Risk Loci Research Articles

Novel risk loci for COVID-19 hospitalization among admixed American populations.

The genetic basis of severe COVID-19 has been thoroughly studied, and many genetic risk factors shared between populations have been identified. However, reduced sample sizes from non-European groups have limited the discovery of population-specific common risk loci. In this second study nested in the SCOURGE consortium, we conducted a genome-wide association study (GWAS) for COVID-19 hospitalization in admixed Americans, comprising a total of 4702 hospitalized cases recruited by SCOURGE and seven other participating studies in the COVID-19 Host Genetic Initiative. We identified four genome-wide significant associations, two of which constitute novel loci and were first discovered in Latin American populations (BAZ2B and DDIAS). A trans-ethnic meta-analysis revealed another novel cross-population risk locus in CREBBP. Finally, we assessed the performance of a cross-ancestry polygenic risk score in the SCOURGE admixed American cohort. This study constitutes the largest GWAS for COVID-19 hospitalization in admixed Latin Americans conducted to date. This allowed to reveal novel risk loci and emphasize the need of considering the diversity of populations in genomic research.

Enrichment of Allelic Editing Outcomes by Prime Editing in Induced Pluripotent Stem Cells.

Gene editing in human induced pluripotent stem (iPS) cells with programmable nucleases facilitates reliable disease models, but methods using double-strand break repair often produce random on-target by-products. Prime editing (PE) combines Cas9 nickase with reverse transcriptase and PE guide RNA (pegRNA) encoding a repair template to reduce by-products. We implemented a GMP-compatible protocol for transfecting Cas9- or PE-2A-mCherry plasmids to track and fractionate human iPS cells based on PE expression level. We compared the editing outcomes of Cas9- and PE-based methods in a GFP-to-BFP conversion assay at the HEK3 benchmark locus and at the APOE Alzheimer's risk locus, revealing superior precision of PE at high expression levels. Moreover, sorting cells for PE expression level influenced allelic editing outcomes at the target loci. We expect that our findings will aid in the creation of gene-edited human iPS cells with intentional heterozygous and homozygous genotypes.

Identification of Genetic Variants in Progressive Supranuclear Palsy in Southeast Asia.

Progressive supranuclear palsy (PSP) is largely a sporadic disease with few reported familial cases. Genome-wide association studies (GWAS) in sporadic PSP in Caucasian populations have identified MAPT as the most commonly associated genetic risk locus with the strongest effect size. At present there are limited data on genetic factors associated with PSP in Asian populations. Our goal was to investigate the genetic factors associated with PSP in Southeast Asian PSP patients. Next-generation sequencing (whole-exome, whole-genome and targeted sequencing) was performed in two Asian cohorts, comprising 177 PSP patients. We identified 17 pathogenic or likely pathogenic variants in 16 PSP patients (9%), eight of which were novel. The most common relevant genetic variants identified were in MAPT, GBA1, OPTN, SYNJ1, and SQSTM1. Other variants detected were in TBK1, PRNP, and ABCA7-genes that have been implicated in other neurodegenerative diseases. Eighteen patients had a positive family history, of whom two carried pathogenic MAPT variants, and one carried a likely pathogenic GBA1 variant. None of the patients had expanded repeats in C9orf72. Furthermore, we found 16 different variants of uncertain significance in 21 PSP patients in PSEN2, ABCA7, SMPD1, MAPT, ATP13A2, OPTN, SQSTM1, CYLD, and BSN. The genetic findings in our PSP cohorts appear to be somewhat distinct from those in Western populations, and also suggest an overlap of the genetic architecture between PSP and other neurodegenerative diseases. Further functional studies and validation in independent Asian cohorts will be useful for improving our understanding of PSP genetics and guiding genetic screening strategies in these populations. © 2024 International Parkinson and Movement Disorder Society.

Identification of candidate causal variants and target genes at 41 breast cancer risk loci through differential allelic expression analysis

Understanding breast cancer genetic risk relies on identifying causal variants and candidate target genes in risk loci identified by genome-wide association studies (GWAS), which remains challenging. Since most loci fall in active gene regulatory regions, we developed a novel approach facilitated by pinpointing the variants with greater regulatory potential in the disease’s tissue of origin. Through genome-wide differential allelic expression (DAE) analysis, using microarray data from 64 normal breast tissue samples, we mapped the variants associated with DAE (daeQTLs). Then, we intersected these with GWAS data to reveal candidate risk regulatory variants and analysed their cis-acting regulatory potential. Finally, we validated our approach by extensive functional analysis of the 5q14.1 breast cancer risk locus. We observed widespread gene expression regulation by cis-acting variants in breast tissue, with 65% of coding and noncoding expressed genes displaying DAE (daeGenes). We identified over 54 K daeQTLs for 6761 (26%) daeGenes, including 385 daeGenes harbouring variants previously associated with BC risk. We found 1431 daeQTLs mapped to 93 different loci in strong linkage disequilibrium with risk-associated variants (risk-daeQTLs), suggesting a link between risk-causing variants and cis-regulation. There were 122 risk-daeQTL with stronger cis-acting potential in active regulatory regions with protein binding evidence. These variants mapped to 41 risk loci, of which 29 had no previous report of target genes and were candidates for regulating the expression levels of 65 genes. As validation, we identified and functionally characterised five candidate causal variants at the 5q14.1 risk locus targeting the ATG10 and ATP6AP1L genes, likely acting via modulation of alternative transcription and transcription factor binding. Our study demonstrates the power of DAE analysis and daeQTL mapping to identify causal regulatory variants and target genes at breast cancer risk loci, including those with complex regulatory landscapes. It additionally provides a genome-wide resource of variants associated with DAE for future functional studies.

A Novel Metabolomic Aging Clock Predicting Health Outcomes and Its Genetic and Modifiable Factors.

Existing metabolomic clocks exhibit deficiencies in capturing the heterogeneous aging rates among individuals with the same chronological age. Yet, the modifiable and non-modifiable factors in metabolomic aging have not been systematically studied. Here, a new aging measure-MetaboAgeMort-is developed using metabolomic profiles from 239,291 UK Biobank participants for 10-year all-cause mortality prediction. The MetaboAgeMort showed significant associations with all-cause mortality, cause-specific mortality, and diverse incident diseases. Adding MetaboAgeMort to a conventional risk factors model improved the predictive ability of 10-year mortality. A total of 99 modifiable factors across seven categories are identified for MetaboAgeMort. Among these, 16 factors representing pulmonary function, body composition, socioeconomic status, dietary quality, smoking status, alcohol intake, and disease status showed quantitatively stronger associations. The genetic analyses revealed 99 genomic risk loci and 271 genes associated with MetaboAgeMort. The tissue-enrichment analysis showed significant enrichment in liver. While the external validation of the MetaboAgeMort is required, this study illuminates heterogeneous metabolomic aging across the same age, providing avenues for identifying high-risk individuals, developing anti-aging therapies, and personalizing interventions, thus promoting healthy aging and longevity.

Improved polygenic risk prediction in migraine-first patients

BackgroundRecent meta-analyses estimated 14.6% and 11.2% SNP-based heritability of migraine, compared to twin-heritability estimates of 30–60%. This study aimed to investigate heritability estimates in “migraine-first” individuals, patients for whom G43 (migraine with or without aura) was their first medical diagnosis in their lifetime.FindingsUsing data from the UK Biobank (N = 199,929), genome-wide association studies (GWAS) were conducted on 6,139 migraine-first patients and 193,790 healthy controls. SNP-based heritability was estimated using SumHer, yielding 19.37% (± 0.019) for all SNPs and 21.31% (± 0.019) for HapMap3 variants, substantially surpassing previous estimates. Key risk loci included PRDM16, FHL5, ASTN2, STAT6/LRP1, and SLC24A3, and pathway analyses highlighted retinol metabolism and steroid hormone biosynthesis as important pathways in these patients.ConclusionsThe findings underscore that excluding comorbidities at onset time can enhance heritability estimates and genetic signal detection, significantly reducing the extent of “missing heritability” in migraine.

Dynamic responses of human lung innate and adaptive immune cells highlight the roles of genes at asthma risk loci.

The lung is a unique immunological niche with diverse immune cell types. The effects of stimulation through innate and adaptive immune receptors on human lung immune cells has largely been extrapolated from studies of blood immune cells. While multiple immune cell types and many genes have been implicated as contributing to asthma, the dynamics of these in human lung immune cells following activation will yield insights into asthma pathogenesis and lung immunity more broadly. Human lung immune cells from 6 donors were isolated. Mixed leukocytes were treated separately with lipopolysaccharide (LPS), F(ab)2-anti-human-IgM/IgG + IL4 and anti-CD3/CD28 for 4 and 18 hours and underwent single cell RNA sequencing (scRNAseq). Lung immune cell types were annotated, and gene expression compared across conditions. Genes at prior asthma-associated genetic loci were characterized across cell types, treatments and timepoints. Expression of non-classical class II genes associated with asthma, HLA-DQA2 and HLA-DQB2, and their protein products was characterized with immunohistochemistry. We characterized gene expression in 116,697 lung immune cells. Cell-, treatment-, and timepoint-specific effects on gene expression were detected in all lung immune cell populations. Correlation of gene expression between lung and blood lymphocyte populations decreased following stimulation. Among the genes that were differentially expressed, 97 receptor:ligand pairs had changes with treatments. 96.0% of genes at asthma risk loci demonstrated differential expression in at least one cell type and at least one treatment. B cells were the cell type with the highest expression of HLA-DQA2 and HLA-DQB2 which increased with anti-IgM/IgG treatment and the HLA-DQB2 protein was identified in lung B cells from a donor with asthma. Human lung immune activation elicits a broad range of cellular responses that deviate from those of blood immune cells and are relevant to asthma. Lung B cells expressing HLA-DQA2 and HLA-DQB2 appear to be involved in a novel antigen presentation pathway that contributes to asthma risk.

Pinpointing Novel Plasma and Brain Proteins for Common Ocular Diseases: A Comprehensive Cross-Omics Integration Analysis.

The pathogenesis of ocular diseases (ODs) remains unclear, although genome-wide association studies (GWAS) have identified numerous associated genetic risk loci. We integrated protein quantitative trait loci (pQTL) datasets and five large-scale GWAS summary statistics of ODs under a cutting-edge systematic analytic framework. Proteome-wide association studies (PWAS) identified plasma and brain proteins associated with ODs, and 11 plasma proteins were identified by Mendelian randomization (MR) and colocalization (COLOC) analyses as being potentially causally associated with ODs. Five of these proteins (protein-coding genes ECI1, LCT, and NPTXR for glaucoma, WARS1 for age-related macular degeneration (AMD), and SIGLEC14 for diabetic retinopathy (DR)) are newly reported. Twenty brain-protein-OD pairs were identified by COLOC analysis. Eight pairs (protein-coding genes TOM1L2, MXRA7, RHPN2, and HINT1 for senile cataract, WARS1 and TDRD7 for AMD, STAT6 for myopia, and TPPP3 for DR) are newly reported in this study. Phenotype-disease mapping analysis revealed 10 genes related to the eye/vision phenotype or ODs. Combined with a drug exploration analysis, we found that the drugs related to C3 and TXN have been used for the treatment of ODs, and another eight genes (GSTM3 for senile cataract, IGFBP7 and CFHR1 for AMD, PTPMT1 for glaucoma, EFEMP1 and ACP1 for myopia, SIRPG and CTSH for DR) are promising targets for pharmacological interventions. Our study highlights the role played by proteins in ODs, in which brain proteins were taken into account due to the deepening of eye-brain connection studies. The potential pathogenic proteins finally identified provide a more reliable reference range for subsequent medical studies.

Genome-wide association study of hypersensitivity skin reactions induced by nonionic iodinated contrast media.

In Taiwan, nonionic iodinated contrast media (ICMs) are commonly used but can occasionally cause severe side effects. The infrequency of these adverse events, coupled with the complexities in establishing direct causality, poses significant challenges for genetic research. : To investigate the genetic factors associated with skin reactions mediated by nonionic ICMs on a genome-wide scale. A hospital-based cohort from the China Medical University Hospital biobank was utilized to conduct a comprehensive genome-wide association study (GWAS) using PLINK v1.9. The study incorporated two distinct cohorts: one based on adverse drug reaction (ADR) reports, capturing immediate reactions, and the other based on self-reports, which primarily reflected delayed reactions. Known loci were determined by the GWAS catalog. Fine mapping was conducted by FINEMAP to predict causal variants. Pathway enrichment analysis was performed by clusterProfiler to reveal the biological function of the identified genetic signatures. The ADR-based cohort included 120 cases and 3640 controls. GWAS identified 6 candidate risk loci, namely rs150515068, rs6847491, rs192044153, rs191908641, rs376660317, and rs368821335. The self-report-based cohort, consisting of 275 cases and 8338 controls, revealed 36 additional candidate risk loci. Fine mapping further identified 4 causal variants within each cohort. Pathway analysis showed that immediate HSR-related genes are linked to growth hormone response and signaling, while non-immediate HSR genes are involved in neurotransmission. This study offers new perspectives on the genetic foundation of nonionic ICM-induced skin reactions within the Taiwanese population, suggesting that the genes contributing to immediate and non-immediate HSRs might have different functional roles.

Genetic Susceptibility to Acute Viral Bronchiolitis

Abstract Background Acute viral bronchiolitis is a major cause of infant hospitalizations worldwide. Childhood bronchiolitis is considered a risk factor for asthma, suggesting shared genetic factors and biological pathways. Genetic risk loci may provide new insights into disease pathogenesis. Methods We conducted a genome-wide association study to examine the genetic contributions to bronchiolitis susceptibility in the FinnGen project data. We analyzed 1465 infants hospitalized for bronchiolitis who were <2 years of age and 356 404 individuals without a history of acute lower respiratory infections. Results The genome-wide association study identified associations (P < 5 × 10−8) for variants in gasdermin B (GSDMB) and a missense variant in cadherin-related family member 3 (CDHR3). Children with bronchiolitis in infancy were more likely to develop asthma later in life as compared with controls. The 2 associated loci were previously linked to asthma and susceptibility to wheezing illness by causative agents other than respiratory syncytial virus (RSV). The identified loci were associated with overall bronchiolitis, with larger effects in non-RSV than RSV-induced infection. Conclusions Our results suggest that genetic variants in CDHR3 and GSDMB modulate susceptibility to bronchiolitis, especially when caused by viruses other than RSV. Severe bronchiolitis in infancy may trigger the development of asthma in genetically susceptible individuals, or it could be a marker of genetic predisposition to asthma.

Exome sequencing of 20,979 individuals with epilepsy reveals shared and distinct ultra-rare genetic risk across disorder subtypes.

Identifying genetic risk factors for highly heterogeneous disorders like epilepsy remains challenging. Here, we present the largest whole-exome sequencing study of epilepsy to date, with >54,000 human exomes, comprising 20,979 deeply phenotyped patients from multiple genetic ancestry groups with diverse epilepsy subtypes and 33,444 controls, to investigate rare variants that confer disease risk. These analyses implicate seven individual genes, three gene sets, and four copy number variants at exome-wide significance. Genes encoding ion channels show strong association with multiple epilepsy subtypes, including epileptic encephalopathies, generalized and focal epilepsies, while most other gene discoveries are subtype-specific, highlighting distinct genetic contributions to different epilepsies. Combining results from rare single nucleotide/short indel-, copy number-, and common variants, we offer an expanded view of the genetic architecture of epilepsy, with growing evidence of convergence among different genetic risk loci on the same genes. Top candidate genes are enriched for roles in synaptic transmission and neuronal excitability, particularly postnatally and in the neocortex. We also identify shared rare variant risk between epilepsy and other neurodevelopmental disorders. Our data can be accessed via an interactive browser, hopefully facilitating diagnostic efforts and accelerating the development of follow-up studies.

Identification of risk loci for postpartum depression in a genome-wide association study.

Genome-wide association studies (GWAS) of postpartum depression (PPD) based on accumulated cohorts with multiple ethnic backgrounds have failed to identify significantly associated loci. Herein, we conducted a GWAS of Japanese perinatal women along with detailed confounding information to uncover PPD-associated loci. The first and second cohorts (n = 9260 and n = 8582 perinatal women enrolled in the Tohoku Medical Megabank Project) and the third cohort (n = 997), recruited at Nagoya University, underwent genotyping. Of them, 1421, 1264, and 225 were classified as PPD based on the Edinburgh Postnatal Depression Scale 1 month after delivery. The most influential confounding factors of genetic liability to PPD were selected, and logistic regression analyses were performed to evaluate genetic associations with PPD after adjusting for confounders. A meta-analysis of GWAS results from the three cohorts identified significant associations between PPD and the following loci (P < 5 × 10-8) by integrating the number of deliveries and the number of family members living together as the most influential confounders: rs377546683 at DAB1, rs11940752 near UGT8, rs141172317, rs117928019, rs76631412, rs118131805 at DOCK2, rs188907279 near ZNF572, rs504378, rs690150, rs491868, rs689917, rs474978, rs690118, rs690253 near DIRAS2, rs1435984417 at ZNF618, rs57705782 near PTPRM, and rs185293917 near PDGFB. Pathway analyses indicated that SNPs suggestively associated with PPD were mostly over-represented in categories including long-term depression, GnRH signaling, glutamatergic synapse, oxytocin signaling, and Rap1 signaling. The current GWAS study identified eight loci significantly associated with PPD, which may clarify the genetic structure underlying its pathogenesis.

Genetically predicted dietary intake and risks of colorectal cancer: a Mendelian randomisation study

BackgroundEffects of confounders on associations between diet and colorectal cancer (CRC) in observational studies can be minimized in Mendelian randomization (MR) approach. This study aimed to investigate observational and genetically predicted associations between dietary intake and CRC using one-sample MR.MethodsUsing genetic data of over 93 million variants, we performed a genome-wide association study to find genomic risk loci associated with dietary intake in participants from the UK Biobank. Then we calculated genetic risk scores of diet-related variants and used them as instrumental variables in the two-stage least square MR framework to estimate the hazard ratios (HRs) and 95% confidence intervals (CIs) for associations. We also performed observational analyses using age as a time-scale in Cox proportional hazard models.ResultsAllele scores were calculated from 399 genetic variants associated with the consumption of of red meat, processed meat, poultry, fish, milk, cheese, fruits, vegetables, coffee, tea, and alcohol in participants from the UK Biobank. In MR analysis, genetically predicted fruit intake was significantly associated with a 21% decreased risk of CRC (HR = 0.79, 95% CI = 0.66–0.95), and there was a marginally inverse association between vegetable intake and CRC (HR = 0.85, 95% CI = 0.71–1.02). However, null findings were observed in multivariable analysis, with HRs (95% CIs) of 0.99 (0.98–1.01) and 0.99 (0.98–1.00) per increment of daily servings of fruits and vegetables, respectively.ConclusionDietary habits were attributable to genetic variations, which can be used as instrumental variables in the MR framework. Our study supported a causal relationship between fruit intake and a decreased risk of CRC and suggested an effective strategy of consuming fruits in the primary prevention of CRC.

Fine-mapping genomic loci refines bipolar disorder risk genes.

Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 17 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of genes involved in neurotransmission and neurodevelopment including SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, CRTC3, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, DPH1, GSDMB, MED24 and THRA in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance of BD polygenic risk scores across diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).

Investigating the shared genetic basis of inflammatory bowel disease and systemic lupus erythematosus using genetic overlap analysis

BackgroundInflammatory bowel disease (IBD) and systemic lupus erythematosus (SLE) are autoimmune diseases that often coexist clinically. This phenomenon might be due to shared genetic components.MethodsGenome-wide association study (GWAS) data for IBD and SLE were analyzed to determine both global and local genetic correlations using three methodologies: linkage disequilibrium score regression (LDSC), genetic covariance analyzer (GNOVA), and SUPERGNOVA. The genetic overlap and risk loci were subsequently examined using the conditional/conjunctional false discovery rate (cond/conjFDR) statistical framework. Furthermore, a multi-trait analysis of MTAG was employed to validate the loci, followed by an LDSC analysis focusing on tissue-specific gene expression.ResultsGWAS findings demonstrated a marked global genetic correlation between IBD (including Crohn’s disease and ulcerative colitis) and SLE. Locally, SLE showed a strong association with IBD and Crohn’s disease on chromosomes 10, 19, and 22. ConjFDR analysis confirmed the genetic overlap and identified relevant genetic risk loci. MTAG further validated several shared susceptibility genes. Additionally, the LDSC-SEG analysis results indicate that IBD (including CD and UC) and SLE are jointly enriched in the tissues of Spleen and Whole Blood.ConclusionThis study confirms a genetic overlap between IBD and SLE, identifying marked comorbid genes and offering new insights for treating these diseases.

GsQTL: Associating genetic risk variants with gene sets by exploiting their shared variability.

To investigate the functional significance of genetic risk loci identified through genome-wide association studies (GWASs), genetic loci are linked to genes based on their capacity to account for variation in gene expression, resulting in expression quantitative trait loci (eQTL). Following this, gene set analyses are commonly used to gain insights into functionality. However, the efficacy of this approach is hampered by small effect sizes and the burden of multiple testing. We propose an alternative approach: instead of examining the cumulative associations of individual genes within a gene set, we consider the collective variation of the entire gene set. We introduce the concept of gene set QTL (gsQTL), and show it to be more adept at identifying links between genetic risk variants and specific gene sets. Notably, gsQTL experiences less susceptibility to inflation or deflation of significant enrichments compared with conventional methods. Furthermore, we demonstrate the broader applicability of shared variability within gene sets. This is evident in scenarios such as the coordinated regulation of genes by a transcription factor or coordinated differential expression.

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.

Genetics and Epigenetic in Mental Health

Genetics and epigenetics play critical roles in mental health, offering insights into the complex interplay between biological predisposition and environmental influences in the development and progression of mental disorders. Genetic studies have identified numerous risk loci associated with conditions such as schizophrenia, bipolar disorder, and depression, highlighting the polygenic nature of these illnesses. However, the presence of genetic risk factors alone does not fully account for the variability in disease onset, severity, or response to treatment. This gap is increasingly understood through the lens of epigenetics, which involves heritable changes in gene expression that do not alter the DNA sequence itself but are influenced by environmental factors, such as stress, diet, and exposure to toxins. Epigenetic mechanisms, including DNA methylation, histone modification, and non-coding RNAs, can modulate gene activity in response to external stimuli, leading to long-lasting effects on brain function and behavior. These processes are particularly important during critical periods of brain development, where epigenetic modifications can shape neural circuits involved in emotion regulation, cognition, and stress response. Emerging research suggests that the interaction between genetic predisposition and epigenetic changes contributes to the heterogeneity observed in mental health disorders, explaining why individuals with similar genetic risks can have different outcomes. Understanding these intricate genetic and epigenetic networks is essential for developing personalized therapeutic strategies, which could revolutionize the prevention, diagnosis, and treatment of mental health conditions. Advances in this field hold the promise of identifying biomarkers for early intervention and creating targeted interventions that consider an individual’s unique genetic and epigenetic profile, ultimately improving mental health outcomes on a global scale.

Joint genotype and ancestry analysis identify novel loci associated with atopic dermatitis in African American population

Atopic dermatitis (AD) is a chronic itchy inflammatory disease of the skin. Genetic studies have identified multiple risk factors linked to the disease; however, most of studies have been derived from European and East Asian populations. The admixed genome of African American (AA) may provide an opportunity to discovery ancestry-specific loci involved in AD susceptibility. Herein, we present joint analysis of ancestry and genotype effects followed with validation using differential gene expression analysis on AD using 710 AD cases and 1015 non-AD controls from the AA population, genotyped using MEGA followed by imputation using the CAAPA reference panel. The joint analysis identified two novel AD-susceptibility loci, rs2195989 in gene ANGPT1 (8q23.1) and rs62538818 in the intergenic region LURAP1L—MPDZ (9p23). Admixture mapping (AM) results showed potential genomic inflation, and we implemented genomic control and identified five ancestry-of-origin loci with European ancestry effects. The multi-omics functional prioritization of variants in AM signals prioritized the loci SLAIN2, RNF39, and FOXA2. GWAS identified variants significantly associated with AD in the AA population, including SGK1 (rs113357522, OR = 2.81), EFR3A (rs16904552, OR = 1.725), and MMP14 (rs911912, OR = 1.791). GWAS variants were common in the AA but rare in the European population, which suggests an African ancestry-specific risk of AD. Four genes (ANGPT1, LURAP1L, EFR3A, and SGK1) were further validated using qPCR from AD and healthy skin. This study highlighted the importance of genetic studies on admixed populations, as well as local ancestry and genotype-ancestry joint effects to identify risk loci for AD.

Sex-specific associations of Notch signaling with chronic HBV infection: a study from Taiwan Biobank

BackgroundHepatitis B, a liver infection caused by the hepatitis B virus (HBV), can develop into a chronic infection that puts patients at high risk of death from cirrhosis and liver cancer. In this study, we aimed to investigate the difference of reactome pre-Notch expression and processing between males and females by using gene to function analysis in FUMA.MethodsWe analyzed Taiwan Biobank (TWB) data pertaining to 48,874 women and 23,178 men individuals which were collected from 2008 to 2019. According to hepatitis B surface antigen (HBsAg) status in hematology, positive and negative were classified into case and control in the genome-wide association study (GWAS) analysis.ResultsWe found 4715 women and 2656 men HBV cases. The genomic risk loci were different between males and females. In male, three risk loci (rs3732421, rs1884575 and Affx-28516147) were detected while eight risk loci (Affx-4564106, rs932745, rs7574865, rs34050244, rs77041685, rs107822, rs2296651 and rs12599402) were found in female. In addition, sex also presented different results. In females, the most significant SNPs are gathered in chromosome 6. However, except for chromosome 6, significant HBV infection SNPs also could be found in chromosome 3 among males. We further investigated gene function in FUMA to identify the difference in reactome pre-Notch expression and processing between males and females. We found that POGLUT1 and HIST1H2BC only appeared in men but not in women.ConclusionAccording to our study, the reactome pre-Notch expression including POGLUT1 and HIST1H2BC was associated with a risk of Hepatitis B in Taiwanese men when compared to women.