Gene-level Association Research Articles

A genome-wide association study of escitalopram treatment outcomes in patients with major depressive disorder

Major depressive disorder (MDD) is a common psychological condition, the consequences of which, such as suicide, can be severe. Escitalopram, a selective serotonin reuptake inhibitor, is a commonly used antidepressant in clinics. However, more than one-third of patients with MDD do not respond to this drug. Gene polymorphism may affect the efficacy of escitalopram, but the genetic architecture of the antidepressant response in patients with MDD remains unclear. We perform a genome-wide association study (GWAS) of the genetic effect on the outcome of escitalopram in patients with MDD. A total of 203 patients with MDD and 176 healthy control (HC) adults were recruited from Beijing Anding Hospital. Patients received 12 weeks of antidepressant treatment with escitalopram. The Quick Inventory of Depressive Symptomatology-Self-Report (QIDS-SR) or Hamilton depression scale (HAMD) were used to evaluate the severity of depression symptoms at the baseline and the end of 2 and 12 weeks of treatment. A total of 140 variants in MDD patients were identified by GWAS to have genome-wide significance (p < 5e − 8) compared with HCs. Similarly, 189 and 18 variants were identified to be associated with QIDS-SR and HAMD score changes in patients after antidepressant treatment (p < 1e − 5), including rs12602361, rs72799048, rs16842235, and rs2518256. In the two weeks QIDS-SR score study, the gene-level association for these variants and gene set enrichment analyses implicate the enrichment of genes involved in the synaptic plasticity process and nervous system development. Our results implicate the predictive capacity of the effect of escitalopram treatment, supporting a link between genetic basis and remission of depression.

The landscape of rare genetic variants in familial Waldenström macroglobulinemia

AbstractWaldenström macroglobulinemia (WM) is a rare hematological malignancy. Risk for WM is elevated 20-fold among first-degree relatives of patients with WM. However, the list of variants and genes that cause WM remains incomplete. In this study we analyzed exomes from 64 WM pedigrees for evidence of genetic susceptibility for this malignancy. We determined the frequency of pathogenic (P) or likely pathogenic (LP) variants among patients with WM; performed variant- and gene-level association analyses with the set of 166 WM cases and 681 unaffected controls; and examined the segregation pattern of deleterious variants among affected members in each pedigree. We identified P/LP variants in TREX1 and SAMHD1 (genes that function at the interface between innate immune response, genotoxic surveillance, and DNA repair) segregating in patients with WM from 2 pedigrees. There were additional P/LP variants in cancer-predisposing genes (eg, POT1, RECQL4, PTPN11, PMS2). In variant- and gene-level analyses, no associations were statistically significant after multiple testing correction. On a pathway level, we observed involvement of genes that play a role in telomere maintenance (q-value = 0.02), regulation of innate immune response (q-value = 0.05), and DNA repair (q-value = 0.08). Affected members of each pedigree shared multiple deleterious variants (median, n = 18), but the overlap between the families was modest. In summary, P/LP variants in highly penetrant genes constitute a modest proportion of the deleterious variants; each pedigree is largely unique in its genetic architecture, and multiple genes are likely involved in the etiology of WM.

Genetic architecture and biology of youth-onset type 2 diabetes

The prevalence of youth-onset type 2 diabetes (T2D) and childhood obesity has been rising steadily1, producing a growing public health concern1 that disproportionately affects minority groups2. The genetic basis of youth-onset T2D and its relationship to other forms of diabetes are unclear3. Here we report a detailed genetic characterization of youth-onset T2D by analysing exome sequences and common variant associations for 3,005 individuals with youth-onset T2D and 9,777 adult control participants matched for ancestry, including both males and females. We identify monogenic diabetes variants in 2.4% of individuals and three exome-wide significant (P < 2.6 × 10−6) gene-level associations (HNF1A, MC4R, ATXN2L). Furthermore, we report rare variant association enrichments within 25 gene sets related to obesity, monogenic diabetes and β-cell function. Many youth-onset T2D associations are shared with adult-onset T2D, but genetic risk factors of all frequencies—and rare variants in particular—are enriched within youth-onset T2D cases (5.0-fold increase in the rare variant and 3.4-fold increase in common variant genetic liability relative to adult-onset cases). The clinical presentation of participants with youth-onset T2D is influenced in part by the frequency of genetic risk factors within each individual. These findings portray youth-onset T2D as a heterogeneous disease situated on a spectrum between monogenic diabetes and adult-onset T2D.

Novel genome-wide associations for effort valuation and psychopathology in children and adults.

The Research Domain Criteria (RDoC) initiative was established by the US National Institute of Mental Health as a multilevel, disorder-agnostic framework for analysis of human psychopathology through designated domains and constructs, including the "Positive Valence Systems" domain focused on reward-related behavior. This study investigates the reward valuation subconstruct of "effort" and its association with genetic markers, functional neurobiological pathways, and polygenic risk scores for psychopathology in 1215 children aged 6-12 and their parents (n = 1044). All participants completed the effort expenditure for rewards task (EEfRT), which assesses "effort" according to two quantitative measures: hard-task choice and reward sensitivity. Genetic association analyses were undertaken in MAGMA, utilizing EEfRT outcome variables as genome-wide association studies phenotypes to compute SNP and gene-level associations. Genome-wide association analyses found two distinct genetic loci that were significantly associated with measures of reward sensitivity and a separate genetic locus associated with hard task choice. Gene-set enrichment analysis yielded significant associations between "effort" and multiple gene sets involved in reward processing-related pathways, including dopamine receptor signaling, limbic system and forebrain development, and biological response to cocaine. These results serve to establish "effort" as a relevant construct for understanding reward-related behavior at the genetic level and support the RDoC framework for assessing disorder-agnostic psychopathology.

Ancestry-Specific Genetic Determinants of Clonal Haematopoiesis: A Comparative Analysis of 136,401 Admixed Americans and 419,228 Europeans

Introduction: Somatic mutations in blood stem cells can drive clonal expansion and result in clonal haematopoiesis (CH). CH is a precursor to myeloid malignancies, and is increasingly also recognised as a risk factor for non-malignant diseases. CH has been investigated in Europeans, but remains understudied in non-European populations. Here, we investigate the causes and consequences of CH in two large prospective cohort studies, specifically the Mexico City Prospective Study (MCPS) and UK Biobank (UKB). MCPS represents the largest CH study in a non-European population to date. Methods: Admixed Americans were identified from MCPS (n=136,401) while Europeans were identified from the UKB (n=419,228) participants. Somatic variant calling was performed using Mutect2 on whole exome sequencing (WES) data across a selected panel of genes to identify putative CH driver mutations. WES was performed at an average depth of 55x, and CH was defined using a variant allele frequency of ≥3%. Genome-wide association studies (GWAS) for CH were performed using imputed array data, and exome-wide association studies (ExWAS) and gene-level association analyses using WES data. Global/Continental-level ancestry was assigned based on peddy score ≥95% while local ancestry was inferred using RFMix (Ziyatdinov et al., 2022). Results: The most recurrently mutated genes in MCPS and UKB were DNMT3A, TET2, ASXL1, PPM1D, TP53, SF3B1 and SRSF2. The prevalence of CH increased progressively with age to approximately 8/22 (36%) detected as carriers at age 100 and above. CH was 40% more prevalent in age-matched Europeans (4.96%) compared to Admixed Americans (3.10%). Inter-population comparison revealed overall CH, DNMT3A-, TET2-, ASXL1-, PPM1D-, TP53-, JAK2-, and SRSF2-mutant CH to be more prevalent in UKB relative to MCPS (Figure A). Intra-population analysis of the Admixed American cohort further revealed that individuals with a higher fraction of European ancestry were at higher risk of overall CH, DNMT3A-, ASXL1-, and SRSF2-mutant CH, but not TET2-, PPM1D-, TP53-, and JAK2-mutant CH. These suggest differences in relative contribution of genetic, lifestyle or environment factors to specific CH genes. CH GWAS performed in Admixed Americans recapitulated previously reported variants in Europeans, and also identified novel, ancestry-specific variants associated with CH risk, including SNPs upstream of TCL1B (rs968294563: OR=1.79, P=2.01x10 -9; rs187319135: OR=1.85, P=2.69x10 -9). Notably, TCL1B variants were associated with an increased risk of TET2- and ASXL1-mutant CH (rs968294563: OR=3.17, P=3.82x10 -16 for TET2; OR=2.36, P=2.40x10 -3 for ASXL1), but a decreased risk of DNMT3A-mutantCH (rs968294563: OR=0.51, P=6.32x10 -4) (Figure B). The minor allele frequency (MAF) of the most common TCL1B variant in Admixed Americans was 1.23% but was virtually absent in Europeans. CH ExWAS can identify rare causal variants not captured by genotyping or imputation, and these variants may be in linkage disequilibrium with common variants detectable via GWAS. Indeed, ExWAS in Admixed Americans identified one rare SNP on the TCL1B promoter (rs774615666: OR=2.24, P=1.94x10 -8) that was associated with an increased risk of TET2-mutantCH (OR=4.19, P=2.77x10 -10) and a decreased risk of DNMT3A-mutantCH (OR=0.13, P=1.65x10 -4), mirroring our GWAS findings. The rs774615666 risk allele was &amp;gt;200-fold more common in Admixed Americans (MAF: 0.33%) compared to Europeans (MAF: 0.0011%) and was not in linkage disequilibrium with the previously reported TCL1A promoter CH risk SNP in Europeans (Weinstock et al., 2023). Meta-analyses were performed using 555,629 individuals, from both MCPS Admixed American CH GWAS and UKB European CH GWAS. Of the 11 loci reported for overall CH, one was novel, namely GACAT3/ CYRIA. Lastly, we investigated the phenotypic associations of CH in Admixed Americans. Gene-specific CH was associated with increased risk of death from haematological malignancies ( TET2, TP53, SF3B1, and SRSF2), other cancer types ( ASXL1, DNMT3A, and SRSF2) and cardiovascular diseases( DNMT3A, TP53). Conclusions: The substantial difference in CH prevalence between populations and the ancestry-specific genetic associations, demonstrate how the analysis of non-European cohorts can generate novel insights and highlights the importance of such analyses in advancing health equality amongst different human populations.

RAVAR: a curated repository for rare variant-trait associations.

Rare variants contribute significantly to the genetic causes of complex traits, as they can have much larger effects than common variants and account for much of the missing heritability in genome-wide association studies. The emergence of UK Biobank scale datasets and accurate gene-level rare variant-trait association testing methods have dramatically increased the number of rare variant associations that have been detected. However, no systematic collection of these associations has been carried out to date, especially at the gene level. To address the issue, we present the Rare Variant Association Repository (RAVAR), a comprehensive collection of rare variant associations. RAVAR includes 95047 high-quality rare variant associations (76186 gene-level and 18861 variant-level associations) for 4429 reported traits which are manually curated from 245 publications. RAVAR is the first resource to collect and curate published rare variant associations in an interactive web interface with integrated visualization, search, and download features. Detailed gene and SNP information are provided for each association, and users can conveniently search for related studies by exploring the EFO tree structure and interactive Manhattan plots. RAVAR could vastly improve the accessibility of rare variant studies. RAVAR is freely available for all users without login requirement at http://www.ravar.bio.

Gene-Level Analysis of Anthracycline-Induced Cardiomyopathy in Cancer Survivors: A Report From COG-ALTE03N1, BMTSS, and CCSS

BackgroundAnthracyclines are highly effective in treating cancer, albeit with increased cardiomyopathy risk. Although risk is attributed to associations with single nucleotide polymorphisms (SNPs), multiple SNPs on a gene and their interactions remain unexamined. ObjectivesThis study examined gene-level associations with cardiomyopathy among cancer survivors using whole-exome sequencing data. MethodsFor discovery, 278 childhood cancer survivors (129 cases; 149 matched control subjects) from the COG (Children’s Oncology Group) study ALTE03N1 were included. Logic regression (machine learning) was used to identify gene-level SNP combinations for 7,212 genes and ordinal logistic regression to estimate gene-level associations with cardiomyopathy. Models were adjusted for primary cancer, age at cancer diagnosis, sex, race/ethnicity, cumulative anthracycline dose, chest radiation, cardiovascular risk factors, and 3 principal components. Statistical significance threshold of 6.93 × 10−6 accounted for multiple testing. Three independent cancer survivor populations (COG study, BMTSS [Blood or Marrow Transplant Survivor Study] and CCSS [Childhood Cancer Survivor Study]) were used to replicate gene-level associations and examine SNP-level associations from discovery genes using ordinal logistic, conditional logistic, and Cox regression models, respectively. ResultsMedian age at cancer diagnosis for discovery cases and control subjects was 6 years and 8 years, respectively. Gene-level association for P2RX7 (OR: 0.10; 95% CI: 0.04-0.27; P = 2.19 × 10−6) was successfully replicated (HR: 0.65; 95% CI: 0.47-0.90; P = 0.009) in the CCSS cohort. Additional signals were identified on TNIK, LRRK2, MEFV, NOBOX, and FBN3. Individual SNPs across all discovery genes, except FBN3, were replicated. ConclusionsIn our study, SNP sets having 1 or no copies of P2RX7 variant alleles were associated with reduced risk of cardiomyopathy, presenting a potential therapeutic target to mitigate cardiac outcomes in cancer survivors.

A Large-Scale Exome-Wide Association Study Identifies Novel Germline Mutations in Lung Cancer.

Rationale: Genome-wide association studies have identified common variants of lung cancer. However, the contribution of rare exome-wide variants, especially protein-coding variants, to cancers remains largely unexplored. Objectives: To evaluate the role of human exomes in genetic predisposition to lung cancer. Methods: We performed exome-wide association studies to detect the association of exomes with lung cancer in 30,312 patients and 652,902 control subjects. A scalable and accurate implementation of a generalized mixed model was used to detect the association signals for loss-of-function, missense, and synonymous variants and gene-level sets. Furthermore, we performed association and Bayesian colocalization analyses to evaluate their relationships with intermediate exposures. Measurements and Main Results: We systematically analyzed 216,739 single-nucleotide variants in the human exome. The loss-of-function variants exhibited the most notable effects on lung cancer risk. We identified four novel variants, including two missense variants (rs202197044TET3 [Pmeta (P values of meta-analysis) = 3.60 × 10-8] and rs202187871POT1 [Pmeta = 2.21 × 10-8]) and two synonymous variants (rs7447927TMEM173 [Pmeta = 1.32 × 10-9] and rs140624366ATRN [Pmeta = 2.97 × 10-9]). rs202197044TET3 was significantly associated with emphysema (odds ratio, 3.55; Pfdr = 0.015), whereas rs7447927POT1 was strongly associated with telomere length (β = 1.08; Pfdr (FDR corrected P value) = 3.76 × 10-53). Functional evidence of expression of quantitative trait loci, splicing quantitative trait loci, and isoform expression was found for the four novel genes. Gene-level association tests identified several novel genes, including POT1 (protection of telomeres 1), RTEL1, BSG, and ZNF232. Conclusions: Our findings provide insights into the genetic architecture of human exomes and their role in lung cancer predisposition.

Using cancer proteomics data to identify gene candidates for therapeutic targeting.

Gene-level associations obtained from mass-spectrometry-based cancer proteomics datasets represent a resource for identifying gene candidates for functional studies. When recently surveying proteomic correlates of tumor grade across multiple cancer types, we identified specific protein kinases having a functional impact on uterine endometrial cancer cells. This previously published study provides just one template for utilizing public molecular datasets to discover potential novel therapeutic targets and approaches for cancer patients. Proteomic profiling data combined with corresponding multi-omics data on human tumors and cell lines can be analyzed in various ways to prioritize genes of interest for interrogating biology. Across hundreds of cancer cell lines, CRISPR loss of function and drug sensitivity scoring can be readily integrated with protein data to predict any gene's functional impact before bench experiments are carried out. Public data portals make cancer proteomics data more accessible to the research community. Drug discovery platforms can screen hundreds of millions of small molecule inhibitors for those that target a gene or pathway of interest. Here, we discuss some of the available public genomic and proteomic resources while considering approaches to how these could be leveraged for molecular biology insights or drug discovery. We also demonstrate the inhibitory effect of BAY1217389, a TTK inhibitor recently tested in a Phase I clinical trial for the treatment of solid tumors, on uterine cancer cell line viability.

Gene-level association analysis of bivariate ordinal traits with functional regressions.

In genetic studies, many phenotypes have multiple naturally ordered discrete values. The phenotypes can be correlated with each other. If multiple correlated ordinal traits are analyzed simultaneously, the power of analysis may increase significantly while the false positives can be controlled well. In this study, we propose bivariate functional ordinal linear regression (BFOLR) models using latent regressions with cumulative logit link or probit link to perform a gene-based analysis for bivariate ordinal traits and sequencing data. In the proposed BFOLR models, genetic variant data are viewed as stochastic functions of physical positions, and the genetic effects are treated as a function of physical positions. The BFOLR models take the correlation of the two ordinal traits into account via latent variables. The BFOLR models are built upon functional data analysis which can be revised to analyze the bivariate ordinal traits and high-dimension genetic data. The methods are flexible and can analyze three types of genetic data: (1) rare variants only, (2) common variants only, and (3) a combination of rare and common variants. Extensive simulation studies show that the likelihood ratio tests of the BFOLR models control type I errors well and have good power performance. The BFOLR models are applied to analyze Age-Related Eye Disease Studydata, in which two genes, CFH and ARMS2, are found to strongly associate with eye drusen size, drusen area, age-related macular degeneration (AMD) categories, and AMD severity scale.

Genome-Wide Association Study Identifies ROBO2 as a Novel Susceptibility Gene for Anthracycline-Related Cardiomyopathy in Childhood Cancer Survivors.

Interindividual variability in the dose-dependent association between anthracyclines and cardiomyopathy suggests a modifying role of genetic susceptibility. Few previous studies have examined gene-anthracycline interactions. We addressed this gap using the Childhood Cancer Survivor Study (discovery) and the Children's Oncology Group (COG) study COG-ALTE03N1 (replication). A genome-wide association study (Illumina HumanOmni5Exome Array) in 1,866 anthracycline-exposed Childhood Cancer Survivor Study participants (126 with heart failure) was used to identify single-nucleotide polymorphisms (SNPs) with either main or gene-environment interaction effect on anthracycline-related cardiomyopathy that surpassed a prespecified genome-wide threshold for statistical significance. We attempted replication in a matched case-control set of anthracycline-exposed childhood cancer survivors with (n = 105) and without (n = 160) cardiomyopathy from COG-ALTE03N1. Two SNPs (rs17736312 [ROBO2]) and rs113230990 (near a CCCTC-binding factor insulator [< 750 base pair]) passed the significance cutoff for gene-anthracycline dose interaction in discovery. SNP rs17736312 was successfully replicated. Compared with the GG/AG genotypes on rs17736312 and anthracyclines ≤ 250 mg/m2, the AA genotype and anthracyclines > 250 mg/m2 conferred a 2.2-fold (95% CI, 1.2 to 4.0) higher risk of heart failure in discovery and an 8.2-fold (95% CI, 2.0 to 34.4) higher risk in replication. ROBO2 encodes transmembrane Robo receptors that bind Slit ligands (SLIT). Slit-Robo signaling pathway promotes cardiac fibrosis by interfering with the transforming growth factor-β1/small mothers against decapentaplegic (Smad) pathway, resulting in disordered remodeling of the extracellular matrix and potentiating heart failure. We found significant gene-level associations with heart failure: main effect (TGF-β1, P = .007); gene*anthracycline interaction (ROBO2*anthracycline, P = .0003); and gene*gene*anthracycline interaction (SLIT2*TGF-β1*anthracycline, P = .009). These findings suggest that high-dose anthracyclines combined with genetic variants involved in the profibrotic Slit-Robo signaling pathway promote cardiac fibrosis via the transforming growth factor-β1/Smad pathway, providing credence to the biologic plausibility of the association between SNP rs17736312 (ROBO2) and anthracycline-related cardiomyopathy.

Association between ten-eleven methylcytosine dioxygenase 2 genetic variation and viral load in people with HIV.

Identifying genetic factors that influence HIV-pathogenesis is critical for understanding disease pathways. Previous studies have suggested a role for the human gene ten-eleven methylcytosine dioxygenase 2 (TET2) in modulating HIV-pathogenesis. We assessed whether genetic variation in TET2 was associated with markers of HIV-pathogenesis using both gene level and single nucleotide polymorphism (SNP) level association in 8512 HIV-positive persons across five clinical trial cohorts. Variation at both the gene and SNP-level of TET2 was found to be associated with levels of HIV viral load (HIV-VL) consistently in the two cohorts that recruited antiretroviral-naïve participants. The SNPs occurred in two clusters of high linkage disequilibrium (LD), one associated with high HIV-VL and the other low HIV-VL, and were predominantly found in Black participants. Genetic variation in TET2 was associated with HIV-VL in two large antiretroviral therapy (ART)-naive clinical trial cohorts. The role of TET2 in HIV-pathogenesis warrants further investigation.

Human genetics uncovers MAP3K15 as an obesity-independent therapeutic target for diabetes.

We performed collapsing analyses on 454,796 UK Biobank (UKB) exomes to detect gene-level associations with diabetes. Recessive carriers of nonsynonymous variants in MAP3K15 were 30% less likely to develop diabetes (P = 5.7 × 10-10) and had lower glycosylated hemoglobin (β = -0.14 SD units, P = 1.1 × 10-24). These associations were independent of body mass index, suggesting protection against insulin resistance even in the setting of obesity. We replicated these findings in 96,811 Admixed Americans in the Mexico City Prospective Study (P < 0.05)Moreover, the protective effect of MAP3K15 variants was stronger in individuals who did not carry the Latino-enriched SLC16A11 risk haplotype (P = 6.0 × 10-4). Separately, we identified a Finnish-enriched MAP3K15 protein-truncating variant associated with decreased odds of both type 1 and type 2 diabetes (P < 0.05) in FinnGen. No adverse phenotypes were associated with protein-truncating MAP3K15 variants in the UKB, supporting this gene as a therapeutic target for diabetes.

Identifying shared genetic factors underlying epilepsy and congenital heart disease in Europeans.

Epilepsy (EP) and congenital heart disease (CHD) are two apparently unrelated diseases that nevertheless display substantial mutual comorbidity. Thus, while congenital heart defects are associated with an elevated risk of developing epilepsy, the incidence of epilepsy in CHD patients correlates with CHD severity. Although genetic determinants have been postulated to underlie the comorbidity of EP and CHD, the precise genetic etiology is unknown. We performed variant and gene association analyses on EP and CHD patients separately, using whole exomes of genetically identified Europeans from the UK Biobank and Mount Sinai BioMe Biobank. We prioritized biologically plausible candidate genes and investigated the enriched pathways and other identified comorbidities by biological proximity calculation, pathway analyses, and gene-level phenome-wide association studies. Our variant- and gene-level results point to the Voltage-Gated Calcium Channels (VGCC) pathway as being a unifying framework for EP and CHD comorbidity. Additionally, pathway-level analyses indicated that the functions of disease-associated genes partially overlap between the two disease entities. Finally, phenome-wide association analyses of prioritized candidate genes revealed that cerebral blood flow and ulcerative colitis constitute the two main traits associated with both EP and CHD.

Novel plasma and brain proteins that are implicated in multiple sclerosis.

Understanding how variations in the plasma and brain proteome contribute to multiple sclerosis susceptibility can provide important insights to guide drug repurposing and therapeutic development for the disease. However, the role of genetically predicted protein abundance in multiple sclerosis remains largely unknown. Integrating plasma proteomics (n = 3301) and brain proteomics (n = 376 discovery; n = 152 replication) into multiple sclerosis genome-wide association studies (n = 14 802 cases and 26 703 controls), we employed summary-based methods to identify candidate proteins involved in multiple sclerosis susceptibility. Next, we evaluated associations of the corresponding genes with multiple sclerosis at tissue-level using large gene expression quantitative trait data from whole-blood (n = 31 684) and brain (n = 1194) tissue. Further, to assess transcriptional profiles for candidate proteins at cell-level, we examined gene expression patterns in immune cell types (Dataset 1: n = 73 cases and 97 controls; Dataset 2: n = 31 cases and 31 controls) for identified plasma proteins, and in brain cell types (Dataset 1: n = 4 cases and 5 controls; Dataset 2: n = 5 cases and 3 controls) for identified brain proteins. In a longitudinal multiple sclerosis cohort (n = 203 cases followed up to 15 years), we also assessed the corresponding gene-level associations with the outcome of disability worsening. We identified 39 novel proteins associated with multiple sclerosis risk. Based on five identified plasma proteins, four available corresponding gene candidates showed consistent associations with multiple sclerosis risk in whole-blood, and we found TAPBPL upregulation in multiple sclerosis B cells, CD8+ T cells and natural killer cells compared with controls. Among the 34 candidate brain proteins, 18 were replicated in a smaller cohort and 14 of 21 available corresponding gene candidates also showed consistent associations with multiple sclerosis risk in brain tissue. In cell-specific analysis, six identified brain candidates showed consistent differential gene expression in neuron and oligodendrocyte cell clusters. Based on the 39 protein-coding genes, we found 23 genes that were associated with disability worsening in multiple sclerosis cases. The findings present a set of candidate protein biomarkers for multiple sclerosis, reinforced by high concordance in downstream transcriptomics findings at tissue-level. This study also highlights the heterogeneity of cell-specific transcriptional profiles for the identified proteins and that numerous candidates were also implicated in disease progression. Together, these findings can serve as an important anchor for future studies of disease mechanisms and therapeutic development.

Gene-Level Associations in Patients With and Without Pathogenic Germline Variants in CDKN2A and Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) is a component of familial melanoma due to germline pathogenic variants (GPVs) in CDKN2A. However, it is unclear what role this gene or other genes play in its etiology. We analyzed 189 cancer predisposition genes using parametric rare-variant association (RVA) tests and nonparametric permutation tests to identify gene-level associations in PDAC for patients with (CDKN2A+) and without (CDKN2A-) GPV. Exome sequencing was performed on 84 patients with PDAC, 47 CDKN2A+ and 37 CDKN2A-. After variant filtering, various RVA tests and permutation tests were run separately by CDKN2A status. Genes with the strongest nominal associations were evaluated in patients with PDAC from The Cancer Genome Atlas and the UK Biobank (UKB). A secondary analysis including only GPV from UKB was also performed. In RVA tests, ERCC4 and RET showed the most compelling evidence as plausible PDAC candidate genes for CDKN2A+ patients. In contrast, the findings in CDKN2A- patients provided evidence for HMBS, EPCAM, and MRE11 as potential new candidate genes and confirmed ATM, BRCA2, and PALB2 as PDAC genes, consistent with findings in The Cancer Genome Atlas and the UKB. As expected, CDKN2A- patients were more likely to harbor GPVs from the 189 genes investigated. When including only GPVs from UKB, significant associations with PDAC were seen for ATM, BRCA2, and CDKN2A. These results suggest that variants in other genes likely play a role in PDAC in all patients and that PDAC in CDKN2A+ patients has a distinct etiology from PDAC in CDKN2A- patients.

Association analysis of risk genes identified by SCHEMA with schizophrenia in the Chinese Han population.

Schizophrenia is a chronic brain disorder. Previously, the Schizophrenia Exome Sequencing Meta-analysis consortium identified 10 highest risk genes related to schizophrenia. This study aimed to analyze the relationship between the 10 highest risk genes identified by the SCHEMA and schizophrenia in a Chinese population. A total of 225 variants in 10 genes were screened in a Chinese population of 6836 using a customized array. All variants were annotated through the Variant Effect Predictor tool, and the functional impacts of missense variants were assessed based on sorting intolerant from tolerant and PolyPhen-2 scores. The SHEsisPlus tool was used to analyze the association between risk genes and schizophrenia at the locus and gene levels. At the locus level, no missense variants significantly related to schizophrenia were found, but we detected three missense variants that appeared only in cases, including TRIO p. Arg1185Gln, RB1CC1 p. Arg1514Cys, and HERC1 p. Val4517Leu. At the gene level, five genes (TRIO, RB1CC1, HERC1, GRIN2A, and CACAN1G) with more than one variant analyzed were kept for the gene-level association analysis. Only the association between RB1CC1 and schizophrenia reached a significant level (OR = 1.634; 95% CI, 1.062-2.516; P = 0.025). In this study, we determined that RB1CC1 might be a risk gene for schizophrenia in the Chinese population. Our results provide new evidence for recognizing the correlation of these risk genes with the Chinese schizophrenia population.

Integrated Quantile RAnk Test (iQRAT) for gene-level associations

Gene-based testing is a commonly employed strategy in many genetic association studies. Gene-trait associations can be complex due to underlying population heterogeneity, gene-environment interactions, and various other reasons. Existing gene-based tests, such as burden and sequence kernel association tests (SKAT), are mean-based tests and may miss or underestimate higher-order associations that could be scientifically interesting. In this paper we propose a new family of gene-level association tests that integrate quantile rank score process to better accommodate complex associations. The resulting test statistics have multiple advantages: (1) they are almost as efficient as the best existing tests when the associations are homogeneous across quantile levels and have improved efficiency for complex and heterogeneous associations; (2) they provide useful insights into risk stratification; (3) the test statistics are distribution free and could hence accommodate a wide range of underlying distributions, and (4) they are computationally efficient. We established the asymptotic properties of the proposed tests under the null and alternative hypotheses and conducted large-scale simulation studies to investigate their finite sample performance. The performance of the proposed approach is compared with that of conventional mean-based tests, that is, the burden and SKAT tests, through simulation studies and applications to a metabochip dataset on lipid traits and to the genotype-tissue expression data in GTEx to identify eGenes, that is, genes whose expression levels are associated with cis-eQTLs.

Excise Taxes as a Policy Lever for Reaching Healthy North Carolina 2030 Targets.

Excise taxes can raise the price of unhealthy products, reducing consumption and associated health risks and costs. Raising state excise taxes on tobacco, alcohol, and sugary drinks and allowing local governments to do the same are win-win strategies for achieving three Healthy North Carolina 2030 health behavior targets while increasing state revenues.

Uncovering variable neoplasms between ATM protein-truncating and common missense variants using 394 694 UK Biobank exomes.

As an essential regulator of DNA damage, ataxia-telangiectasia mutated (ATM) gene has been widely studied in oncology. However, the independent effects of ATM missense variants and protein-truncating variants (PTVs) on neoplasms have not been heavily studied. Whole-exome sequencing data and the clinical health records of 394,694 UK Biobank European participants were used in this analysis. We mined genetic associations from gene-level and variant-level phenome-wide association studies, and conducted a variant-level conditional association study to test whether the effects of ATM missense variants on neoplasms were independent of ATM PTV carrier status. The gene-level PTV collapsing analysis was consistent with established ATM PTV literature showing that the aggregated impact of 286 ATM PTVs significantly (p< 2× 10-9 ) associated with 31 malignant neoplasm phenotypes. Of 773 distinct protein-coding variants in ATM, three individual missense variants significantly (p< 2× 10-9 ) associated with nine phenotypes. Remarkably, although the nine phenotypes were tumor-related, none overlapped the established ATM PTV-linked malignancies. A subsequent conditional analysis identified that the missense signals were acting independently of the known clinically relevant ATM PTVs.