the VAX1 gene further. RNA secondary structure study showed that the rs10787760 (G > A) had two different secondary structures in 3'UTR region.

SIGNIFICANCE

The rs10787760 variant in the 3'UTR region of VAX1 gene is associated with CL/P in northwest Chinese population. We hypothesize that the machanism of it might be caused by the RNA differenct fold in the 3'UTR region caused by the polymorphism of the gene.

LEVEL OF EVIDENCE

Original Reports.

A Deep Dive into Statistical Modeling of RNA Splicing QTLs Reveals New Variants that Explain Neurodegenerative Disease

Genome-wide association studies (GWAS) have identified thousands of putative disease causing variants with unknown regulatory effects. Efforts to connect these variants with splicing quantitative trait loci (sQTLs) have provided functional insights, yet sQTLs reported by existing methods cannot explain many GWAS signals. We show current sQTL modeling approaches can be improved by considering alternative splicing representation, model calibration, and covariate integration. We then introduce MAJIQTL, a new pipeline for sQTL discovery. MAJIQTL includes two new statistical methods: a weighted multiple testing approach for sGene discovery and a model for sQTL effect size inference to improve variant prioritization. By applying MAJIQTL to GTEx, we find significantly more sGenes harboring sQTLs with functional significance. Notably, our analysis implicates the novel variant rs582283 in Alzheimer's disease. Using antisense oligonucleotides, we validate this variant's effect by blocking the implicated YBX3 binding site, leading to exon skipping in the gene MS4A3.

Heritability of white matter in twins: A diffusion neuroimaging review

Diffusion neuroimaging has emerged as an essential non-invasive technique to explore in vivo microstructural characteristics of white matter (WM), whose integrity allows complex behaviors and cognitive abilities. Studying the factors contributing to inter-individual variability in WM microstructure can provide valuable insight into structural and functional differences of brain among individuals. Genetic influence on this variation has been largely investigated in twin studies employing different measures derived from diffusion neuroimaging. In this context, we performed a comprehensive literature search across PubMed, Scopus and Web of Science of original twin studies focused on the heritability of WM. Overall, our results highlighted a consistent heritability of diffusion indices (i.e., fractional anisotropy, mean, axial and radial diffusivity), and network topology among twins. The genetic influence resulted prominent in frontal and occipital regions, in the limbic system, and in commissural fibers. To enhance the understanding of genetic influence on WM microstructure further studies in less heterogeneous experimental settings, encompassing all diffusion indices, are warranted.

A broken network of susceptibility genes in the monocytes of Crohn's disease patients

Genome-wide association studies have identified over 200 genetic loci associated with inflammatory bowel disease; however, the mechanism of such a large amount of susceptibility genes remains uncertain. In this study, we integrated bioinformatics analysis and two independent single-cell transcriptome datasets to investigate the expression network of 232 susceptibility genes in Crohn's disease (CD) patients and healthy controls. The study revealed that most of the susceptibility genes are specifically and strictly expressed in the monocytes of the human intestinal tract. The susceptibility genes established a network within the monocytes of health control. The robustness of a gene network may prevent disease onset that is influenced by the genetic and environmental alteration in the expression of susceptibility genes. In contrast, we showed a sparse network in pediatric/adult CD patients, suggesting the broken network contributed to the CD etiology. The network status of susceptibility genes at the single-cell level of monocytes provided novel insight into the etiology.

Pathogenicity of de novo CACNA1D Ca2+ channel variants predicted from sequence co-variation

Voltage-gated L-type Cav1.3 Ca2+ channels support numerous physiological functions including neuronal excitability, sinoatrial node pacemaking, hearing, and hormone secretion. De novo missense mutations in the gene of their pore-forming α1-subunit (CACNA1D) induce severe gating defects which lead to autism spectrum disorder and a more severe neurological disorder with and without endocrine symptoms. The number of CACNA1D variants reported is constantly rising, but their pathogenic potential often remains unclear, which complicates clinical decision-making. Since functional tests are time-consuming and not always available, bioinformatic tools further improving pathogenicity potential prediction of novel variants are needed. Here we employed evolutionary analysis considering sequences of the Cav1.3 α1-subunit throughout the animal kingdom to predict the pathogenicity of human disease-associated CACNA1D missense variants. Co-variation analyses of evolutionary information revealed residue-residue couplings and allowed to generate a score, which correctly predicted previously identified pathogenic variants, supported pathogenicity in variants previously classified as likely pathogenic and even led to the re-classification or re-examination of 18 out of 80 variants previously assessed with clinical and electrophysiological data. Based on the prediction score, we electrophysiologically tested one variant (V584I) and found significant gating changes associated with pathogenic risks. Thus, our co-variation model represents a valuable addition to complement the assessment of the pathogenicity of CACNA1D variants completely independent of clinical diagnoses, electrophysiology, structural or biophysical considerations, and solely based on evolutionary analyses.

Comprehensive Genetic Analysis of Associations between Obesity-Related Parameters and Physical Activity: A Scoping Review

Genetic epidemiological studies have shown that numerous genetic variants cumulatively increase obesity risk. Although genetically predisposed individuals are more prone to developing obesity, it has been shown that physical activity can modify the genetic predisposition to obesity. Therefore, genetic data obtained from earlier studies, including 30 polymorphisms located in 18 genes, were analyzed using novel methods such as the total genetic score and Biofilter 2.4 software to combine genotypic and phenotypic information for nine obesity-related traits measured before and after the realization of the 12-week training program. The results revealed six genes whose genotypes were most important for post-training changes-LEP, LEPR, ADIPOQ, ADRA2A, ADRB3, and DRD2. Five noteworthy pairwise interactions, LEP × LEPR, ADRB2 × ADRB3, ADRA2A × ADRB3, ADRA2A × ADRB2, ADRA2A × DRD2, and three specific interactions demonstrating significant associations with key parameters crucial for health, total cholesterol (TC), high-density lipoprotein (HDL), and fat-free mass (FFM), were also identified. The molecular basis of training adaptation described in this study would have an enormous impact on the individualization of training programs, which, designed according to a given person's genetic profile, will be effective and safe intervention strategies for preventing obesity and improving health.

Insights from homozygous signatures of cervus nippon revealed genetic architecture for components of fitness

This study investigates the genomic landscape of Sika deer populations, emphasizing the detection and characterization of runs of homozygosity (ROH) and their contribution towards components of fitness. Using 85,001 high-confidence SNPs, the investigation into ROH distribution unveiled nuanced patterns of autozygosity across individuals especially in 2 out of the 8 farms, exhibiting elevated ROH levels and mean genome coverage under ROH segments. The prevalence of shorter ROH segments (0.5-4 Mb) suggests historical relatedness and potential selective pressures within these populations. Intriguingly, despite observed variations in ROH profiles, the overall genomic inbreeding coefficient (FROH) remained relatively low across all farms, indicating a discernible degree of genetic exchange and effective mitigation of inbreeding within the studied Sika deer populations. Consensus ROH (cROH) were found to harbor genes for important functions viz., EGFLAM gene which is involved in the vision function of the eye, SKP2 gene which regulates cell cycle, CAPSL involved in adipogenesis, SPEF2 which is essential for sperm flagellar assembly, DCLK3 involved in the heat stress. This first ever study on ROH in Sika deer, to shed light on the adaptive role of genes in these homozygous regions. The insights garnered from this study have broader implications in the management of genetic diversity in this vulnerable species.

Inheritance patterns of lower urinary tract symptoms in adults: a systematic review

OBJECTIVE

To compile and evaluate the heritability and inheritance patterns of lower urinary tract symptoms (LUTS) in adult cohorts.

METHODS

Searches of five databases (PubMed, Embase, APA PsycInfo, Global Health, and OVID Medline) commenced on 6 July 2024, resulting in 736 articles retrieved after deduplication. Studies evaluating heritability patterns, gene frequencies, and familial aggregation of symptoms were included for review. Screening and predefined eligibility criteria produced 34 studies for final review. A descriptive analysis of synthesised data was performed, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. The Cochrane Risk of Bias in Non-Randomised Studies of Interventions (ROBINS-I) tool and the Johanna Briggs Institute checklist were used to evaluate these studies.

RESULTS

Ten of the 34 studies (29%) described general LUTS, 14 (41%) described symptoms due to benign prostatic enlargement (BPE), nine (26%) described urinary incontinence (UI; urge UI [UUI], stress UI [SUI] and mixed UI [MUI]), four (12%) described nocturia alone, two (6%) described overactive bladder (OAB), and four (13%) described other specific symptoms (frequency, postvoid residual urine volume). BPE symptoms, UI (MUI and UUI), nocturia alone, and frequency alone were associated with genetic predisposition, whilst OAB and SUI had more modest inheritance.

CONCLUSION

The pathogenetic and pharmacological mechanisms fundamental to LUTS manifestation are highly heterogeneous. Further work is required to evaluate the inheritance patterns of LUTS more extensively.

Contribution of rare variants to heritability of a disease is much greater than conventionally estimated: modification of allele distribution model

"Missing heritability" is a current problem in human genetics. I previously reported a method to estimate heritability of a polymorphism (hp2) for a common disease without calculating the genetic variance under dominant and the recessive models. Here, I extend the method to the co-dominant model and carry out trial calculations of hp2. I also calculate hp2 applying the allele distribution model originally reported by Pawitan et al. for comparison as a conventional method. But unexpectedly, hp2 calculated for rare variants with high odds ratios was much higher than the calculated values with the allele distribution model. Also, while examining the basis for the difference in calculated hp2, I noticed that conventional methods use the allele frequency (AF) of a variant in the general population to calculate the genetic variance of that variant. However, this implicitly assumes that the unaffected are included among the phenotypes of the disease - an assumption that is inconsistent with case-control studies in which unaffected individuals belong to the control (unaffected) group. Therefore, I modified the allele distribution model by using the AF in the patient population. Consequently, the hp2 of rare variants calculated with the modified allele distribution model was quite high. Recalculating hp2 of several rare variants reported in the literature with the modified allele distribution model yielded results were 3.2 - 53.7 times higher than the hp2 calculated with the original allele distribution model. These results suggest that the contribution of rare variants to heritability of a disease has been considerably underestimated.

Crosstalk between epitranscriptomic and epigenomic modifications and its implication in human diseases

Crosstalk between N6-methyladenosine (m6A) and epigenomes is crucial for gene regulation, but its regulatory directionality and disease significance remain unclear. Here, we utilize quantitative trait loci (QTLs) as genetic instruments to delineate directional maps of crosstalk between m6A and two epigenomic traits, DNA methylation (DNAme) and H3K27ac. We identify 47 m6A-to-H3K27ac and 4,733 m6A-to-DNAme and, in the reverse direction, 106 H3K27ac-to-m6A and 61,775 DNAme-to-m6A regulatory loci, with differential genomic location preference observed for different regulatory directions. Integrating these maps with complex diseases, we prioritize 20 genome-wide association study (GWAS) loci for neuroticism, depression, and narcolepsy in brain; 1,767 variants for asthma and expiratory flow traits in lung; and 249 for coronary artery disease, blood pressure, and pulse rate in muscle. This study establishes disease regulatory paths, such as rs3768410-DNAme-m6A-asthma and rs56104944-m6A-DNAme-hypertension, uncovering locus-specific crosstalk between m6A and epigenomic layers and offering insights into regulatory circuits underlying human diseases.

Unraveling schizophrenia's genetic complexity through advanced causal inference and chromatin 3D conformation

Schizophrenia is a polygenic complex disease with a heritability as high as 80 %, yet the mechanism of polygenic interaction in its pathogenesis remains unclear. Studying the interaction and regulation of schizophrenia susceptibility genes is crucial for unraveling the pathogenesis of schizophrenia and developing antipsychotic drugs. Therefore, we developed a bioinformatics method named GRACI (Gene Regulation Analysis based on Causal Inference) based on the principles of information theory, a causal inference model, and high order chromatin 3D conformation. GRACI captures the interaction and regulatory relationships between schizophrenia susceptibility genes by analyzing genotyping data. Two datasets, comprising 1459 and 2065 samples respectively, were analyzed, and the gene networks from both datasets were constructed. GRACI showcased superior accuracy when compared to widely adopted methods for detecting gene-gene interactions and intergenic regulation. This alignment was further substantiated by its correlation with chromatin high-order conformation patterns. Using GRACI, we identified three potential genes-KCNN3, KCNH1, and KCND3-that are directly associated with schizophrenia pathogenesis. Furthermore, the results of GRACI on the standalone dataset illustrated the method's applicability to other complex diseases. GRACI download: https://github.com/liuliangjie19/GRACI.

Gene‒Environment Interaction Between CAST Gene and Eye-Rubbing in the Chinese Keratoconus Cohort Study: A Case-Only Study

Purpose

Keratoconus (KC), characterized by progressive corneal protrusion and thinning, is a complex disease influenced by the combination of genetic and environmental factors. The purpose of this study was to explore potential gene‒environment interaction between the calpastatin (CAST) gene and eye-rubbing in KC.

Methods

A case-only study including 930 patients (676 patients with eye-rubbing and 254 patients without eye-rubbing) from the Chinese Keratoconus (CKC) cohort study was performed in the present study. Genotyping of single nucleotide polymorphism (SNP) was conducted using the Illumina Infinium Human Asian Screening Array (ASA) Beadchip. The gene‒environment interactions between CAST gene and eye-rubbing were analyzed using PLINK version 1.90. The interactions between CAST genotypes and eye-rubbing were analyzed by logistic regression models. The SNP-SNP-environment interactions were analyzed using generalized multifactor dimensionality reduction (GMDR).

Results

Three SNPs in CAST gene, namely, rs26515, rs27991, and rs9314177, reached the significance threshold for interactions (defined as P < 2.272 × 10-3). Notably, the minor alleles of these three SNPs exhibited negative interactions with eye-rubbing in KC. The results of logistic regression models revealed that the minor allele homozygotes and heterozygotes of rs26515, rs27991, and rs9314177 also exhibited negative interactions with eye-rubbing. Furthermore, GMDR analysis revealed the significant SNP-SNP-environment interactions among rs26515, rs27991, rs9314177, and eye-rubbing in KC.

Conclusions

This study identified rs26515, rs27991, and rs9314177 in CAST gene existed gene-environment interactions with eye-rubbing in KC, which is highly important for understanding the underlying biological mechanisms of KC and guiding precision prevention and proper management.

Assessing the lack of diversity in genetics research across neurodegenerative diseases: A systematic review of the GWAS Catalog and literature

The under-representation of non-European cohorts in neurodegenerative disease genome-wide association studies (GWAS) hampers precision medicine efforts. Despite the inherent genetic and phenotypic diversity in these diseases, GWAS research consistently exhibits a disproportionate emphasis on participants of European ancestry. This study reviews GWAS up to 2022, focusing on non-European or multi-ancestry neurodegeneration studies. We conducted a systematic review of GWAS results and publications up to 2022, focusing on non-European or multi-ancestry neurodegeneration studies. Rigorous article inclusion and quality assessment methods were employed. Of 123 neurodegenerative disease (NDD) GWAS reviewed, 82% predominantly featured European ancestry participants. A single European study identified over 90 risk loci, compared to a total of 50 novel loci in identified in all non-European or multi-ancestry studies. Notably, only six of the loci have been replicated. The significant under-representation of non-European ancestries in NDD GWAS hinders comprehensive genetic understanding. Prioritizing genomic diversity in future research is crucial for advancing NDD therapies and understanding. HIGHLIGHTS: Eighty-two percent of neurodegenerative genome-wide association studies (GWAS) focus on Europeans. Only 6 of 50 novel neurodegenerative disease (NDD) genetic loci have been replicated. Lack of diversity significantly hampers understanding of NDDs. Increasing diversity in NDD genetic research is urgently required. New initiatives are aiming to enhance diversity in NDD research.

Genetics of Metabolic Dysfunction-associated Steatotic Liver Disease: The State of Art Update

Recent advances in the genetics of metabolic dysfunction-associated steatotic liver disease (MASLD) are gradually revealing the mechanisms underlying the heterogeneity of the disease and have shown promising results in patient stratification. Genetic characterization of the disease has been rapidly developed using genome-wide association studies, exome-wide association studies, phenome-wide association studies, and whole exome sequencing. These advances have been powered by the increase in computational power, the development of new analytical algorithms, including some based on artificial intelligence, and the recruitment of large and well-phenotyped cohorts. This review presents an update on genetic studies that emphasize new biological insights from next-generation sequencing approaches. Additionally, we discuss innovative methods for discovering new genetic loci for MASLD, including rare variants. To comprehensively manage MASLD, it is important to stratify risks. Therefore, we present an update on phenome-wide association study associations, including extreme phenotypes. Additionally, we discuss whether polygenic risk scores and targeted sequencing are ready for clinical use. With particular focus on precision medicine, we introduce concepts such as the interplay between genetics and the environment in modulating genetic risk with lifestyle or standard therapies. A special chapter is dedicated to gene-based therapeutics. The limitations of approved pharmacological approaches are discussed, and the potential of gene-related mechanisms in therapeutic development is reviewed, including the decision to perform genetic testing in patients with MASLD.

Association between waist circumference and chronic pain: insights from observational study and two-sample Mendelian randomization

Background

Current research offers limited clarity on the correlation between waist circumference and chronic pain prevalence.

Objective

This investigation seeks to elucidate the potential relationship between waist circumference and chronic pain and their causal association.

Methods

An observational study was conducted, leveraging data from the National Health and Nutrition Examination Survey (NHANES) collected between 2001 and 2004. The multivariable logistic regression was used to assess the relationship between waist circumference and chronic pain. Furthermore, a meta-analysis of Mendelian Randomization (MR) was applied to explore a causal relationship between waist circumference and pain.

Results

The observational study, post multivariable adjustment, indicated that an increase in waist circumference by 1 dm (decimeter) correlates with a 14% elevation in chronic pain risk (Odds Ratio [OR] = 1.14, 95% Confidence Interval [CI]: 1.04-1.24, p = 0.01). Moreover, the meta-analysis of MR demonstrated that an increased waist circumference was associated with a genetic predisposition to pain risk (OR = 1.14, 95%CI: 1.06-1.23, p = 0.0007).

Conclusion

Observational analysis confirmed a significant relationship between increased waist circumference and the incidence of chronic pain, and results based on MR Study identified increased waist circumference as potentially causal for pain.

A high-dimensional omnibus test for set-based association analysis

Set-based association analysis is a valuable tool in studying the etiology of complex diseases in genome-wide association studies, as it allows for the joint testing of variants in a region or group. Two common types of single nucleotide polymorphism (SNP)-disease functional models are recognized when evaluating the joint function of a set of SNP: the cumulative weak signal model, in which multiple functional variants with small effects contribute to disease risk, and the dominating strong signal model, in which a few functional variants with large effects contribute to disease risk. However, existing methods have two main limitations that reduce their power. Firstly, they typically only consider one disease-SNP association model, which can result in significant power loss if the model is misspecified. Secondly, they do not account for the high-dimensional nature of SNPs, leading to low power or high false positives. In this study, we propose a solution to these challenges by using a high-dimensional inference procedure that involves simultaneously fitting many SNPs in a regression model. We also propose an omnibus testing procedure that employs a robust and powerful P-value combination method to enhance the power of SNP-set association. Our results from extensive simulation studies and a real data analysis demonstrate that our set-based high-dimensional inference strategy is both flexible and computationally efficient and can substantially improve the power of SNP-set association analysis. Application to a real dataset further demonstrates the utility of the testing strategy.

Genome-wide detection of multiple variants associated with teat number in French Yorkshire pigs

BACKGROUND

Teat number is a vital reproductive trait in sows, crucial for providing immunity and nutrition to piglets during lactation. However, "missing heritability" in Single Nucleotide Polymorphism (SNP)-based Genome-Wide Association Studies (GWAS) has led to an increasing focus on structural variations in the genetic analysis of complex biological traits.

RESULTS

In this study, we generated a comprehensive CNV map in a population of French Yorkshire pigs (n = 644) and identified 429 CNVRs. Notably, 44% (189 CNVRs) of these were detected for the first time. Subsequently, we conducted GWAS for teat number in the French Yorkshire pig population using both 80K chip and its imputed data, as well as a GWAS analysis based on CNV regions (CNVR). Interestingly, 80K chip GWAS identified two SNPs located on Sus scrofa chromosome 5 (SSC5) that were simultaneously associated with Total Teat Number (TTN), Left Teat Number (LTN), and Right Teat Number (RTN). The leading SNP (WU_10.2_5_76130558) explained 3.33%, 2.69%, and 2.67% of the phenotypic variance for TTN, LTN, and RTN, respectively. Moreover, through imputed GWAS, we successfully identified 30 genetic variants associated with TTN located within the 73.22 -73.30 Mb region on SSC5. The two SNPs identified in the 80K chip GWAS were also located in this region. In addition, CNVR-based GWAS revealed three significant CNVRs associated with TTN. Finally, through gene annotation, we pinpointed two candidate genes, TRIM66 and PRICKLE1, which are related to diverse processes such as breast cancer and abnormal vertebral development.

CONCLUSIONS

Our research provides an in-depth analysis of the complex genetic structure underlying teat number, contributing to the genetic enhancement of sows with improved reproductive performance and, ultimately, bolstering the economic benefits of swine production enterprises.

The relationship between loneliness and blood glucose: a cross-sectional survey among Japanese

Recently, researchers have uncovered a correlation between loneliness and both the development and management of diabetes. Nevertheless, previous studies employing an unvalidated loneliness questionnaire impair result accuracy. Furthermore, this aspect has not been researched in the Japanese population. Therefore, this cross-sectional study analyzed data from the Kanagawa prospective "ME-BYO" Cohort Study (ME-BYO cohort) to investigate the correlation between loneliness, as measured by 20 items on the UCLA Loneliness Scale, and blood glucose levels. A total of 666 participants were included in the analysis, with a mean age of 54.1 years and a mean BMI of 23 kg/m2. Half of the participants had obtained an education level beyond high school. The mean household income and physical activity level were reported as 6.83 million Japanese yen and 12.3 METs-h/day, respectively. Model 1 of the linear regression analysis determined that there was no significant association between the loneliness scale and HbA1c (p = 0.512). After adjusting for age, gender, BMI (model 2), sitting time, physical activity level (model 3), housemates, household income, and final education (model 4), and controlling for social support, quality of life, and depression (model 5), the results showed no significant association, with a p-value of 0.823, 0.791, 0.792, and 0.816, respectively. Thus, the study found no link between loneliness and HbA1c in the high SES population. This finding contradicts previous results and may be attributed to the impact of population characteristics, SES status, or genetic backgrounds.

A functional schizophrenia-associated genetic variant near the TSNARE1 and ADGRB1 genes

Recent collaborative genome-wide association studies (GWAS) have identified >200 independent loci contributing to risk for schizophrenia (SCZ). The genes closest to these loci have diverse functions, supporting the potential involvement of multiple relevant biological processes, yet there is no direct evidence that individual variants are functional or directly linked to specific genes. Nevertheless, overlap with certain epigenetic marks suggest that most GWAS-implicated variants are regulatory. Based on the strength of association with SCZ and the presence of regulatory epigenetic marks, we chose one such variant near TSNARE1 and ADGRB1, rs4129585, to test for functional potential and assay differences that may drive the pathogenicity of the risk allele. We observed that the variant-containing sequence drives reporter expression in relevant neuronal populations in zebrafish. Next, we introduced each allele into human induced pluripotent cells and differentiated four isogenic clones homozygous for the risk allele and five clones homozygous for the non-risk allele into neural progenitor cells. Employing RNA sequencing, we found that the two alleles yield significant transcriptional differences in the expression of 109 genes at a false discovery rate (FDR) of <0.05 and 259 genes at a FDR of <0.1. We demonstrate that these genes are highly interconnected in pathways enriched for synaptic proteins, axon guidance, and regulation of synapse assembly. Exploration of genes near rs4129585 suggests that this variant does not regulate TSNARE1 transcripts, as previously thought, but may regulate the neighboring ADGRB1, a regulator of synaptogenesis. Our results suggest that rs4129585 is a functional common variant that functions in specific pathways likely involved in SCZ risk.

Replication of Known and Identification of Novel Associations in Biobank-Scale Datasets: A Survey Using UK Biobank and FinnGen

Over the last two decades, numerous genome-wide association studies (GWAS) have been performed to unveil the genetic architecture of human complex traits. Despite multiple efforts aimed at the trans-biobank integration of GWAS results, no systematic analysis of the variant-level properties affecting the replication of known associations (or identifying novel ones) in genome-wide meta-analysis has yet been performed using biobank-scale data. To address this issue, we performed a systematic comparison of GWAS summary statistics for 679 complex traits in the UK Biobank (UKB) and FinnGen (FG) cohorts. We identified 37,148 index variants with genome-wide associations with at least one trait in either cohort or in the meta-analysis, only 3528 (9.5%) of which were shared between UKB and FG. Nearly twice as many variants (6577) were replicated in another dataset at the significance level adjusted for the number of variants selected for replication. However, as many as 9230 loci failed to be replicated. Moreover, as many as 5813 loci were observed as significant associations only in meta-analysis results, highlighting the importance of trans-biobank meta-analysis efforts. We showed that variants that failed to replicate in UKB or FG tend to correspond to rare, less pleiotropic variants with lower effect sizes and lower LD score values. Genome-wide associations specific to meta-analysis were also enriched in low-effect variants; however, such variants tended to be more common and have more consistent frequencies between populations. Taken together, our results show a relatively high rate of non-replication of genome-wide associations in the studied cohorts and highlight both widely appreciated and less acknowledged properties of the associations affecting their identification and replication.

Genetic and Non-Genetic Contributions to Eosinophilic Granulomatosis with Polyangiitis: Current Knowledge and Future Perspectives

In this work, we present a comprehensive overview of the genetic and non-genetic complexity of eosinophilic granulomatosis with polyangiitis (EGPA). EGPA is a rare complex systemic disease that occurs in people presenting with severe asthma and high eosinophilia. After briefly introducing EGPA and its relationship with the anti-neutrophil cytoplasmic autoantibodies (ANCA)-associated vasculitis (AAVs), we delve into the complexity of this disease. At first, the two main biological actors, ANCA and eosinophils, are presented. Biological and clinical phenotypes related to ANCA positivity or negativity are explained, as well as the role of eosinophils and their pathological subtypes, pointing out their intricate relations with EGPA. Then, the genetics of EGPA are described, providing an overview of the research effort to unravel them. Candidate gene studies have investigated biologically relevant candidate genes; the more recent genome-wide association studies and meta-analyses, able to analyze the whole genome, have confirmed previous associations and discovered novel risk loci; in the end, family-based studies have dissected the contribution of rare variants and the heritability of EGPA. Then, we briefly present the environmental contribution to EGPA, reporting seasonal events and pollutants as triggering factors. In the end, the latest omic research is discussed and the most recent epigenomic, transcriptomic and microbiome studies are presented, highlighting the current challenges, open questions and suggesting approaches to unraveling this complex disease.

Elucidating the nexus between onco-immunology and kidney transplantation: An insight from precision medicine perspective

The interplay of onco-immunology and kidney transplantation heralds a transformative era in medical science. This integration, while promising, presents significant challenges. Chief among these is the dichotomy of immunosuppression-boosting immunity against malignancies while suppressing it for graft survival. Additionally, limited clinical data on novel therapies, genetic variations influencing responses, economic concerns, and the narrow therapeutic window for post-transplant malignancies necessitate strategic addressal. Conversely, opportunities abound, including personalized immune monitoring, targeted therapies, minimized immunosuppression, and improved patient quality of life. Emphasizing collaborative research and interdisciplinary cooperation, the merging of these fields offers the potential for enhanced graft survival and reduced post-transplant malignancy risks. As we harness modern technology and promote patient-centric care, the vision for the future of kidney transplantation becomes increasingly hopeful, paving the way for more personalized and effective treatments. The article aims to elucidate the critical challenge of balancing immunosuppression to simultaneously combat malignancies and ensure graft survival. It addresses the scarcity of clinical data on novel therapies, the impact of genetic variations on treatment responses, and the economic and therapeutic concerns in managing post-transplant malignancies. Furthermore, it explores the opportunities precision medicine offers, such as personalized immune monitoring, targeted therapies, and reduced immunosuppression, which could significantly improve patient outcomes. Highlighting the importance of collaborative research and interdisciplinary efforts, the article seeks to demonstrate the potential for enhanced graft survival and reduced post-transplant malignancy risks. By leveraging modern technology and prioritizing patient-centric care, it envisions a future where kidney transplantation is more personalized and effective, offering hope for advancements in this field.

Genetic and Epigenetic Landscape for Drug Development in Polycystic Ovary Syndrome

The treatment of polycystic ovary syndrome (PCOS) faces challenges as all known treatments are merely symptomatic. The US Food and Drug Administration has not approved any drug specifically for treating PCOS. As the significance of genetics and epigenetics rises in drug development, their pivotal insights have greatly enhanced the efficacy and success of drug target discovery and validation, offering promise for guiding the advancement of PCOS treatments. In this context, we outline the genetic and epigenetic advancement in PCOS, which provide novel insights into the pathogenesis of this complex disease. We also delve into the prospective method for harnessing genetic and epigenetic strategies to identify potential drug targets and ensure target safety. Additionally, we shed light on the preliminary evidence and distinctive challenges associated with gene and epigenetic therapies in the context of PCOS.

Utility of polygenic risk scores to aid in the diagnosis of rheumatic diseases

Rheumatic diseases (RDs) are characterized by autoimmunity and autoinflammation and are recognized as complex due to the interplay of multiple genetic, environmental, and lifestyle factors in their pathogenesis. The rapid advancement of genome-wide association studies (GWASs) has enabled the identification of numerous single nucleotide polymorphisms (SNPs) associated with RD susceptibility. Based on these SNPs, polygenic risk scores (PRSs) have emerged as promising tools for quantifying genetic risk in this disease group. This chapter reviews the current status of PRSs in assessing the risk of RDs and discusses their potential to improve the accuracy of the diagnosis of these complex diseases through their ability to discriminate among different RDs. PRSs demonstrate a high discriminatory capacity for various RDs and show potential clinical utility. As GWASs continue to evolve, PRSs are expected to enable more precise risk stratification by integrating genetic, environmental, and lifestyle factors, thereby refining individual risk predictions and advancing disease management strategies.

Genome-wide analyses reveal a potential role for the MAPT, MOBP, and APOE loci in sporadic frontotemporal dementia

Frontotemporal dementia (FTD) is the second most common cause of early-onset dementia after Alzheimer disease (AD). Efforts in the field mainly focus on familial forms of disease (fFTDs), while studies of the genetic etiology of sporadic FTD (sFTD) have been less common. In the current work, we analyzed 4,685 sFTD cases and 15,308 controls looking for common genetic determinants for sFTD. We found a cluster of variants at the MAPT (rs199443; p = 2.5 × 10-12, OR = 1.27) and APOE (rs6857; p = 1.31 × 10-12, OR = 1.27) loci and a candidate locus on chromosome 3 (rs1009966; p = 2.41 × 10-8, OR = 1.16) in the intergenic region between RPSA and MOBP, contributing to increased risk for sFTD through effects on expression and/or splicing in brain cortex of functionally relevant in-cis genes at the MAPT and RPSA-MOBP loci. The association with the MAPT (H1c clade) and RPSA-MOBP loci may suggest common genetic pleiotropy across FTD and progressive supranuclear palsy (PSP) (MAPT and RPSA-MOBP loci) and across FTD, AD, Parkinson disease (PD), and cortico-basal degeneration (CBD) (MAPT locus). Our data also suggest population specificity of the risk signals, with MAPT and APOE loci associations mainly driven by Central/Nordic and Mediterranean Europeans, respectively. This study lays the foundations for future work aimed at further characterizing population-specific features of potential FTD-discriminant APOE haplotype(s) and the functional involvement and contribution of the MAPT H1c haplotype and RPSA-MOBP loci to pathogenesis of sporadic forms of FTD in brain cortex.

Somatic Variants Acquired Later in Life Associated with Thoracic Aortic Aneurysms: JAK2 V617F

The JAK2 V617F somatic variant is a well-known driver of myeloproliferative neoplasms (MPN) associated with an increased risk for athero-thrombotic cardiovascular disease. Recent studies have demonstrated its role in the development of thoracic aortic aneurysm (TAA). However, limited clinical information and level of JAK2 V617F burden have been provided for a comprehensive evaluation of potential confounders. A retrospective genotype-first study was conducted to identify carriers of the JAK2 V617F variant from an internal exome sequencing database in Yale DNA Diagnostics Lab. Additionally, the overall incidence of somatic variants in the JAK2 gene across various tissue types in the healthy population was carried out based on reanalysis of SomaMutDB and data from the UK Biobank (UKBB) cohort to compare our dataset to the population prevalence of the variant. In our database of 12,439 exomes, 594 (4.8%) were found to have a thoracic aortic aneurysm (TAA), and 12 (0.049%) were found to have a JAK2 V617F variant. Among the 12 JAK2 V617F variant carriers, five had a TAA (42%), among whom four had an ascending TAA and one had a descending TAA, with a variant allele fraction ranging from 11.2% to 20%. Among these five patients, 60% were female, and average age at diagnosis was 70 (49-79). The mean ascending aneurysm size was 5.05 cm (range 4.6-5.5 cm), and four patients had undergone surgical aortic replacement or repair. UKBB data revealed a positive correlation between the JAK2 V617F somatic variant and aortic valve disease (effect size 0.0086, p = 0.85) and TAA (effect size = 0.004, p = 0.92), although not statistically significant. An unexpectedly high prevalence of TAA in our dataset (5/594, 0.84%) is greater than the prevalence reported before for the general population, supporting its association with TAA. JAK2 V617F may contribute a meaningful proportion of otherwise unexplained aneurysm patients. Additionally, it may imply a potential JAK2-specific disease mechanism in the developmental of TAA, which suggests a possible target of therapy that warrants further investigation.

Functional Genomics in Psoriasis

Psoriasis is an autoimmune cutaneous condition that significantly impacts quality of life and represents a burden on society due to its prevalence. Genome-wide association studies (GWASs) have pinpointed several psoriasis-related risk loci, underlining the disease's complexity. Functional genomics is paramount to unveiling the role of such loci in psoriasis and disentangling its complex nature. In this review, we aim to elucidate the main findings in this field and integrate our discussion with gold-standard techniques in molecular biology-i.e., Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-and high-throughput technologies. These tools are vital to understanding how disease risk loci affect gene expression in psoriasis, which is crucial in identifying new targets for personalized treatments in advanced precision medicine.

Genomic prediction in Brassica napus: evaluating the benefit of imputed whole-genome sequencing data

Advances in sequencing technology allow whole plant genomes to be sequenced with high quality. Combining genotypic and phenotypic data in genomic prediction helps breeders to select crossing partners in partially phenotyped populations. In plant breeding programs, the cost of sequencing entire breeding populations still exceeds available genotyping budgets. Hence, the method for genotyping is still mainly single nucleotide polymorphism (SNP) arrays; however, arrays are unable to assess the entire genome- and population-wide diversity. A compromise involves genotyping the entire population using an SNP array and a subset of the population with whole-genome sequencing. Both datasets can then be used to impute markers from whole-genome sequencing onto the entire population. Here, we evaluate whether imputation of whole-genome sequencing data enhances genomic predictions, using data from a nested association mapping population of rapeseed (Brassica napus). Employing two cross-validation schemes that mimic scenarios for the prediction of close and distant relatives, we show that imputed marker data do not significantly improve prediction accuracy, likely due to redundancy in relationship estimates and imputation errors. In simulation studies, only small improvements were observed, further corroborating the findings. We conclude that SNP arrays are already equipped with the information that is added by imputation through relationship and linkage disequilibrium.

PathGPS: discover shared genetic architecture using GWAS summary data

The increasing availability and scale of biobanks and "omic" datasets bring new horizons for understanding biological mechanisms. PathGPS is an exploratory data analysis tool to discover genetic architectures using Genome Wide Association Studies (GWAS) summary data. PathGPS is based on a linear structural equation model where traits are regulated by both genetic and environmental pathways. PathGPS decouples the genetic and environmental components by contrasting the GWAS associations of "signal" genes with those of "noise" genes. From the estimated genetic component, PathGPS then extracts genetic pathways via principal component and factor analysis, leveraging the low-rank and sparse properties. In addition, we provide a bootstrap aggregating ("bagging") algorithm to improve stability under data perturbation and hyperparameter tuning. When applied to a metabolomics dataset and the UK Biobank, PathGPS confirms several known gene-trait clusters and suggests multiple new hypotheses for future investigations.

Etiology of Borderline Intellectual Functioning

Borderline intellectual functioning (BIF), characterized by intelligence quotient scores between 70 and 85, can lead to challenges in daily life. This review explored the multifaceted nature of BIF by examining the interplay between genetic predisposition, prenatal/perinatal factors, environmental influences, and underlying medical conditions.