A HapMap harvest of insights into the genetics of common disease

Enhancer-promoter activation by the Kaposi sarcoma-associated herpesvirus episome maintenance protein LANA

Higher-order genome structure influences the transcriptional regulation of cellular genes through the juxtaposition of regulatory elements, such as enhancers, close to promoters of target genes. While enhancer activation has emerged as an important facet of Kaposi sarcoma-associated herpesvirus (KSHV) biology, the mechanisms controlling enhancer-target gene expression remain obscure. Here, we discover that the KSHV genome tethering protein latency-associated nuclear antigen (LANA) potentiates enhancer-target gene expression in primary effusion lymphoma (PEL), a highly aggressive B cell lymphoma causally associated with KSHV. Genome-wide analyses demonstrate increased levels of enhancer RNA transcription as well as activating chromatin marks at LANA-bound enhancers. 3D genome conformation analyses identified genes critical for latency and tumorigenesis as targets of LANA-occupied enhancers, and LANA depletion results in their downregulation. These findings reveal a mechanism in enhancer-gene coordination and describe a role through which the main KSHV tethering protein regulates essential gene expression in PEL.

Interactive data sharing for multiple questionnaire-based exposome-wide association studies and exposome correlations in the Personalized Environment and Genes Study

The correlations among individual exposures in the exposome, which refers to all exposures an individual encounters throughout life, are important for understanding the landscape of how exposures co-occur, and how this impacts health and disease. Exposome-wide association studies (ExWAS), which are analogous to genome-wide association studies (GWAS), are increasingly being used to elucidate links between the exposome and disease. Despite increased interest in the exposome, tools and publications that characterize exposure correlations and their relationships with human disease are limited, and there is a lack of data and results sharing in resources like the GWAS catalog. To address these gaps, we developed the PEGS Explorer web application to explore exposure correlations in data from the diverse North Carolina-based Personalized Environment and Genes Study (PEGS) that were rigorously calculated to account for differing data types and previously published results from ExWAS. Through globe visualizations, PEGS Explorer allows users to explore correlations between exposures found to be associated with complex diseases. The exposome data used for analysis includes not only standard environmental exposures such as point source pollution and ozone levels but also exposures from diet, medication, lifestyle factors, stress, and occupation. The web application addresses the lack of accessible data and results sharing, a major challenge in the field, and enables users to put results in context, generate hypotheses, and, importantly, replicate findings in other cohorts. PEGS Explorer will be updated with additional results as they become available, ensuring it is an up-to-date resource in exposome science.

Network pharmacology combined with Mendelian randomization analysis to identify the key targets of renin-angiotensin-aldosterone system inhibitors in the treatment of diabetic nephropathy

Background

Diabetic Nephropathy (DN) is one of the microvascular complications of diabetes. The potential targets of renin-angiotensin-aldosterone system (RAAS) inhibitors for the treatment of DN need to be explored.

Methods

The GSE96804 and GSE1009 datasets, 729 RAAS inhibitors-related targets and 6,039 DN-related genes were derived from the public database and overlapped with the differentially expressed genes (DN vs. normal) in GSE96804 to obtain the candidate targets. Next, key targets were screened via the Mendelian randomization analysis and expression analysis. The diagnostic nomogram was constructed and assessed in GSE96804. Additionally, enrichment analysis was conducted and a 'core active ingredient-key target-disease pathway' network was established. Finally, molecular docking was performed.

Results

In total, 60 candidate targets were derived, in which CTSC and PDE5A were screened as the key targets and had a causal association with DN as the protective factors (P < 0.05, OR < 1). Further, a nomogram exhibited pretty prediction efficiency. It is indicated that Benadryl hydrochloride might play a role in the DN by affecting the pathways of 'cytokine cytokine receptor interaction', etc. targeting the CTSC. Moreover, PDE5A might be involved in 'ECM receptor interaction', etc. for the effect of NSAID, captopril, chlordiazepoxide on DN. Molecular docking analysis showed a good binding ability of benadryl hydrochloride and CTSC, NSAID and PDE5A. PTGS2, ITGA4, and ANPEP are causally associated with acute kidney injury.

Conclusion

CTSC and PDE5A were identified as key targets for RAAS inhibitors in the treatment of DN, which might provide some clinical significance in helping to diagnose and treat DN. Among the targets of RAAS inhibitors, PTGS2, ITGA4 and ANPEP have a causal relationship with acute kidney injury, which is worthy of further clinical research.

Schizophrenia in the genetic era: a review from development history, clinical features and genomic research approaches to insights of susceptibility genes

Schizophrenia is a devastating neuropsychiatric disorder affecting 1% of the world population and ranks as one of the disorders providing the most severe burden for society. Schizophrenia etiology remains obscure involving multi-risk factors, such as genetic, environmental, nutritional, and developmental factors. Complex interactions of genetic and environmental factors have been implicated in the etiology of schizophrenia. This review provides an overview of the historical origins, pathophysiological mechanisms, diagnosis, clinical symptoms and corresponding treatment of schizophrenia. In addition, as schizophrenia is a polygenic, genetic disorder caused by the combined action of multiple micro-effective genes, we further detail several approaches, such as candidate gene association study (CGAS) and genome-wide association study (GWAS), which are commonly used in schizophrenia genomics studies. A number of GWASs about schizophrenia have been performed with the hope to identify novel, consistent and influential risk genetic factors. Finally, some schizophrenia susceptibility genes have been identified and reported in recent years and their biological functions are also listed. This review may serve as a summary of past research on schizophrenia genomics and susceptibility genes (NRG1, DISC1, RELN, BDNF, MSI2), which may point the way to future schizophrenia genetics research. In addition, depending on the above discovery of susceptibility genes and their exact function, the development and application of antipsychotic drugs will be promoted in the future.

Safety tests and clinical research on buccal and nasal microneedle swabs for genomic analysis

Conventional swabs have been used as a non-invasive method to obtain samples for DNA analysis from the buccal and the nasal mucosa. However, swabs may not always collect pure enough genetic material. In this study, buccal and nasal microneedle swab is developed to improve the accuracy and reliability of genomic analysis. A cytotoxicity test, a skin sensitivity test, and a skin irritation test are conducted with microneedle swabs. Polymer microneedle swabs meet the safety requirements for clinical research and commercial use. When buccal and nasal microneedle swabs are used, the amount of genetic material obtained is greater than that from commercially available swabs, and DNA purity is also high. The comparatively short microneedle swab (250 μm long) cause almost no pain to all 25 participants. All participants also report that the microneedle swabs are very easy to use. When genotypes are compared at five SNP loci from blood of a participant and from that person's buccal or nasal microneedle swab, the buccal and nasal microneedle swabs show 100% concordance for all five SNP genotypes. Microneedle swabs can be effectively used for genomic analysis and prevention through genomic analysis, so the utilization of microneedle swabs is expected to be high.

ASCARIS: Positional feature annotation and protein structure-based representation of single amino acid variations

Background

Genomic variations may cause deleterious effects on protein functionality and perturb biological processes. Elucidating the effects of variations is critical for developing novel treatment strategies for diseases of genetic origin. Computational approaches have been aiding the work in this field by modeling and analyzing the mutational landscape. However, new approaches are required, especially for accurate representation and data-centric analysis of sequence variations.

Method

In this study, we propose ASCARIS (Annotation and StruCture-bAsed RepresentatIon of Single amino acid variations), a method for the featurization (i.e., quantitative representation) of single amino acid variations (SAVs), which could be used for a variety of purposes, such as predicting their functional effects or building multi-omics-based integrative models. ASCARIS utilizes the direct and spatial correspondence between the location of the SAV on the sequence/structure and 30 different types of positional feature annotations (e.g., active/lipidation/glycosylation sites; calcium/metal/DNA binding, inter/transmembrane regions, etc.), along with structural features and physicochemical properties. The main novelty of this method lies in constructing reusable numerical representations of SAVs via functional annotations.

Results

We statistically analyzed the relationship between these features and the consequences of variations and found that each carries information in this regard. To investigate potential applications of ASCARIS, we trained variant effect prediction models that utilize our SAV representations as input. We carried out an ablation study and a comparison against the state-of-the-art methods and observed that ASCARIS has a competing and complementary performance against widely-used predictors. ASCARIS can be used alone or in combination with other approaches to represent SAVs from a functional perspective. ASCARIS is available as a programmatic tool at https://github.com/HUBioDataLab/ASCARIS and as a web-service at https://huggingface.co/spaces/HUBioDataLab/ASCARIS.

Whole Genome Analysis of Venous Thromboembolism: the Trans-Omics for Precision Medicine Program

BACKGROUND

Risk for venous thromboembolism has a strong genetic component. Whole genome sequencing from the TOPMed program (Trans-Omics for Precision Medicine) allowed us to look for new associations, particularly rare variants missed by standard genome-wide association studies.

METHODS

The 3793 cases and 7834 controls (11.6% of cases were individuals of African, Hispanic/Latino, or Asian ancestry) were analyzed using a single variant approach and an aggregate gene-based approach using our primary filter (included only loss-of-function and missense variants predicted to be deleterious) and our secondary filter (included all missense variants).

RESULTS

Single variant analyses identified associations at 5 known loci. Aggregate gene-based analyses identified only PROC (odds ratio, 6.2 for carriers of rare variants; P=7.4×10-14) when using our primary filter. Employing our secondary variant filter led to a smaller effect size at PROC (odds ratio, 3.8; P=1.6×10-14), while excluding variants found only in rare isoforms led to a larger one (odds ratio, 7.5). Different filtering strategies improved the signal for 2 other known genes: PROS1 became significant (minimum P=1.8×10-6 with the secondary filter), while SERPINC1 did not (minimum P=4.4×10-5 with minor allele frequency <0.0005). Results were largely the same when restricting the analyses to include only unprovoked cases; however, one novel gene, MS4A1, became significant (P=4.4×10-7 using all missense variants with minor allele frequency <0.0005).

CONCLUSIONS

Here, we have demonstrated the importance of using multiple variant filtering strategies, as we detected additional genes when filtering variants based on their predicted deleteriousness, frequency, and presence on the most expressed isoforms. Our primary analyses did not identify new candidate loci; thus larger follow-up studies are needed to replicate the novel MS4A1 locus and to identify additional rare variation associated with venous thromboembolism.

The Role of Neural and Genetic Processes in Learning to Read and Specific Reading Disabilities: Implications for Instruction

To learn to read, the brain must repurpose neural systems for oral language and visual processing to mediate written language. We begin with a description of computational models for how alphabetic written language is processed. Next, we explain the roles of a dorsal sublexical system in the brain that relates print and speech, a ventral lexical system that develops the visual expertise for rapid orthographic processing at the word level, and the role of cognitive control networks that regulate attentional processes as children read. We then use studies of children, adult illiterates learning to read, and studies of poor readers involved in intervention, to demonstrate the plasticity of these neural networks in development and in relation to instruction. We provide a brief overview of the rapid increase in the field's understanding and technology for assessing genetic influence on reading. Family studies of twins have shown that reading skills are heritable, and molecular genetic studies have identified numerous regions of the genome that may harbor candidate genes for the heritability of reading. In selected families, reading impairment has been associated with major genetic effects, despite individual gene contributions across the broader population that appear to be small. Neural and genetic studies do not prescribe how children should be taught to read, but these studies have underscored the critical role of early intervention and ongoing support. These studies also have highlighted how structured instruction that facilitates access to the sublexical components of words is a critical part of training the brain to read.

GWAS on retinal vasculometry phenotypes

The eye is the window through which light is transmitted and visual sensory signalling originates. It is also a window through which elements of the cardiovascular and nervous systems can be directly inspected, using ophthalmoscopy or retinal imaging. Measurements of ocular parameters may therefore offer important information on the physiology and homeostasis of these two important systems. Here we report the results of a genetic characterisation of retinal vasculature. Four genome-wide association studies performed on different aspects of retinal vasculometry phenotypes, such as arteriolar and venular tortuosity and width, found significant similarities between retinal vascular characteristics and cardiometabolic health. Our analyses identified 119 different regions of association with traits of retinal vasculature, including 89 loci associated arteriolar tortuosity, the strongest of which was rs35131825 (p = 2.00×10-108), 2 loci with arteriolar width (rs12969347, p = 3.30×10-09 and rs5442, p = 1.9E-15), 17 other loci associated with venular tortuosity and 11 novel associations with venular width. Our causal inference analyses also found that factors linked to arteriolar tortuosity cause elevated diastolic blood pressure and not vice versa.

Roles of the m6A methyltransferases METTL3, METTL14, and WTAP in pulmonary tuberculosis

Objective

The aim of the current study was to investigate the contributing role of gene variation and transcription levels among the m6A methyltransferases METTL3, METTL14, and WTAP in pulmonary tuberculosis (PTB).

Methods

A case-control study including 461 PTB patients and 467 normal controls was designed for genotyping. Three SNPs in METTL3 (rs1061027, rs1139130, rs1061026), three SNPs in METTL14 (rs62328061, rs4834698, rs1064034), and two SNPs in WTAP (rs1853259, rs11752345) were genotyped via the SNPscan™ technique. METTL3, METTL14, and WTAP transcription levels were determined in 78 PTB patients and 86 controls via quantitative real-time reverse-transcription PCR.

Results

Frequencies of the METTL14 rs62328061 GG genotype, WTAP rs11752345 CT genotype, and T allele were significantly increased in PTB patients compared to controls. An increased risk of rs62328061 was detected in a recessive model, and a decreased risk of rs11752345 was detected in a dominant model in the PTB group. METTL3 gene variation was not associated with PTB risk. The METTL3 rs1139130 GG genotype was significantly increased with drug resistance, and the G allele was significantly decreased with drug-induced liver injury in PTB patients. A reduced frequency of the METTL14 rs62328061 G allele was associated with leukopenia, a reduced frequency of the WTAP rs11752345 T allele was associated with sputum smear positivity, and a higher frequency of the METTL14 rs4834698 TC genotype was evident in PTB patients with hypoproteinemia. Compared to controls, METTL3, METTL14, and WTAP transcription levels in PTB patients were significantly decreased, and the level of WTAP was increased in PTB patients with drug resistance. METTL3 level was negatively associated with erythrocyte sedimentation rate and aspartate aminotransferase, and METTL14 level was negatively correlated with alanine aminotransferase and aspartate aminotransferase.

Conclusion

METTL14 rs62328061 and WTAP rs11752345 variants were associated with the genetic background of PTB, and METTL3, METTL14, and WTAP levels were abnormally decreased, suggesting that these m6A methyltransferases may play important roles in PTB.

Deletion of Jazf1 gene causes early growth retardation and insulin resistance in mice

Single-nucleotide polymorphisms in the human juxtaposed with another zinc finger protein 1 (JAZF1) gene have repeatedly been associated with both type 2 diabetes (T2D) and height in multiple genome-wide association studies (GWAS); however, the mechanism by which JAZF1 causes these traits is not yet known. To investigate the possible functional role of JAZF1 in growth and glucose metabolism in vivo, we generated Jazf1 knockout (KO) mice and examined body composition and insulin sensitivity both in young and adult mice by using ¹H-nuclear magnetic resonance and hyperinsulinemic-euglycemic clamp techniques. Plasma concentrations of insulin-like growth factor 1 (IGF-1) were reduced in both young and adult Jazf1 KO mice, and young Jazf1 KO mice were shorter in stature than age-matched wild-type mice. Young Jazf1 KO mice manifested reduced fat mass, whereas adult Jazf1 KO mice manifested increased fat mass and reductions in lean body mass associated with increased plasma growth hormone (GH) concentrations. Adult Jazf1 KO manifested muscle insulin resistance that was further exacerbated by high-fat diet feeding. Gene set enrichment analysis in Jazf1 KO liver identified the hepatocyte hepatic nuclear factor 4 alpha (HNF4α), which was decreased in Jazf1 KO liver and in JAZF1 knockdown cells. Moreover, GH-induced IGF-1 expression was inhibited by JAZF1 knockdown in human hepatocytes. Taken together these results demonstrate that reduction of JAZF1 leads to early growth retardation and late onset insulin resistance in vivo which may be mediated through alterations in the GH-IGF-1 axis and HNF4α.

Missing Causality and Heritability of Autoimmune Hepatitis

BACKGROUND

Autoimmune hepatitis has an unknown cause and genetic associations that are not disease-specific or always present. Clarification of its missing causality and heritability could improve prevention and management strategies.

AIMS

Describe the key epigenetic and genetic mechanisms that could account for missing causality and heritability in autoimmune hepatitis; indicate the prospects of these mechanisms as pivotal factors; and encourage investigations of their pathogenic role and therapeutic potential.

METHODS

English abstracts were identified in PubMed using multiple key search phases. Several hundred abstracts and 210 full-length articles were reviewed.

RESULTS

Environmental induction of epigenetic changes is the prime candidate for explaining the missing causality of autoimmune hepatitis. Environmental factors (diet, toxic exposures) can alter chromatin structure and the production of micro-ribonucleic acids that affect gene expression. Epistatic interaction between unsuspected genes is the prime candidate for explaining the missing heritability. The non-additive, interactive effects of multiple genes could enhance their impact on the propensity and phenotype of autoimmune hepatitis. Transgenerational inheritance of acquired epigenetic marks constitutes another mechanism of transmitting parental adaptations that could affect susceptibility. Management strategies could range from lifestyle adjustments and nutritional supplements to precision editing of the epigenetic landscape.

CONCLUSIONS

Autoimmune hepatitis has a missing causality that might be explained by epigenetic changes induced by environmental factors and a missing heritability that might reflect epistatic gene interactions or transgenerational transmission of acquired epigenetic marks. These unassessed or under-evaluated areas warrant investigation.

Clinical relevance of vitamin B12 level and vitamin B12 metabolic gene variation in pulmonary tuberculosis

The aim of this study was to assess the association of vitamin B12 level and single nucleotide polymorphisms (SNPs) in vitamin B12 metabolic genes with pulmonary tuberculosis (PTB) in Chinese Han population. The plasma vitamin B12 expression level was detected using ELISA. Ten SNPs in six key genes (TCN1, TCN2, CUBN, MMACHC, FUT6, and MUT) of vitamin B12 metabolic pathway were included for genotyping by the SNPscan technique among 454 PTB patients and 467 controls. Our results found that vitamin B12 level was significantly reduced in PTB patients when compared with controls. There was no significant association between TCN1 rs526934, TCN2 rs1801198, CUBN rs7906242, rs10904861, rs1801222, MMACHC rs10789465, FUT6 rs3760776, rs3760775, MUT rs9473555, rs9381784 variants, and PTB susceptibility. TCN2 rs1801198 CC genotype, C allele was significantly associated with hypoproteinemia in PTB patients. In CUBN, rs7906242 GG genotype, G allele, rs10904861 TT genotype, and T allele were significantly related to the decreased frequency of sputum smear-positive, and rs10904861 variant affected the occurrence of drug resistance in PTB patients. In addition, the increased frequency of CUBN rs1801222 AA genotype was significantly associated with leukopenia. The decreased frequency of MUT rs9473555 CC genotype was found in the PTB patients with hypoproteinemia. However, vitamin B12 expression was not associated with the genotype distribution of above SNPs. In conclusion, vitamin B12 level was significantly decreased in PTB patients and genetic variants in vitamin B12 metabolic genes were not contributed to PTB susceptibility. Several SNPs in TCN2, CUBN, and MUT gene might associate with multiple clinical manifestations in PTB.

3D chromatin maps of the human pancreas reveal lineage-specific regulatory architecture of T2D risk

Three-dimensional (3D) chromatin organization maps help dissect cell-type-specific gene regulatory programs. Furthermore, 3D chromatin maps contribute to elucidating the pathogenesis of complex genetic diseases by connecting distal regulatory regions and genetic risk variants to their respective target genes. To understand the cell-type-specific regulatory architecture of diabetes risk, we generated transcriptomic and 3D epigenomic profiles of human pancreatic acinar, alpha, and beta cells using single-cell RNA-seq, single-cell ATAC-seq, and high-resolution Hi-C of sorted cells. Comparisons of these profiles revealed differential A/B (open/closed) chromatin compartmentalization, chromatin looping, and transcriptional factor-mediated control of cell-type-specific gene regulatory programs. We identified a total of 4,750 putative causal-variant-to-target-gene pairs at 194 type 2 diabetes GWAS signals using pancreatic 3D chromatin maps. We found that the connections between candidate causal variants and their putative target effector genes are cell-type stratified and emphasize previously underappreciated roles for alpha and acinar cells in diabetes pathogenesis.

Integration of Protein Structure and Population-Scale DNA Sequence Data for Disease Gene Discovery and Variant Interpretation

The experimental and computational techniques for capturing information about protein structures and genetic variation within the human genome have advanced dramatically in the past 20 years, generating extensive new data resources. In this review, we discuss these advances, along with new approaches for determining the impact a genetic variant has on protein function. We focus on the potential of new methods that integrate human genetic variation into protein structures to discover relationships to disease, including the discovery of mutational hotspots in cancer-related proteins, the localization of protein-altering variants within protein regions for common complex diseases, and the assessment of variants of unknown significance for Mendelian traits. We expect that approaches that integrate these data sources will play increasingly important roles in disease gene discovery and variant interpretation. Expected final online publication date for the Annual Review of Biomedical Data Science, Volume 5 is August 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Assessing accuracy of genotype imputation in the Afrikaner and Brahman cattle breeds of South Africa

Imputation may be used to rescue genomic data from animals that would otherwise be eliminated due to a lower than desired call rate. The aim of this study was to compare the accuracy of genotype imputation for Afrikaner, Brahman, and Brangus cattle of South Africa using within- and multiple-breed reference populations. A total of 373, 309, and 101 Afrikaner, Brahman, and Brangus cattle, respectively, were genotyped using the GeneSeek Genomic Profiler 150 K panel that contained 141,746 markers. Markers with MAF ≤ 0.02 and call rates ≤ 0.95 or that deviated from Hardy Weinberg Equilibrium frequency with a probability of ≤ 0.0001 were excluded from the data as were animals with a call rate ≤ 0.90. The remaining data included 99,086 SNPs and 360 Afrikaner, 75,291 SNPs and 288 animals Brahman, and 97,897 SNPs and 99 Brangus animals. A total of 7986, 7002, and 7000 SNP from 50 Afrikaner and Brahman and 30 Brangus cattle, respectively, were masked and then imputed using BEAGLE v3 and FImpute v2. The within-breed imputation yielded accuracies ranging from 89.9 to 96.6% for the three breeds. The multiple-breed imputation yielded corresponding accuracies from 69.21 to 88.35%. The results showed that population homogeneity and numerical representation for within and across breed strategies, respectively, are crucial components for improving imputation accuracies.

Rare diseases: human genome research is coming home

After a long and largely disappointing detour, Genome Research has reidentified Rare Diseases as a major opportunity for improving health care and a clue to understanding gene and genome function. In this Special Issue of CSH Molecular Case Studies on Rare Diseases, several invited Perspectives, numerous Case Reports, and this Editorial itself address recent breakthroughs as well as unsolved problems in this wide field. These range from exciting prospects for gap-free diagnostic whole-genome sequencing to persisting problems related to identifying and distinguishing pathogenic and benign variants; and from the good news that soon, the United Kingdom will no longer be the only country to have introduced whole-genome sequencing into health care to the sobering conclusion that in many countries the clinical infrastructure for bringing Genome Medicine to the patient is still lacking. With less than 5000 genes firmly implicated in disease, the identification of at least twice as many disease genes is a major challenge, and the elucidation of their function is an even larger task. But given the renewed interest in rare diseases, their importance for health care, and the vast and growing spectrum of concepts and methods for studying them, the future of Human Genome Research is bright.

Genetic Variants in METTL14 are Associated with the Risk of Acute Lymphoblastic Leukemia in Southern Chinese Children: A Five-Center Case-Control Study

Background/Aim

Acute lymphoblastic leukemia (ALL) is the most common form of pediatric cancer. METTL14, an N⁶-methyladenosine (m⁶A) modification protein, plays several roles in cancer development and is involved in the pathogenesis of various types of cancers. However, the role of METTL14 gene single nucleotide polymorphisms (SNPs) in pediatric ALL susceptibility remains to be investigated.

Methods

A case-control design and multinomial logistic regression were used to develop models to estimate the overall risk for pediatric ALL and three METTL14 gene SNPs (rs298982 G/A, rs298981 A/G and rs1064034 T/A) in 808 cases and 1340 controls, which were genotyped using a TaqMan assay. The associations were estimated by odds ratios (ORs) with their 95% confidence intervals (CIs). Furthermore, stratified analysis was performed to explore associations of rs298982 and rs1064034 with pediatric ALL susceptibility in terms of age, sex, immunophenotype, minimal residual disease (MRD), and other clinical characteristics.

Results

Among the three analyzed SNPs, rs298982 G/A and rs1064034 T/A exhibited a significant association with decreased childhood ALL risk, while rs298981 A/G exhibited no difference. In stratified analysis, rs298982 GA/AA and rs1064034 TA/AA had a protective effect in children <120 months of age and males, common B ALL, TEL-AML, non gene fusion, normal diploid, and high WBC. However, the rs1064034 TA/AA genotype was associated with an increased risk of mixed immunophenotyping. Compared with the reference haplotype GAT, haplotypes CAA, CGT and CGA were significantly associated with elevated ALL risk, while haplotype GGT was significantly associated decreased ALL risk. Moreover, subjects carrying rs298982 A or rs1064034 A exhibited less minimal MRD after induced chemotherapy. Functional annotations revealed that METTL14 gene SNPs rs298982 G/A and rs1064034 T/A could be potential functional variants.

Conclusion

In conclusion, METTL14 gene polymorphisms influence the risk of ALL in southern Chinese children and might be potential biomarkers for pediatric ALL susceptibility and chemotherapeutics.

Genetic Pathways and Functional Subnetworks for the Complex Nature of Bipolar Disorder in Genome-Wide Association Study

Bipolar disorder is a complex psychiatric trait that is also recognized as a high substantial heritability from a worldwide distribution. The success in identifying susceptibility loci for bipolar disorder (BPD) has been limited due to its complex genetic architecture. Growing evidence from association studies including genome-wide association (GWA) studies points to the need of improved analytic strategies to pinpoint the missing heritability for BPD. More importantly, many studies indicate that BPD has a strong association with dementia. We conducted advanced pathway analytics strategies to investigate synergistic effects of multilocus within biologically functional pathways, and further demonstrated functional effects among proteins in subnetworks to examine mechanisms underlying the complex nature of bipolarity using a GWA dataset for BPD. We allowed bipolar susceptible loci to play a role that takes larger weights in pathway-based analytic approaches. Having significantly informative genes identified from enriched pathways, we further built function-specific subnetworks of protein interactions using MetaCore. The gene-wise scores (i.e., minimum p-value) were corrected for the gene-length, and the results were corrected for multiple tests using Benjamini and Hochberg’s method. We found 87 enriched pathways that are significant for BPD; of which 36 pathways were reported. Most of them are involved with several metabolic processes, neural systems, immune system, molecular transport, cellular communication, and signal transduction. Three significant and function-related subnetworks with multiple hotspots were reported to link with several Gene Ontology processes for BPD. Our comprehensive pathway-network frameworks demonstrated that the use of prior knowledge is promising to facilitate our understanding between complex psychiatric disorders (e.g., BPD) and dementia for the access to the connection and clinical implications, along with the development and progression of dementia.

METTL14 gene polymorphisms decrease Wilms tumor susceptibility in Chinese children

BACKGROUND

Wilms tumor is a highly heritable malignancy. Aberrant METTL14, a critical component of N6-methyladenosine (m⁶A) methyltransferase, is involved in carcinogenesis. The association between genetic variants in the METTL14 gene and Wilms tumor susceptibility remains to be fully elucidated. We aimed to assess whether variants within this gene are implicated in Wilms tumor susceptibility.

METHODS

A total of 403 patients and 1198 controls were analyzed. METTL14 genotypes were assessed by TaqMan genotyping assay.

RESULT

Among the five SNPs analyzed, rs1064034 T > A and rs298982 G > A exhibited a significant association with decreased susceptibility to Wilms tumor. Moreover, the joint analysis revealed that the combination of five protective genotypes exerted significantly more protective effects against Wilms tumor than 0-4 protective genotypes with an OR of 0.69. The stratified analysis further identified the protective effect of rs1064034 T > A, rs298982 G > A, and combined five protective genotypes in specific subgroups. The above significant associations were further validated by haplotype analysis and false-positive report probability analysis. Preliminary mechanism exploration indicated that rs1064034 T > A and rs298982 G > A are correlated with the expression and splicing event of their surrounding genes.

CONCLUSIONS

Collectively, our results suggest that METTL14 gene SNPs may be genetic modifiers for the development of Wilms tumor.

Problems and promises: How to tell the story of a Genome Wide Association Study?

The promise of treatments for common complex diseases (CCDs) is understood as an important force driving large scale genetics research over the last few decades. This paper considers the phenomenon of the Genome Wide Association Study (GWAS) via one high profile example, the Wellcome Trust Case Control Consortium (WTCCC). The WTCCC despite not fulfilling promises of new health interventions is still understood as an important step towards tackling CCDs clinically. The 'sociology of expectations' has considered many examples of failure to fulfil promises and the subsequent negative consequences including disillusionment, disappointment and disinvestment. In order to explore why some domains remain resilient in the face of apparent failure, I employ the concept of the 'problematic' found in the work of Giles Deleuze. This alternative theoretical framework challenges the idea that the failure to reach promised goals results in largely negative outcomes for a given field. I will argue that collective scientific action is motivated not only by hopes for the future but also by the drive to create solutions to the actual setbacks and successes which scientists encounter in their day-to-day work. I draw on eighteen interviews.

Effects of single nucleotide polymorphism ascertainment on population structure inferences

Single nucleotide polymorphism (SNP) data are widely used in research on natural populations. Although they are useful, SNP genotyping data are known to contain bias, normally referred to as ascertainment bias, because they are conditioned by already confirmed variants. This bias is introduced during the genotyping process, including the selection of populations for novel SNP discovery and the number of individuals involved in the discovery panel and selection of SNP markers. It is widely recognized that ascertainment bias can cause inaccurate inferences in population genetics and several methods to address these bias issues have been proposed. However, especially in natural populations, it is not always possible to apply an ideal ascertainment scheme because natural populations tend to have complex structures and histories. In addition, it was not fully assessed if ascertainment bias has the same effect on different types of population structure. Here, we examine the effects of bias produced during the selection of population for SNP discovery and consequent SNP marker selection processes under three demographic models: the island, stepping-stone, and population split models. Results show that site frequency spectra and summary statistics contain biases that depend on the joint effect of population structure and ascertainment schemes. Additionally, population structure inferences are also affected by ascertainment bias. Based on these results, it is recommended to evaluate the validity of the ascertainment strategy prior to the actual typing process because the direction and extent of ascertainment bias vary depending on several factors.

Revisiting the metallothionein genes polymorphisms and the risk of oral squamous cell carcinoma in a Brazilian population

Background

Metallothioneins (MTs) gene polymorphisms have been associated with the ability of free radical scavenging and detoxification of heavy metals leading to cancer development. Our aim was to revisit, in a Brazilian population, single-nucleotide polymorphisms (SNPs) of the MT gene family previously associated with oral squamous cell carcinoma (OSCC).

Material and Methods

A case-control investigation with 28 OSCC patients and 45 controls was conducted, using conventional risk factors (tobacco use and alcohol consumption) as covariates. SNPs genotyping for rs8052334 (MT1B), rs964372 (MT1B), and rs1610216 (MT2A) was performed by PCR-RFLP, and SNPs for rs11076161 (MT1A) were analyzed by TaqMan assay.

Results

The only SNP associated with increased risk for OSCC was the MT-1A AA genotype (OR = 4.7; p = 0.01). We have also evidenced for the first time a significant linkage disequilibrium between the SNPs of MT-2A and MT-1A in this population with the highest frequency (30%) of the unfavorable haplotype G/A/C/T (rs1610216 / rs11076161 / rs964372 / rs8052334) of MT gene polymorphisms (OR = 6.2; p = 0.04). Interestingly, after removing the effects of conventional risk factors, we have uncovered the significance of the AA genotype of the rs11076161 with increased odds of 19-fold higher towards OSCC development.

Conclusions

This is the first demonstration that a significant linkage disequilibrium among gene polymorphisms of the MT family may affect susceptibility to oral cancer, which is conditioned by the G/A/C/T haplotype (rs1610216/rs11076161/rs964372/ rs8052334) and the MT-1A gene polymorphism has a potential clinical utility for the OSCC risk assessment.

Key words:Oral squamous cell carcinoma, polymorphism, metallothionein, oral cancer.

Prioritizing Pain-Associated Targets with Machine Learning

While hundreds of genes have been associated with pain, much of the molecular mechanisms of pain remain unknown. As a result, current analgesics are limited to few clinically validated targets. Here, we trained a machine learning (ML) ensemble model to predict new targets for 17 categories of pain. The model utilizes features from transcriptomics, proteomics, and gene ontology to prioritize targets for modulating pain. We focused on identifying novel G-protein-coupled receptors (GPCRs), ion channels, and protein kinases because these proteins represent the most successful drug target families. The performance of the model to predict novel pain targets is 0.839 on average based on AUROC, while the predictions for arthritis had the highest accuracy (AUROC = 0.929). The model predicts hundreds of novel targets for pain; for example, GPR132 and GPR109B are highly ranked GPCRs for rheumatoid arthritis. Overall, gene-pain association predictions cluster into three groups that are enriched for cytokine, calcium, and GABA-related cell signaling pathways. These predictions can serve as a foundation for future experimental exploration to advance the development of safer and more effective analgesics.

Effect of metabolic genetic variants on long-term disease comorbidity in patients with type 2 diabetes

Underlying genetic determinants contribute to developing type 2 diabetes (T2D) future diseases. The present study aimed to identify which genetic variants are associated with the incident of the major T2D co-morbid disease. First, we conducted a discovery study by investigating the genetic associations of comorbid diseases within the framework of the Utrecht Cardiovascular Pharmacogenetic studies by turning information of > 25 years follow-up data of 1237 subjects whom were genotyped and included in the discovery study. We performed Cox proportional-hazards regression to examine associations between genetic variants and comorbid diseases including cardiovascular diseases (CVD), chronic eye disease, cancer, neurologic diseases and chronic kidney disease. Secondly, we replicated our findings in two independent cohorts consisting of 1041 subjects. Finally, we performed a meta-analysis by combining the discovery and two replication cohorts. We ascertained 390 (39.7%) incident cases of CVD, 182 (16.2%) of chronic eye disease, 155 (13.8%) of cancer, 31 (2.7%) of neurologic disease and 13 (1.1%) of chronic kidney disease during a median follow-up of 10.2 years. In the discovery study, we identified a total of 39 Single Nucleotide Polymorphisms (SNPs) associated with comorbid diseases. The replication study, confirmed that rs1870849 and rs8051326 may play a role in the incidence of chronic eye disease in T2D patients. Half of patients developed at least one comorbid disease, with CVD occurring most often and earliest followed by chronic eye disease. Further research is needed to confirm the associations of two associated SNPs with chronic eye disease in T2D.

Exploiting XG Boost for Predicting Enhancer-promoter Interactions

Background:

Gene expression and disease control are regulated by the interaction between distal enhancers and proximal promoters, and the study of enhancer promoter interactions (EPIs) provides insight into the genetic basis of diseases.

Objective:

Although the recent emergence of high-throughput sequencing methods have a deepened understanding of EPIs, accurate prediction of EPIs still limitations.

Methods:

We have implemented a XGBoost-based approach and introduced two sets of features (epigenomic and sequence) to predict the interactions between enhancers and promoters in different cell lines.

Results:

Extensive experimental results show that XGBoost effectively predicts EPIs across three cell lines, especially when using epigenomic and sequence features.

Conclusion:

XGBoost outperforms other methods, such as random forest, Adadboost, GBDT, and TargetFinder.

Research Strategies for Low-Survival Cancers

While substantial progress has been made to improve the diagnosis, prognosis, and survivorship of patients with cancer, certain cancer types, along with metastatic and refractory disease, remain clinical challenges. To improve patient outcomes, ultimately, the cancer research community must meet and overcome these challenges, leading to improved approaches to treat the most difficult cancers. Here, we discuss research progress aimed at gaining a better understanding of the molecular and cellular changes in tumor cells and the surrounding stroma, presented at the 56th Irish Association for Cancer Research (IACR) Annual Conference. With a focus on poor prognosis cancers, such as esophageal and chemo-resistant colorectal cancers, we highlight how detailed molecular knowledge of tumor and stromal biology can provide windows of opportunity for biomarker discovery and therapeutic targets. Even with previously characterized targets, such as phosphoinositide 3-kinase (PI3K), one of the most altered proteins in all human cancers, new insights into how this protein may be more effectively inhibited through novel combination therapies is presented.

Genomics and bioinformatics capacity in Africa: no continent is left behind

Despite the poor genomics research capacity in Africa, efforts have been made to empower African scientists to get involved in genomics research, particularly that involving African populations. As part of the Human Heredity and Health in Africa (H3Africa) Consortium, an initiative was set to make genomics research in Africa an African endeavor and was developed through funding from the United States' National Institutes of Health Common Fund and the Wellcome Trust. H3Africa is intended to encourage a contemporary research approach by African investigators and to stimulate the study of genomic and environmental determinants of common diseases. The goal of these endeavors is to improve the health of African populations. To build capacity for bioinformatics and genomics research, organizations such as the African Society for Bioinformatics and Computational Biology have been established. In this article, we discuss the current status of the bioinformatics infrastructure in Africa as well as the training challenges and opportunities.

The emergent phenomenon of aspirin resistance: insights from genetic association studies

Despite the clinical benefits of aspirin, the interindividual variation in response to this antiplatelet drug is considerable. The manifestation of aspirin resistance (AR) is frequently observed, although this complex process remains poorly understood. While AR etiology is likely to be multifactorial, genetic factors appear to be preponderant. According to several genetic association studies, both genome-wide and candidate gene studies, numerous SNPs in cyclooxygenase, thromboxane and platelet receptors-related genes have been identified as capable of negatively affecting aspirin action. Thus, it is essential to understand the clinical relevance of AR-related SNPs as potential predictive and prognostic biomarkers as they may be essential to defining the AR phenotype.

Stem cells in natural product and medicinal plant drug discovery-An overview of new screening approaches

Natural products remain a rich source of new drugs, and the search for bioactive molecules from nature continues to play an important role in the development of new medicines. Also, there is increasing use of herbal medicines for the treatment of a plethora of diseases, and demands for more scientific evidence for their efficacy and safety remains a huge challenge. The propensity of stem cells to differentiate into almost every cell type not only holds promise for the delivery of cell-based therapies for currently incurable diseases or a useful tool in studying cell physiology and pathophysiology. Increasingly, stem cells are becoming an important tool in preclinical drug screening and toxicity testing. In this review, we examine the scientific advances made towards the use of pluripotent stem cells as a model for the screening of plant-based medicines. The combination of well-established in vitro electrophysiological and a plethora of toxicogenomic technologies, together with the optimisation of culture methods of herbal plants and pluripotent stem cells can be explored to establish the basis for efficacy, and tissue/organ-based toxicities of many currently used medicinal plants whose efficacies and toxicities remain unknown.

METTL14 Gene Polymorphisms Confer Neuroblastoma Susceptibility: An Eight-Center Case-Control Study

Neuroblastoma is the primary cause of cancer death in childhood. METTL14 is tightly linked to cancer. However, whether single-nucleotide polymorphisms (SNPs) in the METTL14 gene could predispose to neuroblastoma susceptibility lacks evidence. With an epidemiology case-control study, associations between METTL14 gene SNPs and overall risk for neuroblastoma were estimated in 898 cases and 1,734 controls. Following that, stratified analysis was performed. Among the five analyzed SNPs, rs298982 G>A and rs62328061 A>G exhibited a significant association with decreased susceptibility to neuroblastoma, whereas the associations with increased neuroblastoma susceptibility were observed for rs9884978 G>A and rs4834698 T>C. Moreover, subjects carrying two to five risk genotypes were more inclined to develop neuroblastoma than those with zero to one risk genotypes. The stratified analysis further demonstrated the protective effect of rs298982 G>A and rs62328061 A>G, as well as the predisposing effect of rs4834698 T>C and two to five risk genotypes, in certain subgroups. Haplotype analysis was performed. Moreover, false-positive report probability analysis validated the reliability of the significant results. The expression quantitative trait locus analysis revealed that rs298982 is correlated with the expression levels of its surrounding genes. Our results suggest that some SNPs in the METTL14 gene are associated with predisposition to neuroblastoma.

Association of the NCAN-TM6SF2-CILP2-PBX4-SUGP1-MAU2 SNPs and gene-gene and gene-environment interactions with serum lipid levels

This study investigated the association of the NCAN-TM6SF2-CILP2-PBX4-SUGP1-MAU2 SNPs and gene-gene and gene-environment interactions with serum lipid levels in the population of Southwest China. Genotyping of 12 SNPs (i.e., rs2238675, rs2228603, rs58542926, rs735273, rs16996148, rs968525, rs17216525, rs12610185, rs10401969, rs8102280, rs73001065 and rs150268548) was performed in 1248 hyperlipidemia patients and 1248 normal subjects. The allelic and genotypic frequencies of the detected SNPs differed substantially between the normal and hyperlipidemia groups (P < 0.05-0.001), and the association of the 12 SNPs and hyperlipidemia was also observed (P < 0.004-0.0001). Four haplotypes (i.e., NCAN C-C, CILP2 G-T, PBX4-SUGP1 G-C, and MAU2 C-A-G-T) and 5 gene-gene interaction haplotypes (i.e., rs2238675C-rs2228603C, rs16996148G-rs17216525T, rs12610185G-rs10401969C, rs73001065G-rs8102280A-rs150268548G-rs968525C and rs73001065C-rs8102280A-rs150268548G-rs96852）showed a protective effect, whereas four other haplotypes (i.e., TM6SF2 T-A, TM6SF2 C-A, MAU2 G-G-G-C and MAU2 C-G-A-T), as well as 4 gene-gene interaction haplotypes (i.e., rs58542926C-rs735273A, rs58542926T-rs735273A, rs73001065G-rs8102280G-rs150268548G-rs968525C, and rs73001065C-rs8102280G-rs150268548A-rs968525T), exhibited an inverse effect on hyperlipidemia (P < 0.05-0.0001). There were notable three-locus models comprising SNP-SNP, SNP-environment, and haplotype-haplotype interactions (P < 0.05-0.0001). The individuals with some genotypes and haplotypes reduced the prevalence of hyperlipidemia, whereas the individuals with some other genotypes and haplotypes augmented the prevalence of hyperlipidemia. The NCAN-TM6SF2-CILP2-PBX4-SUGP1-MAU2 SNPs and gene-gene and gene-environment interactions on hyperlipidemia were observed in the population of Southwest China.

The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019

The GWAS Catalog delivers a high-quality curated collection of all published genome-wide association studies enabling investigations to identify causal variants, understand disease mechanisms, and establish targets for novel therapies. The scope of the Catalog has also expanded to targeted and exome arrays with 1000 new associations added for these technologies. As of September 2018, the Catalog contains 5687 GWAS comprising 71673 variant-trait associations from 3567 publications. New content includes 284 full P-value summary statistics datasets for genome-wide and new targeted array studies, representing 6 × 10⁹ individual variant-trait statistics. In the last 12 months, the Catalog's user interface was accessed by ∼90000 unique users who viewed >1 million pages. We have improved data access with the release of a new RESTful API to support high-throughput programmatic access, an improved web interface and a new summary statistics database. Summary statistics provision is supported by a new format proposed as a community standard for summary statistics data representation. This format was derived from our experience in standardizing heterogeneous submissions, mapping formats and in harmonizing content. Availability: https://www.ebi.ac.uk/gwas/.

Construction, comparison and evolution of networks in life sciences and other disciplines

Network approaches have become pervasive in many research fields. They allow for a more comprehensive understanding of complex relationships between entities as well as their group-level properties and dynamics. Many networks change over time, be it within seconds or millions of years, depending on the nature of the network. Our focus will be on comparative network analyses in life sciences, where deciphering temporal network changes is a core interest of molecular, ecological, neuropsychological and evolutionary biologists. Further, we will take a journey through different disciplines, such as social sciences, finance and computational gastronomy, to present commonalities and differences in how networks change and can be analysed. Finally, we envision how borrowing ideas from these disciplines could enrich the future of life science research.

Aggressive prostate cancer phenotype and genome-wide association studies: where are we now?

The majority of prostate cancer (PCa) is indolent, however, a percentage of patients are initially diagnosed with metastatic disease, for which there is a worse prognosis. There is a lack of biomarkers to identify men at greater risk for developing aggressive PCa. Genome-wide association studies (GWAS) scan the genome to search associations of SNPs with specific traits, like cancer. To date, eight GWAS have resulted in the reporting of 16 SNPs associated with aggressive PCa (p < 5.00 × 10^-2). Still, validation studies need to be conducted to confirm the obtained results as GWAS can generate false-positive results. Furthermore, post-GWAS studies provide a better understanding of the functional consequences.

Computational analysis of functional single nucleotide polymorphisms associated with SLC26A4 gene

Single Nucleotide Polymorphisms (SNPs) are the most common candidate mutations in human beings that play a vital role in the genetic basis of certain diseases. Previous studies revealed that Solute Carrier Family 26 Member 4 (SLC26A4) being an essential gene of the multi-faceted transporter family SLC26 facilitates reflexive movement of Iodide into follicular lumen through apical membrane of thyrocyte. SLC26A4 gene encodes Pendred protein, a membrane glycoprotein, highly hydrophobic in nature, present at the apical membrane of thyrocyte functioning as transporter of iodide for thyroid cells. A minor genetic variation in SLC26A4 can cause Pendred syndrome, a syndrome associated with thyroid glands and deafness. In this study, we performed in-silico analysis of 674 missense SNPs of SLC26A4 using different computational platforms. The bunch of tools including SNPNEXUS, SNAP-2, PhD-SNP, SNPs&GO, I-Mutant, ConSurf, and ModPred were used to predict 23 highly confident damaging and disease causing nsSNPs (G209V, G197R, L458P, S427P, Q101P, W472R, N392Y, V359E, R409C, Q235R, R409P, G139V, G497S, H723R, D87G, Y127H, F667C, G334A, G95R, S427C, R291W, Q383H and E384G) that could potentially alter the SLC26A4 gene. Moreover, protein structure prediction, protein-ligand docking and Molecular Dynamics simulation were performed to confirm the impact of two evident alterations (Y127H and G334A) on the protein structure and function.

Replication of Newly Identified Genetic Associations Between Abdominal Aortic Aneurysm and SMYD2, LINC00540, PCIF1/MMP9/ZNF335, and ERG

OBJECTIVE

A recently published genome wide association study of abdominal aortic aneurysms (AAA), based on pooled case control data of European ancestry, identified four new loci for AAA: SMYD2 (top single nucleotide polymorphism [SNP] rs1795061), LINC00540 (rs9316871), PCIF1/MMP9/ZNF335 (rs3827066), and ERG (rs2836411). Of the four, rs1795061 and rs2836411 showed significant heterogeneity across studies and the p value for rs9316871 did not reach the genome wide significance threshold until discovery and replication data were pooled together in that study. The objective of this study was to replicate these newly identified genetic associations for AAA in a US based prospective cohort study, the Atherosclerosis Risk in Communities (ARIC) Study, and a Greece based case control study.

METHODS

ARIC identified 408 clinically diagnosed AAAs among 8 962 individuals of European ancestry during a median of 22 years of follow up. The Greek case control study included 341 AAAs of European ancestry recruited in a tertiary referral centre and 292 geographically and ethnically matched controls recruited from the same institution. A Cox proportional hazards model was used to analyse the ARIC data and logistic regression to analyse the Greek data.

RESULTS

In ARIC, rs9316871 and rs3827066 were significantly associated with AAA risk (HR [p] was 0.77 [.004] and 1.22 [.03], respectively), rs2836411 was associated at borderline significance (1.13 [.08]), whereas rs1795061 was not associated (p = .55). In the Greek case control study, rs1795061 and rs2836411 were significantly associated with AAA (OR [p] was 1.66 [< .001] and 1.29 [.04], respectively), whereas rs9316871 was not (p = .81). Genotyping of rs3827066 did not succeed. In the meta-analysis of the two studies, the association for rs9316871and rs2836411 was statistically significant and consistent between the two studies: p = .02 and .007, respectively.

CONCLUSIONS

Associations between rs9316871and rs2836411 and AAA risk were replicated in the meta-analysis of the two independent cohorts, providing further support for the importance of these loci in the aetiology of AAA.

Opportunities and challenges of integrating genetics education about human diversity into public health nurses' responsibilities in Japan

BACKGROUND

Many genetic tests are now available due to evolution by the Human Genome Project. However, the growing use of genetic testing and screening may not only lead to improvements in public health and health promotion, but also trigger grave ethical, legal, and societal concerns. The involvement of community healthcare providers is expected in the future because they have direct contact with the residents through their health programs. The aims of the current study were to clarify how public health nurses perceive the relationship between genetics and professional duties and to identify opportunities and challenges of integrating genetics education into their professional duties.

METHODS

In 2017, data were collected through a focus group interview. Content related to the 'presence or absence of health consultation related to genetic issues as part of actual job duties' and 'training for handling genetic-related health consultations' was extracted. Entire sentences were coded and categorized based on similar semantic content.

RESULTS

Public health nurses had difficulties in recognizing genetic issues in public health activities. In some cases, genetic contents were included in conversation and consultation with the general public. Through the professional education and experiences, public health nurses needed specialized education, post-graduation studies and mentoring about genetics.

CONCLUSIONS

Public health nurses whose professional duties do not directly relate to genetics were exposed to genetics-related episodes on a regular basis without their awareness. The provision of accurate information and knowledge related to genetics by public health nurses would also provide an opportunity for clients to be informed about their latent genetic risks. Hence, there is a need for practical resources, the establishment of collaboration networks, and the development of professional organizations for public health nurses.

Seq: A High-Performance Language for Bioinformatics

The scope and scale of biological data are increasing at an exponential rate, as technologies like next-generation sequencing are becoming radically cheaper and more prevalent. Over the last two decades, the cost of sequencing a genome has dropped from $100 million to nearly $100-a factor of over 10⁶-and the amount of data to be analyzed has increased proportionally. Yet, as Moore's Law continues to slow, computational biologists can no longer rely on computing hardware to compensate for the ever-increasing size of biological datasets. In a field where many researchers are primarily focused on biological analysis over computational optimization, the unfortunate solution to this problem is often to simply buy larger and faster machines. Here, we introduce Seq, the first language tailored specifically to bioinformatics, which marries the ease and productivity of Python with C-like performance. Seq starts with a subset of Python-and is in many cases a drop-in replacement-yet also incorporates novel bioinformatics- and computational genomics-oriented data types, language constructs and optimizations. Seq enables users to write high-level, Pythonic code without having to worry about low-level or domain-specific optimizations, and allows for the seamless expression of the algorithms, idioms and patterns found in many genomics or bioinformatics applications. We evaluated Seq on several standard computational genomics tasks like reverse complementation, k-mer manipulation, sequence pattern matching and large genomic index queries. On equivalent CPython code, Seq attains a performance improvement of up to two orders of magnitude, and a 160× improvement once domain-specific language features and optimizations are used. With parallelism, we demonstrate up to a 650× improvement. Compared to optimized C++ code, which is already difficult for most biologists to produce, Seq frequently attains up to a 2× improvement, and with shorter, cleaner code. Thus, Seq opens the door to an age of democratization of highly-optimized bioinformatics software.

Learning Physiology From Inherited Kidney Disorders

The identification of genes causing inherited kidney diseases yielded crucial insights in the molecular basis of disease and improved our understanding of physiological processes that operate in the kidney. Monogenic kidney disorders are caused by mutations in genes coding for a large variety of proteins including receptors, channels and transporters, enzymes, transcription factors, and structural components, operating in specialized cell types that perform highly regulated homeostatic functions. Common variants in some of these genes are also associated with complex traits, as evidenced by genome-wide association studies in the general population. In this review, we discuss how the molecular genetics of inherited disorders affecting different tubular segments of the nephron improved our understanding of various transport processes and of their involvement in homeostasis, while providing novel therapeutic targets. These include inherited disorders causing a dysfunction of the proximal tubule (renal Fanconi syndrome), with emphasis on epithelial differentiation and receptor-mediated endocytosis, or affecting the reabsorption of glucose, the handling of uric acid, and the reabsorption of sodium, calcium, and magnesium along the kidney tubule.

Heritable natural variation of light/dark preference in an outbred zebrafish population

Anxiety is a fear-like response to stimuli perceived to be threatening. Excessive or uncontrollable anxiety is a debilitating psychiatric disorder which affects many people throughout their lifetime. In unravelling the complex genetic and environmental regulations of anxiety-like phenotypes, models measuring the natural dark avoidance of larval zebrafish have shed light on the individual variation and heritability of this anxiety-related trait. Using the light/dark choice paradigm and selective breeding, this study aims to validate previous findings of the variable (VDA) and strong dark aversion (SDA) heritability in AB-WT larval zebrafish using the outbred zebrafish strain EK, which offers more genetic diversity to aid in future molecular mapping efforts. 190 larvae (6 days post fertilization [dpf] and 7 dpf) were tested across four trials and divided into variable (VDA), medium (MDA) and strong (SDA) dark aversion for further in-crosses. VDA and MDA larvae became more explorative with time, whereas SDA larvae rarely left the preferred light zone. The SDA and VDA in-crosses significantly increased the respective phenotypes in the second generation of larvae, whereas VDA × MDA inter-crosses did not. For the second-generation SDA cohort, dark aversion correlated with increased thigmotaxis, which reinforces SDA as an anxiety-like phenotype. Our finding that the dark aversion trait and SDA and VDA phenotypes are heritable in an outbred zebrafish population lays an important foundation for future studies of genetic underpinnings using whole-genome mapping methods. This conserved fear/anxiety-like response in a highly accessible model organism also allows for further pharmacological and behavioral studies to elucidate the etiology of anxiety and the search for novel therapeutics for anxiety disorders.

MHC Genomics and Disease: Looking Back to Go Forward

Ancestral haplotypes are conserved but extremely polymorphic kilobase sequences, which have been faithfully inherited over at least hundreds of generations in spite of migration and admixture. They carry susceptibility and resistance to diverse diseases, including deficiencies of CYP21 hydroxylase (47.1) and complement components (18.1), as well as numerous autoimmune diseases (8.1). The haplotypes are detected by segregation within ethnic groups rather than by SNPs and GWAS. Susceptibility to some other diseases is carried by specific alleles shared by multiple ancestral haplotypes, e.g., ankylosing spondylitis and narcolepsy. The difference between these two types of association may explain the disappointment with many GWAS. Here we propose a pathway for combining the two different approaches. SNP typing is most useful after the conserved ancestral haplotypes have been defined by other methods.

Development of a general logistic model for disease risk prediction using multiple SNPs

Human diseases are usually linked to multiloci genetic alterations, including single‐nucleotide polymorphisms (SNPs). Methods to use these SNPs for disease risk prediction (DRP) are of clinical interest. DRP algorithms explored by commercial companies to date have tended to be complex and led to controversial prediction results. Here, we present a general approach for establishing a logistic model‐based DRP algorithm, in which multiple SNP risk factors from different publications are directly used. In particular, the coefficient β of each SNP is set as the natural logarithm of the reported odds ratio, and the constant coefficient β₀ is comprehensively determined by the coefficient and frequency of each SNP and the average disease risk in populations. Furthermore, homozygous SNP is considered a dummy variable, and the SNPs are updated (addition, deletion and modification) if necessary. Importantly, we validated this algorithm as a proof of concept: two patients with lung cancer were identified as the maximum risk cases from 57 Chinese individuals. Our logistic model‐based DRP algorithm is apparently more intuitive and self‐evident than the algorithms explored by commercial companies, and it may facilitate DRP commercialization in the era of personalized medicine.

Genetic Variation in Long-Range Enhancers

Cis-regulatory elements (CREs), including insulators, promoters, and enhancers, play critical roles in the establishment and maintenance of normal cellular function. Within each cell, the 3D structure of chromatin is arranged in specific patterns to expose the CREs required for optimal spatiotemporal regulation of gene expression. CREs can act over large distances along the linear genome, facilitated by looping of the intervening chromatin to allow direct interaction between distal regulatory elements and their target genes. A number of pathologies are associated with dysregulation of CRE function, including developmental disorders, cancers, and neuropsychiatric disease. A majority of known neuropsychiatric disease risk loci are noncoding, and increasing evidence suggests that they contribute to disease through disruption of CREs. As such, rather than directly altering the amino acid content of proteins, these variants are instead thought to affect where, when, and to what extent a given gene is expressed. The distances over which CREs can operate often render their target genes difficult to identify. Furthermore, as many risk loci contain multiple variants in high linkage disequilibrium, identification of the causative single nucleotide polymorphism(s) therein is not straightforward. Thus, deciphering the genetic etiology of complex neuropsychiatric disorders presents a significant challenge.

Inherited Retinal Disorders: Using Evidence as a Driver for Implementation

Incremental advances in the field of retinal genetics have transformed our understanding of inherited retinal disorders and have led to the development of powerful diagnostic tests and promising gene-based therapies. Despite this, successful integration of these developments into routine healthcare is frequently ineffective. Providing robust evidence of benefit can accelerate the implementation of clinical genetic interventions. For example, the adoption of a genetic test is much more likely when the test's clinical utility (i.e. its ability to influence management and health outcomes) has been clearly demonstrated. However, accruing such evidence for rare conditions like inherited retinal disorders is challenging. Conducting sufficiently powered studies requires both efficient study designs and large-scale, international collaboration. Reaching all populations and as many affected individuals as possible is key. Equally important are efforts to precisely and consistently capture phenotypic information, including natural history data. This article summarizes some of the current obstacles to implemen-tation and discusses approaches to overcome these barriers.

HTRA1 synergizes with oxidized phospholipids in promoting inflammation and macrophage infiltration essential for ocular VEGF expression

Understanding oxidative stress and HTRA1 locus in abnormal angiogenesis resulting in wet AMD pathology is an important step in developing a novel therapeutic approach. Using subretinal injection of oxLDL into C57BL/6 mice, we observed a lesion resembling the features of choroidal neovascularization (CNV), including macrophage infiltration, increased VEGF expression, and neovascularization. However, incubating ARPE-19 cells with oxLDL–a carrier of oxidized phospholipids–resulted in increased expression of inflammatory cytokines and chemoattractant proteins that recruited monocytes, but no substantial increase in expression of VEGF. Furthermore, incubation of ARPE-19 with oxLDL induced higher expression of HTRA1, which we showed to synergize with oxLDL in elevating the expression of inflammatory cytokines and chemoattractant factors. To investigate the role of macrophage infiltration on these expression changes, we treated cultured J774 macrophages with oxLDL and applied the conditioned medium onto ARPE-19 cells. This treatment was found to greatly enhance the expression of VEGF in ARPE-19, indicating the necessity of macrophage secretory products to induce increased expression of VEGF in retinal pigment epithelium. Gene expression analysis revealed that oxLDL induced the expression of Wnt3A in macrophages, a key activator of canonical Wnt signaling pathways. In addition, western blot analysis showed that the macrophage conditioned media further enhanced the reduction of phosphorylated β-catenin induced by oxLDL. Lastly, we investigated HTRA1 as a potential target for AMD therapeutics. We demonstrated the ability of anti-HTRA1 antibody in vitro to neutralize the protease activity of HTRA1 and reduce the inflammatory and angiogenic response to oxidative stress. Finally, we validated the neutralizing effect of anti-HTRA1 antibody in vivo by evaluating lesion size and protein expression in a laser-photocoagulation murine model of CNV. We found that the combination of oxLDL and HTRA1 enhanced CNV size, which was reversed by the addition of anti-HTRA1 antibody. This study not only provides preliminary evidence that HTRA1 may be a viable target for AMD therapeutics but also elucidates the biochemical mechanisms by which this therapeutic effect may be mediated.