Identification Of Genetic Risk Factors Research Articles

Identification of Genetic Risk Factors Based on Disease Progression Derived From Longitudinal Brain Imaging Phenotypes.

Neurodegenerative disorders usually happen stage-by-stage rather than overnight. Thus, cross-sectional brain imaging genetic methods could be insufficient to identify genetic risk factors. Repeatedly collecting imaging data over time appears to solve the problem. But most existing imaging genetic methods only use longitudinal imaging phenotypes straightforwardly, ignoring the disease progression trajectory which might be a more stable disease signature. In this paper, we propose a novel sparse multi-task mixed-effects longitudinal imaging genetic method (SMMLING). In our model, disease progression fitting and genetic risk factors identification are conducted jointly. Specifically, SMMLING models the disease progression using longitudinal imaging phenotypes, and then associates fitted disease progression with genetic variations. The baseline status and changing rate, i.e., the intercept and slope, of the progression trajectory thus shoulder the responsibility to discover loci of interest, which would have superior and stable performance. To facilitate the interpretation and stability, we employ l2,1 -norm and the fused group lasso (FGL) penalty to identify loci at both the individual level and group level. SMMLING can be solved by an efficient optimization algorithm which is guaranteed to converge to the global optimum. We evaluate SMMLING on synthetic data and real longitudinal neuroimaging genetic data. Both results show that, compared to existing longitudinal methods, SMMLING can not only decrease the modeling error but also identify more accurate and relevant genetic factors. Most risk loci reported by SMMLING are missed by comparison methods, implicating its superiority in genetic risk factors identification. Consequently, SMMLING could be a promising computational method for longitudinal imaging genetics.

Angular limb deformity associated with TSPAN18, NRG3 and NOVA2 in Rambouillet rams

Angular limb deformity (ALD) affects many species of livestock and companion animals. The mechanisms of ALD development are not well understood, but previous research suggests the involvement of genetic risk factors. A case-control genome-wide association study (GWAS) was conducted with 40 ALD-affected and 302 unaffected Rambouillet rams and 40,945 single nucleotide polymorphisms (SNPs). Forelimbs of 6 ALD-affected rams were examined and diagnosed with osteochondrosis. Genome-wide or chromosome-wide significant SNPs were positioned exonic, intronic or within the 3′UTR of genes TSPAN18, NRG3 and NOVA2, respectively. These genes have previously described roles related to angiogenesis and osteoblast, osteoclast and chondrocyte proliferation and differentiation, which suggests the possibility for their involvement in the pathogenesis of osteochondrosis. Functional consequences of SNPs were evaluated through transcription factor binding site analysis, which predicted binding sites for transcription factors of known importance to bone growth, including SOX6, SOX9 and RUNX2. The identification of genetic risk factors for ALD may help to improve animal welfare and production in Rambouillet, a breed known to be at risk for ALD development. This study proposes genes TSPAN18, NRG3 and NOVA2 as targets for further research towards understanding the etiology of ALD in Rambouillet sheep.

Role of Genetic Markers in Dental Caries: A Literature Review

Abstract Introduction This article reviews the literature on the role of genetic markers in the initiation and progression of dental caries and provides a modern understanding of the disease etiology. Dental caries is a complex, chronic, multifactorial disease which is influenced by genetic, environmental, and social factors. Identification of genetic risk factors will help screen and identify susceptible patients to better understand the contribution of genes in caries etiopathogenesis to formulate various diagnostic and novel therapeutic approaches in the management of the disease. Materials and Methods Innovations and ideas were retrieved based on the literature in journals and textbooks indexed in PubMed, Google Scholar, Scopus, and Web of Science database. The theories obtained are then summarized into a continuous series; thus, readers can more easily understand the ideas and innovations offered. Results Through interactions of the involved gene products, genetic markers have been constructed and provide us with insights into the molecular mechanisms underlying caries. There can also be gene–gene interactions or gene–environment interactions that create epigenetic effects that all possibly contribute to caries risk and resistance. A variety of caries markers have been identified, including genes affecting salivary flow rates and composition, tooth formation genes, as well as immune genes. Conclusion Information derived from various diverse studies will provide new tools to target individuals and/or populations for a more efficient and effective implementation of new preventive measures and diagnostic and novel therapeutic approaches in the management of dental caries.

Identification of Genetic Risk Factors for Keratinocyte Cancer in Immunosuppressed Solid Organ Transplant Recipients: A Case-Control Study

Because of long-term immunosuppression, solid organ transplant recipients are at increased risk for keratinocyte cancer. We matched solid organ transplant patients (n = 150), cases with keratinocyte cancers and tumor-free controls, considering the most important risk factors for keratinocyte cancer in solid organ transplant recipients. Using whole exome data of germline DNA from this patient cohort, we identified several genetic loci associated with the occurrence of multiple keratinocyte cancers. We found one genome-wide significant association of a common single nucleotide polymorphism located in EXOC3 (rs72698504). In addition, we found several variants with a p-value of less than 10−5 associated with the number of keratinocyte cancers. These variants were located in the genes CYB561, WASHC1, PITRM1-AS1, MUC8, ABI3BP, and THBS2-AS1. Using whole exome sequencing data, we performed groupwise tests for rare missense variants in our dataset and found robust associations (p < 10−6, Burden Zeggini test) between MC1R, EPHA8, EPO, MYCT1, ADGRG3, and MGME1 and keratinocyte cancer. Thus, overall, we detected genes involved in pigmentation/UV protection, tumor suppression, immunomodulation, intracellular traffic, and response to UV as genetic risk factors for multiple keratinocyte cancers in solid organ transplant recipients. We also grouped selected genes to pathways and found a selection of genes involved in the “cellular response to UV” to be significantly associated with multiple keratinocyte cancers.

Associations of polygenic risk scores with posttraumatic stress symptom trajectories following combat deployment.

Identification of genetic risk factors may inform the prevention and treatment of posttraumatic stress disorder (PTSD). This study evaluates the associations of polygenic risk scores (PRS) with patterns of posttraumatic stress symptoms following combat deployment. US Army soldiers of European ancestry (n = 4900) provided genomic data and ratings of posttraumatic stress symptoms before and after deployment to Afghanistan in 2012. Latent growth mixture modeling was used to model posttraumatic stress symptom trajectories among participants who provided post-deployment data (n = 4353). Multinomial logistic regression models tested independent associations between trajectory membership and PRS for PTSD, major depressive disorder (MDD), schizophrenia, neuroticism, alcohol use disorder, and suicide attempt, controlling for age, sex, ancestry, and exposure to potentially traumatic events, and weighted to account for uncertainty in trajectory classification and missing data. Participants were classified into low-severity (77.2%), increasing-severity (10.5%), decreasing-severity (8.0%), and high-severity (4.3%) posttraumatic stress symptom trajectories. Standardized PTSD-PRS and MDD-PRS were associated with greater odds of membership in the high-severity v. low-severity trajectory [adjusted odds ratios and 95% confidence intervals, 1.23 (1.06-1.43) and 1.18 (1.02-1.37), respectively] and the increasing-severity v. low-severity trajectory [1.12 (1.01-1.25) and 1.16 (1.04-1.28), respectively]. Additionally, MDD-PRS was associated with greater odds of membership in the decreasing-severity v. low-severity trajectory [1.16 (1.03-1.31)]. No other associations were statistically significant. Higher polygenic risk for PTSD or MDD is associated with more severe posttraumatic stress symptom trajectories following combat deployment. PRS may help stratify at-risk individuals, enabling more precise targeting of treatment and prevention programs.

Genome-Wide Analysis of Structural Variants in Parkinson Disease.

Identification of genetic risk factors for Parkinson disease (PD) has to date been primarily limited to the study of single nucleotide variants, which only represent a small fraction of the genetic variation in the human genome. Consequently, causal variants for most PD risk are not known. Here we focused on structural variants (SVs), which represent a major source of genetic variation in the human genome. We aimed to discover SVs associated with PD risk by performing the first large-scale characterization of SVs in PD. We leveraged a recently developed computational pipeline to detect and genotype SVs from 7,772 Illumina short-read whole genome sequencing samples. Using this set of SV variants, we performed a genome-wide association study using 2,585 cases and 2,779 controls and identified SVs associated with PD risk. Furthermore, to validate the presence of these variants, we generated a subset of matched whole-genome long-read sequencing data. We genotyped and tested 3,154 common SVs, representing over 412 million nucleotides of previously uncatalogued genetic variation. Using long-read sequencing data, we validated the presence of three novel deletion SVs that are associated with risk of PD from our initial association analysis, including a 2kb intronic deletion within the gene LRRN4. We identified three SVs associated with genetic risk of PD. This study represents the most comprehensive assessment of the contribution of SVs to the genetic risk of PD to date. ANN NEUROL 2023;93:1012-1022.

Identification of Genetic Risk Factors for Monogenic and Complex Canine Diseases.

Advances in DNA sequencing and other technologies have greatly facilitated the identification of genetic risk factors for inherited diseases in dogs. We review recent technological developments based on selected examples from canine disease genetics. The identification of disease-causing variants in dogs with monogenic diseases may become a widely employed diagnostic approach in clinical veterinary medicine in the not-too-distant future. Diseases with complex modes of inheritance continue to pose challenges to researchers but have also become much more tangible than in the past. In addition to strategies for identifying genetic risk factors, we provide some thoughts on the interpretation of sequence variants that are largely inspired by developments in human clinical genetics.

Bioinformatics and System Biological Approaches for the Identification of Genetic Risk Factors in the Progression of Cardiovascular Disease.

Background Cardiovascular disease (CVD) is the combination of coronary heart disease, myocardial infarction, rheumatic heart disease, and peripheral vascular disease of the heart and blood vessels. It is one of the leading deadly diseases that causes one-third of the deaths yearly in the globe. Additionally, the risk factors associated with it make the situation more complex for cardiovascular patients, which lead them towards mortality, but the genetic association between CVD and its risk factors is not clearly explored in the global literature. We addressed this issue and explored the linkage between CVD and its risk factors. Methods We developed an analytical approach to reveal the risk factors and their linkages with CVD. We used GEO microarray datasets for the CVD and other risk factors in this study. We performed several analyses including gene expression analysis, diseasome analysis, protein-protein interaction (PPI) analysis, and pathway analysis for discovering the relationship between CVD and its risk factors. We also examined the validation of our study using gold benchmark databases OMIM, dbGAP, and DisGeNET. Results We observed that the number of 32, 17, 53, 70, and 89 differentially expressed genes (DEGs) is overlapped between CVD and its risk factors of hypertension (HTN), type 2 diabetes (T2D), hypercholesterolemia (HCL), obesity, and aging, respectively. We identified 10 major hub proteins (FPR2, TNF, CXCL8, CXCL1, IL1B, VEGFA, CYBB, PTGS2, ITGAX, and CCR5), 12 significant functional pathways, and 11 gene ontological pathways that are associated with CVD. We also found the connection of CVD with its risk factors in the gold benchmark databases. Our experimental outcomes indicate a strong association of CVD with its risk factors of HTN, T2D, HCL, obesity, and aging. Conclusions Our computational approach explored the genetic association of CVD with its risk factors by identifying the significant DEGs, hub proteins, and signaling and ontological pathways. The outcomes of this study may be further used in the lab-based analysis for developing the effective treatment strategies of CVD.

Comparative Genetic Analysis of Psoriatic Arthritis and Psoriasis for the Discovery of Genetic Risk Factors and Risk Prediction Modeling.

ObjectivesPsoriatic arthritis (PsA) has a strong genetic component, and the identification of genetic risk factors could help identify the ~30% of psoriasis patients at high risk of developing PsA. Our objectives were to identify genetic risk factors and pathways that differentiate PsA from cutaneous‐only psoriasis (PsC) and to evaluate the performance of PsA risk prediction models.MethodsGenome‐wide meta‐analyses were conducted separately for 5,065 patients with PsA and 21,286 healthy controls and separately for 4,340 patients with PsA and 6,431 patients with PsC. The heritability of PsA was calculated as a single‐nucleotide polymorphism (SNP)–based heritability estimate (h2 SNP) and biologic pathways that differentiate PsA from PsC were identified using Priority Index software. The generalizability of previously published PsA risk prediction pipelines was explored, and a risk prediction model was developed with external validation.ResultsWe identified a novel genome‐wide significant susceptibility locus for the development of PsA on chromosome 22q11 (rs5754467; P = 1.61 × 10−9), and key pathways that differentiate PsA from PsC, including NF‐κB signaling (adjusted P = 1.4 × 10−45) and Wnt signaling (adjusted P = 9.5 × 10−58). The heritability of PsA in this cohort was found to be moderate (h2 SNP = 0.63), which was similar to the heritability of PsC (h2 SNP = 0.61). We observed modest performance of published classification pipelines (maximum area under the curve 0.61), with similar performance of a risk model derived using the current data.ConclusionKey biologic pathways associated with the development of PsA were identified, but the investigation of risk classification revealed modest utility in the available data sets, possibly because many of the PsC patients included in the present study were receiving treatments that are also effective in PsA. Future predictive models of PsA should be tested in PsC patients recruited from primary care.

Identification of Genetic Risk Factors of Severe COVID-19 Using Extensive Phenotypic Data: A Proof-of-Concept Study in a Cohort of Russian Patients.

The COVID-19 pandemic has drawn the attention of many researchers to the interaction between pathogen and host genomes. Over the last two years, numerous studies have been conducted to identify the genetic risk factors that predict COVID-19 severity and outcome. However, such an analysis might be complicated in cohorts of limited size and/or in case of limited breadth of genome coverage. In this work, we tried to circumvent these challenges by searching for candidate genes and genetic variants associated with a variety of quantitative and binary traits in a cohort of 840 COVID-19 patients from Russia. While we found no gene- or pathway-level associations with the disease severity and outcome, we discovered eleven independent candidate loci associated with quantitative traits in COVID-19 patients. Out of these, the most significant associations correspond to rs1651553 in MYH14 p = 1.4 × 10−7), rs11243705 in SETX (p = 8.2 × 10−6), and rs16885 in ATXN1 (p = 1.3 × 10−5). One of the identified variants, rs33985936 in SCN11A, was successfully replicated in an independent study, and three of the variants were found to be associated with blood-related quantitative traits according to the UK Biobank data (rs33985936 in SCN11A, rs16885 in ATXN1, and rs4747194 in CDH23). Moreover, we show that a risk score based on these variants can predict the severity and outcome of hospitalization in our cohort of patients. Given these findings, we believe that our work may serve as proof-of-concept study demonstrating the utility of quantitative traits and extensive phenotyping for identification of genetic risk factors of severe COVID-19.

Transcript levels in plasma contribute substantial predictive value as potential Alzheimer's disease biomarkers in African Americans.

SummaryBackgroundAfrican Americans (AA) remain underrepresented in Alzheimer's disease (AD) research, despite the prevalence of AD being double in AA compared to non-Hispanic whites. To address this disparity, our group has established the Florida Consortium for African American Alzheimer's Disease Studies (FCA3DS), focusing on the identification of genetic risk factors and novel plasma biomarkers.MethodUtilizing FCA3DS whole exome sequence (WES) and plasma RNA samples from AD cases (n=151) and cognitively unimpaired (CU) elderly controls (n=269), we have performed differential gene expression (DGE) and expression quantitative trait locus (eQTL) analyses on 50 transcripts measured with a custom nanoString® panel. We designed this panel to measure, in plasma, cell-free mRNA (cf-mRNA) levels of AD-relevant genes.FindingsAssociation with higher plasma CLU in CU vs. AD remained significant after Bonferroni correction. Study-wide significant eQTL associations were observed with 105 WES variants in cis with 22 genes, including variants in genes previously associated with AD risk in AA such as ABCA7 and AKAP9. Results from this plasma eQTL analysis identified AD-risk variants in ABCA7 and AKAP9 that are significantly associated with lower and higher plasma mRNA levels of these genes, respectively. Receiver operating characteristic analysis of age, sex APOE-ε4 dosage, CLU, APP, CD14, ABCA7, AKAP9 and APOE mRNA levels, and ABCA7 and AKAP9 eQTLs, achieved 77% area under the curve to discriminate AD vs. CU, an 8% improvement over a model that only included age, sex and APOE-ε4 dosage.InterpretationIncorporating plasma mRNA levels could contribute to improved predictive value of AD biomarker panels.FundingThis work was supported by the National Institute on Aging [RF AG051504, U01 AG046139, R01 AG061796 to NET; P30 AG062677 to JAL and NGR]; Florida Health Ed and Ethel Moore Alzheimer's Disease grants [5AZ03 and 7AZ17 to NET; 7AZ07 to MMC; 8AZ08 to JAL].

Density Analysis of Enterovirus D68 Shows Viral Particles Can Associate with Exosomes.

ABSTRACTEnterovirus D68 (EV-D68) is an emerging pathogen which causes respiratory disease and is associated with an acute flaccid myelitis that predominately affects children. EV-D68 can infect motor neurons, causing cell death and a loss of motor control leading to flaccid paralysis. However, it remains unknown how viral particles gain entry into the central nervous system (CNS). Here, we show that three distinct densities of EV-D68 particle can be isolated from infected muscle and neural cell lines (RD and SH-SY5Y) using high-speed density centrifugation to separate cell supernatant. The lowest-density peak is composed of viral particles, which have adhered to the exterior surface of a small extracellular vesicle called an exosome. Analysis of prototypic (historic) and contemporary EV-D68 strains suggests that binding to exosomes is a ubiquitous characteristic of EV-D68. We further show that interaction with exosomes increases viral infectivity in a neural cell line. Analysis of the two higher-density peaks, which are not associated with exosomes, revealed that a significant amount of viral titer in the modern (2014) EV-D68 strains is found at 1.20 g/cm3, whereas this density has a very low viral titer in the prototypic Fermon strain.IMPORTANCE Despite the strong causal link between enterovirus D68 (EV-D68) and acute flaccid myelitis (AFM), it remains unclear how EV-D68 gains entry into the central nervous system and what receptors enable it to infect motor neurons. We show that EV-D68 particles can adhere to exosomes, placing EV-D68 among a handful of other picornaviruses which are known to interact with extracellular vesicles. Uptake and infection of permissive cells by virally contaminated exosomes would have major implications in the search for the EV-D68 receptor, as well as providing a possible route for viral entry into motor neurons. This work identifies a novel cellular entry route for EV-D68 and may facilitate the identification of genetic risk factors for development of AFM.

Genetic Distribution of Five Spinocerebellar Ataxia Microsatellite Loci in Mexican Native American Populations and Its Impact on Contemporary Mestizo Populations.

Spinocerebellar ataxias (SCAs) conform a heterogeneous group of neurodegenerative disorders with autosomal dominant inheritance. Five of the most frequent SCAs are caused by a CAG repeat expansion in the exons of specific genes. The SCAs incidence and the distribution of polymorphic CAG alleles vary among populations and ethnicities. Thus, characterization of the genetic architecture of ethnically diverse populations, which have undergone recent admixture and demographic events, could facilitate the identification of genetic risk factors. Owing to the great ethnic diversity of the Mexican population, this study aimed to analyze the allele frequencies of five SCA microsatellite loci (SCA1, SCA2, SCA3, SCA6, and SCA7) in eleven Mexican Native American (MNA) populations. Data from the literature were used to compare the allelic distribution of SCA loci with worldwide populations. The SCA loci allelic frequencies evidenced a certain genetic homogeneity in the MNA populations, except for Mayans, who exhibited distinctive genetic profiles. Neither pathological nor large normal alleles were found in MNA populations, except for the SCA2 pre-mutated allele in the Zapotec population. Collectively, our findings demonstrated the contribution of the MNA ancestry in shaping the genetic structure of contemporary Mexican Mestizo populations. Our results also suggest that Native American ancestry has no impact on the origin of SCAs in the Mexican population. Instead, the acquisition of pathological SCA alleles could be associated with European migration.

Status of precision medicine approaches to traumatic brain injury.

Traumatic brain injury (TBI) is a serious condition in which trauma to the head causes damage to the brain, leading to a disruption in brain function. This is a significant health issue worldwide, with around 69 million people suffering from TBI each year. Immediately following the trauma, damage occurs in the acute phase of injury that leads to the primary outcomes of the TBI. In the hours-to-days that follow, secondary damage can also occur, leading to chronic outcomes. TBIs can range in severity from mild to severe, and can be complicated by the fact that some individuals sustain multiple TBIs, a risk factor for worse long-term outcomes. Although our knowledge about the pathophysiology of TBI has increased in recent years, unfortunately this has not been translated into effective clinical therapies. The U.S. Food and Drug Administration has yet to approve any drugs for the treatment of TBI; current clinical treatment guidelines merely offer supportive care. Outcomes between individuals greatly vary, which makes the treatment for TBI so challenging. A blow of similar force can have only mild, primary outcomes in one individual and yet cause severe, chronic outcomes in another. One of the reasons that have been proposed for this differential response to TBI is the underlying genetic differences across the population. Due to this, many researchers have begun to investigate the possibility of using precision medicine techniques to address TBI treatment. In this review, we will discuss the research detailing the identification of genetic risk factors for worse outcomes after TBI, and the work investigating personalized treatments for these higher-risk individuals. We highlight the need for further research into the identification of higher-risk individuals and the development of personalized therapies for TBI.

Plasma transcript profiling identifies significant differentially expressed genes and expression of quantitative trait loci in African Americans

AbstractBackgroundAfrican Americans (AA) remain underrepresented in Alzheimer’s disease (AD) research, despite the prevalence of AD being ∼2X higher in this population compared to non‐Hispanic whites. To address this disparity, our group has established the Florida Consortium for African American Alzheimer’s Disease Studies (FCA3DS), focusing primarily on the identification of genetic risk factors and novel plasma biomarkers.MethodUtilizing plasma samples from FCA3DS AD cases (n=158) and cognitively unimpaired elderly controls (n=272), we have performed differential gene expression (DEG) and expression quantitative trait locus (eQTL) analyses on 50 transcripts measured with a custom NanoString® panel that we have designed to measure transcript levels in plasma of genes relevant to AD. Transcript counts were determined using the NanoString® nCounter system, following manufacturer’s protocols. Transcript counts from 43 of the 50 customs assays passed pre‐established quality control thresholds and were utilized for the DEG and eQTL analyses. Our published FCA3DS whole exome sequence (WES) data was utilized for the eQTL analyses. Linear mixed models adjusted for relevant biological and technical covariates were implemented with the lme4 package in R software (v3.6.2) for the DEG and eQTL analyses.ResultAn association with higher plasma CLU in controls compared to AD remained significant after Bonferroni correction for the 43 transcripts tested. The eQTL analysis revealed significant association (FDR q‐value<0.05) with 105 WES variants in cis with 22 of 43 genes tested, including variants in genes previously associated with AD risk in AA. ConclusionThe results from this AA plasma eQTL analysis revealed ABCA7 variants that are significantly associated with lower plasma ABCA7 transcript levels. One of the significant plasma ABCA7 eQTLs was previously shown by our group to be associated with increased AD risk in AA, suggesting that this may be a functional eQTL underlying the risk of AD in AA. The association of higher levels of CLU transcript in plasma from controls compared to AD is in line with results published by others which showed that higher baseline concentration of clusterin protein in plasma was associated with slower rates of brain atrophy. These results support plasma transcripts as novel endophenotypes in AD biomarker studies.

Identification of Genetic Risk Factors for Familial Urinary Bladder Cancer: An Exome Sequencing Study.

PURPOSEPrevious studies have shown an approximately two-fold elevation in the relative risk of urinary bladder cancer (UBC) among people with a family history that could not be entirely explained by shared environmental exposures, thus suggesting a genetic component in its predisposition. Multiple genome-wide association studies and recent gene panel sequencing studies identified several genetic loci that are associated with UBC risk; however, the list of UBC-associated variants and genes is incomplete.MATERIALS AND METHODSWe exome sequenced eight patients from three multiplex UBC pedigrees and a group of 77 unrelated familial UBC cases matched to 241 cancer-free controls. In addition, we examined pathogenic germline variation in 444 candidate genes in 392 The Cancer Genome Atlas UBC cases.RESULTSIn the pedigrees, segregating variants were family-specific although the identified genes clustered in common pathways, most notably DNA repair (MLH1 and MSH2) and cellular metabolism (IDH1 and ME1). In the familial UBC group, the proportion of pathogenic and likely pathogenic variants was significantly higher in cases compared with controls (P = .003). Pathogenic and likely pathogenic variant load was also significantly increased in genes involved in cilia biogenesis (P = .001). In addition, a pathogenic variant in CHEK2 (NM_007194.4:c.1100del; p.T367Mfs*15) was over-represented in cases (variant frequency = 2.6%; 95% CI, 0.71 to 6.52) compared with controls (variant frequency = 0.21%; 95% CI, 0.01 to 1.15), but was not statistically significant.CONCLUSIONThese results point to a complex polygenic predisposition to UBC. Despite heterogeneity, the genes cluster in several biologically relevant pathways and processes, for example, DNA repair, cilia biogenesis, and cellular metabolism. Larger studies are required to determine the importance of CHEK2 in UBC etiology.

Transcript Levels in Plasma Contribute Substantial Predictive Value as Potential Alzheimer's Disease Biomarkers in African Americans

Background: African Americans (AA) remain underrepresented in Alzheimer’s disease (AD) research, despite the prevalence of AD being double in AA compared to non-Hispanic whites. To address this disparity, our group has established the Florida Consortium for African American Alzheimer’s Disease Studies (FCA3DS), focusing on the identification of genetic risk factors and novel plasma biomarkers. Method: Utilizing FCA 3 DS whole exome sequence (WES) and plasma RNA samples from AD cases (n=151) and cognitively unimpaired (CU) elderly controls (n=269), we have performed differential gene expression (DGE) and expression quantitative trait locus (eQTL) analyses on 50 transcripts measured with a custom nanoString® panel. We designed this panel to measure, in plasma, cell-free mRNA (cf-mRNA) levels of AD-relevant genes. Findings: Association with higher plasma CLU in CU vs. AD remained significant after Bonferroni correction. Study-wide significant eQTL associations were observed with 105 WES variants in cis with 22 genes, including variants in genes previously associated with AD risk in AA such as ABCA7 and AKAP9. Results from this plasma eQTL analysis identified AD-risk variants in ABCA7 and AKAP9 that are significantly associated with lower and higher plasma mRNA levels of these genes, respectively. ROC analysis of age, sex APOE-e4 dosage, CLU, APP, CD14, ABCA7, AKAP9 and APOE mRNA levels, and ABCA7 and AKAP9 eQTLs, achieved 77% AUC to discriminate AD vs. CU, an 8% improvement over a model that only included age, sex and APOE-e4 dosage. Interpretation: Incorporating plasma mRNA levels could contribute to improved predictive value of AD biomarker panels. Funding: National Institute on Aging, Florida Health Ed and Ethel Moore Alzheimer’s Disease grants. Declaration of Interest: None to declare. Ethical Approval: Informed consent and approval by the Mayo Clinic Institutional Review Board was obtained.

Identification of Novel Variants in Cleft Palate-Associated Genes in Brazilian Patients With Non-syndromic Cleft Palate Only

The identification of genetic risk factors for non-syndromic oral clefts is of great importance for better understanding the biological processes related to this heterogeneous and complex group of diseases. Herein we applied whole-exome sequencing to identify potential variants related to non-syndromic cleft palate only (NSCPO) in the multiethnic Brazilian population. Thirty NSCPO samples and 30 sex- and genetic ancestry-matched healthy controls were pooled (3 pools with 10 samples for each group) and subjected to whole-exome sequencing. After filtering, the functional affects, individually and through interactions, of the selected variants and genes were assessed by bioinformatic analyses. As a group, 399 variants in 216 genes related to palatogenesis/cleft palate, corresponding to 6.43%, were exclusively identified in the NSCPO pools. Among those genes are 99 associated with syndromes displaying cleft palate in their clinical spectrum and 92 previously related to cleft lip palate. The most significantly biological processes and pathways overrepresented in the NSCPO-identified genes were associated with the folic acid metabolism, highlighting the interaction between LDL receptor-related protein 6 (LRP6) and 5-methyltetrahydrofolate-homocysteine methyltransferase (MTR) that interconnect two large networks. This study yields novel data on characterization of specific variants and complex processes and pathways related to NSCPO, including many variants in genes of the folate/homocysteine pathway, and confirms that variants in genes related to syndromic cleft palate and cleft lip-palate may cause NSCPO.

Impact of variant-level batch effects on identification of genetic risk factors in large sequencing studies.

Genetic studies have shifted to sequencing-based rare variants discovery after decades of success in identifying common disease variants by Genome-Wide Association Studies using Single Nucleotide Polymorphism chips. Sequencing-based studies require large sample sizes for statistical power and therefore often inadvertently introduce batch effects because samples are typically collected, processed, and sequenced at multiple centers. Conventionally, batch effects are first detected and visualized using Principal Components Analysis and then controlled by including batch covariates in the disease association models. For sequencing-based genetic studies, because all variants included in the association analyses have passed sequencing-related quality control measures, this conventional approach treats every variant as equal and ignores the substantial differences still remaining in variant qualities and characteristics such as genotype quality scores, alternative allele fractions (fraction of reads supporting alternative allele at a variant position) and sequencing depths. In the Alzheimer’s Disease Sequencing Project (ADSP) exome dataset of 9,904 cases and controls, we discovered hidden variant-level differences between sample batches of three sequencing centers and two exome capture kits. Although sequencing centers were included as a covariate in our association models, we observed differences at the variant level in genotype quality and alternative allele fraction between samples processed by different exome capture kits that significantly impacted both the confidence of variant detection and the identification of disease-associated variants. Furthermore, we found that a subset of top disease-risk variants came exclusively from samples processed by one exome capture kit that was more effective at capturing the alternative alleles compared to the other kit. Our findings highlight the importance of additional variant-level quality control for large sequencing-based genetic studies. More importantly, we demonstrate that automatically filtering out variants with batch differences may lead to false negatives if the batch discordances come largely from quality differences and if the batch-specific variants have better quality.

Genotype Analysis of ABCC1, NCF4 and CBR3 Polymorphism and the Association With Childhood Acute Lymphoblastic Leukemia in Mexican Childhood Population.

Background: The identification of genetic risk factors for Acute Lymphoblastic Leukemia (ALL), are increasingly urgent and necessary. Objective: The purpose of this study is to determine the association of the genetic polymorphisms ABCC1 rs3743527, NCF4 rs1883112 and CBR3 rs1056892 with ALL. Methods: DNA samples were obtained in 71 children with ALL (from 2 to 18 years) and in 71 controls without ALL, to determine the polymorphisms by real-time polymerase chain reaction (qPCR), using specific TaqMan probes in a StepOne® thermal cycler (Applied Biosystems, United States). Results: The results of the Odds Ratio analysis show that in the rs1883112 polymorphism of the NCF4 gene, the heterozygous allele has a risk effect for ALL (OR = 3.1870, CI = 1.8880–7.9383 and p = 0.0002), in turn the mutated genotype (AA) is associated with a protective effect (OR = 0.26, 0.1248 to 0.5434 and p = 0.0003). On the other hand, the CBR3 rs1056892 polymorphism shows a significant association of risk to ALL, in the presence of the HT genotype (OR = 2.77, IC = 1.3837 to 5.5651 and p = 0.004) and the mutated genotype of this polymorphism has a significant association with protection to ALL in the HM genotype (OR = 0.52, IC = 0.2639 to 1.0304 and p = 0.05). While the inheritance models of the polymorphisms let us see that of the rs1883112 polymorphism of the NCF4 polymorphism; the HT genotype of the codominant model shows a protective effect against ALL (OR = 0.4117, IC = 0.1718 to 0.9866 and p = 0.04), the recessive model shows us and confirms what we already saw in table number 3, being that there is an association with protective effect in the HM genotype (OR = 0.2604, IC = 0.1248 to 0.5434 and p = 0.0003). In the polymorphism rs1056892 of the CBR3 gene, a protection association was found in the heterozygous allele of the codominant model (OR = 0.3448, IC = 0.1375 to 0.8896 and p = 0.0274). In addition, the recessive inheritance model for the HM genotype shows a protective effect to ALL, (OR = 0.52, CI = 0.9919 to 3.8638 and p = 0.05). Conclusion: There is an evident impact of the NCF4 rs1883112 and CBR3 rs1056892 polymorphisms with an increased risk of susceptibility to ALL; Likewise, through the codominant inheritance model, the effect of the variation of the CBR3 rs1056892 gene as a protective factor against ALL was evaluated.