Problems of reporting genetic associations with complex outcomes

Genetics of ischemic stroke functional outcome

Ischemic stroke, which accounts for 87% of cerebrovascular accidents, is responsible for massive global burden both in terms of economic cost and personal hardship. Many stroke survivors face long-term disability-a phenotype associated with an increasing number of genetic variants. While clinical variables such as stroke severity greatly impact recovery, genetic polymorphisms linked to functional outcome may offer physicians a unique opportunity to deliver personalized care based on their patient's genetic makeup, leading to improved outcomes. A comprehensive catalogue of the variants at play is required for such an approach. In this review, we compile and describe the polymorphisms associated with outcome scores such as modified Rankin Scale and Barthel Index. Our search identified 74 known genetic polymorphisms spread across 48 features associated with various poststroke disability metrics. The known variants span diverse biological systems and are related to inflammation, vascular homeostasis, growth factors, metabolism, the p53 regulatory pathway, and mitochondrial variation. Understanding how these variants influence functional outcome may be helpful in maximizing poststroke recovery.

Practical approaches to improving translatability and reproducibility in preclinical pain research

Pain research continues to face the challenge of poor translatability of pre-clinical studies. In this short primer, we are summarizing the possible causes, with an emphasis on practical and constructive solutions. In particular, we stress the importance of increased heterogeneity in animal studies; formal or informal pre-registration to combat publication bias; and increased statistical training in order to help pre-clinical scientists appreciate the usefulness of available experimental design and reporting guidelines.

Open Science Practices in Psychiatric Genetics: A Primer

Open science ensures that research is transparently reported and freely accessible for all to assess and collaboratively build on. Psychiatric genetics has led among the health sciences in implementing some open science practices in common study designs, such as replication as part of genome-wide association studies. However, thorough open science implementation guidelines are limited and largely not specific to data, privacy, and research conduct challenges in psychiatric genetics. Here, we present a primer of open science practices, including selection of a research topic with patients/nonacademic collaborators, equitable authorship and citation practices, design of replicable, reproducible studies, preregistrations, open data, and privacy issues. We provide tips for informative figures and inclusive, precise reporting. We discuss considerations in working with nonacademic collaborators and distributing research through preprints, blogs, social media, and accessible lecture materials. Finally, we provide extra resources to support every step of the research process.

The phenotype-genotype reference map: Improving biobank data science through replication

Population-scale biobanks linked to electronic health record data provide vast opportunities to extend our knowledge of human genetics and discover new phenotype-genotype associations. Given their dense phenotype data, biobanks can also facilitate replication studies on a phenome-wide scale. Here, we introduce the phenotype-genotype reference map (PGRM), a set of 5,879 genetic associations from 523 GWAS publications that can be used for high-throughput replication experiments. PGRM phenotypes are standardized as phecodes, ensuring interoperability between biobanks. We applied the PGRM to five ancestry-specific cohorts from four independent biobanks and found evidence of robust replications across a wide array of phenotypes. We show how the PGRM can be used to detect data corruption and to empirically assess parameters for phenome-wide studies. Finally, we use the PGRM to explore factors associated with replicability of GWAS results.

Genomic Association Analysis of Growth and Backfat Traits in Large White Pigs

The pig industry is significantly influenced by complex traits such as growth rate and fat deposition, which have substantial implications for economic returns. Over the years, remarkable genetic advancements have been achieved through intense artificial selection to enhance these traits in pigs. In this study, we aimed to investigate the genetic factors that contribute to growth efficiency and lean meat percentages in Large White pigs. Specifically, we focused on analyzing two key traits: age at 100 kg live weight (AGE100) and backfat thickness at 100 kg (BF100), in three distinct Large White pig populations-500 Canadian, 295 Danish, and 1500 American Large White pigs. By employing population genomic techniques, we observed significant population stratification among these pig populations. Utilizing imputed whole-genome sequencing data, we conducted single population genome-wide association studies (GWAS) as well as a combined meta-analysis across the three populations to identify genetic markers associated with the aforementioned traits. Our analyses highlighted several candidate genes, such as CNTN1-which has been linked to weight loss in mice and is potentially influential for AGE100-and MC4R, which is associated with obesity and appetite and may impact both traits. Additionally, we identified other genes-namely, PDZRN4, LIPM, and ANKRD22-which play a partial role in fat growth. Our findings provide valuable insights into the genetic basis of these important traits in Large White pigs, which may inform breeding strategies for improved production efficiency and meat quality.

Polymorphisms −374 T/A and −429 T/C of the Receptor for Advanced Glycation End-Products (RAGE) and Serum Levels of RAGE (sRAGE) Are Not Associated with Metabolic Syndrome

RAGE is a multi-ligand transmembrane glycoprotein that promotes biological signals associated with inflammatory responses and degenerative diseases. sRAGE is a soluble variant, proposed as an inhibitor of RAGE activity. −374 T/A and −429 T/C polymorphisms of the advanced glycation end products receptor AGER gene are associated with the development of some diseases, such as type of cancer, cardiovascular disease, and micro and macrovascular disease in diabetes among others but their role in metabolic syndrome (MS) is still unknown. We studied 80 healthy men without MS, and 80 men with MS according to the harmonized criteria. −374 T/A and −429 T/C polymorphisms were genotyped by RT-PCR, and sRAGE was measured by ELISA. Allelic and genotypic frequencies did not differ between Non-MS and MS groups (−374 T/A p = 0.48, p = 0.57 and −429 T/C p = 0.36, p = 0.59). Significant differences were found in fasting glucose levels and diastolic blood pressure among the genotypes of the −374 T/A polymorphism in the Non-MS group (p < 0.01 and p = 0.008). Glucose levels were different between −429 T/C genotypes in the MS group (p = 0.02). sRAGE levels were similar in both groups, but in the Non-MS group showed a significant difference between individuals with only 1 or 2 components of the metabolic syndrome (p = 0.047). However, no associations of any SNP with MS were found (recessive model p = 0.48, dominant model p = 0.82 for −374 T/A; recessive model p = 0.48, dominant model p = 0.42 for −429 T/C). −374 T/A and −429 T/C polymorphisms are not associated with MS in Mexican population and have no influence on serum sRAGE levels.

Comparison of Database Searching Programs for the Analysis of Single-Cell Proteomics Data

Single-cell proteomics is emerging as an important subfield in the proteomics and mass spectrometry communities, with potential to reshape our understanding of cell development, cell differentiation, disease diagnosis, and the development of new therapies. Compared with significant advancements in the "hardware" that is used in single-cell proteomics, there has been little work comparing the effects of using different "software" packages to analyze single-cell proteomics datasets. To this end, seven popular proteomics programs were compared here, applying them to search three single-cell proteomics datasets generated by three different platforms. The results suggest that MSGF+, MSFragger, and Proteome Discoverer are generally more efficient in maximizing protein identifications, that MaxQuant is better suited for the identification of low-abundance proteins, that MSFragger is superior in elucidating peptide modifications, and that Mascot and X!Tandem are better for analyzing long peptides. Furthermore, an experiment with different loading amounts was carried out to investigate changes in identification results and to explore areas in which single-cell proteomics data analysis may be improved in the future. We propose that this comparative study may provide insight for experts and beginners alike operating in the emerging subfield of single-cell proteomics.

Identification of rare missense mutations in the glutamate ionotropic receptor AMPA type subunit genes in schizophrenia

OBJECTIVE

The alpha-amino-3-hydroxy-5-methyl-4-isoxazole propionate (AMPA) receptors significantly regulate the synaptic transmission and functions of various synaptic receptors. This study aimed to identify single nucleotide mutations in the glutamate receptor, ionotropic, AMPA type (GRIA) gene family, which is associated with schizophrenia.

METHODS

The exon regions of four genes (GRIA1, GRIA2, GRIA3, and GRIA4) encoding glutamate ionotropic receptor AMPA type proteins were resequenced in 516 patients with schizophrenia. We analyzed the protein function of the identified rare mutants via immunoblotting.

RESULTS

A total of 24 coding variants were detected in the GRIA gene family, including six missense mutations, 17 synonymous mutations, and one frameshift insertion. Notably, three ultra-rare missense mutations (GRIA1p.V182A, GRIA2p.P123Q, and GRIA4p.Y491H) were not documented in the single nucleotide polymorphism database, gnomAD genomes, and 1517 healthy controls available from Taiwan BioBank. Immunoblotting revealed GRIA4p.Y491H mutant with altered protein expressions in cultured cells compared with the wild type.

CONCLUSION

Our findings suggest that, in some patients affected by schizophrenia, the GRIA gene family harbors rare functional mutations, which support rare coding variants that could contribute to the genetic architecture of this illness. The in-vitro impacts of these rare pathological mutations on the pathophysiology of schizophrenia are worthy of future investigation.

From SNP to pathway-based GWAS meta-analysis: do current meta-analysis approaches resolve power and replication in genetic association studies?

Genome-wide association studies (GWAS) have benefited greatly from enhanced high-throughput technology in recent decades. GWAS meta-analysis has become increasingly popular to highlight the genetic architecture of complex traits, informing about the replicability and variability of effect estimations across human ancestries. A wealth of GWAS meta-analysis methodologies have been developed depending on the input data and the outcome information of interest. We present a survey of current approaches from SNP to pathway-based meta-analysis by acknowledging the range of resources and methodologies in the field, and we provide a comprehensive review of different categories of Genome-Wide Meta-analysis methods employed. These methods highlight different levels at which GWAS meta-analysis may be done, including Single Nucleotide Polymorphisms, Genes and Pathways, for which we describe their framework outline. We also discuss the strengths and pitfalls of each approach and make suggestions regarding each of them.

Gene Therapy for Chronic Traumatic Brain Injury: Challenges in Resolving Long-term Consequences of Brain Damage

The gene therapy is alluring not only for CNS disorders but also for other pathological conditions. Gene therapy employs the insertion of a healthy gene into the identified genome to replace or replenish genes responsible for pathological disorder or damage due to trauma. The last decade has seen a drastic change in the understanding of vital aspects of gene therapy. Despite the complexity of traumatic brain injury (TBI), the advent of gene therapy in various neurodegenerative disorders has reinforced the ongoing efforts of alleviating TBI-related outcomes with gene therapy. The review highlights the genes modulated in response to TBI and evaluates their impact on the severity and duration of the injury. We have reviewed strategies that pinpointed the most relevant gene targets to restrict debilitating events of brain trauma and utilize vector of choice to deliver the gene of interest at the appropriate site. We have made an attempt to summarize the long-term neurobehavioral consequences of TBI due to numerous pathometabolic perturbations associated with a plethora of genes. Herein, we shed light on the basic pathological mechanisms of brain injury, genetic polymorphism in individuals susceptible to severe outcomes, modulation of gene expression due to TBI, and identification of genes for their possible use in gene therapy. The review also provides insights on the use of vectors and challenges in translations of this gene therapy to clinical practices.

Neuroimaging Genetics and Network Analysis in Alzheimer's Disease

The issue of the genetics in brain imaging phenotypes serves as a crucial link between two distinct scientific fields: neuroimaging genetics (NG). The articles included here provide solid proof that this NG link has considerable synergy. There is a suitable collection of articles that offer a wide range of viewpoints on how genetic variations affect brain structure and function. They serve as illustrations of several study approaches used in contemporary genetics and neuroscience. Genome-wide association studies and candidate-gene association are two examples of genetic techniques. Cortical gray matter structural/volumetric measures from magnetic resonance imaging (MRI) are sources of information on brain phenotypes. Together, they show how various scientific disciplines have benefited from significant technological advances, such as the single-nucleotide polymorphism array in genetics and the development of increasingly higher-resolution MRI imaging. Moreover, we discuss NG's contribution to expanding our knowledge about the heterogeneity within Alzheimer's disease as well as the benefits of different network analyses.

Toll-Like Receptor Polymorphisms and the Risk of Cancer: Meta-analysis Study

A systematic review and meta-analysis is a useful method to summarize the different results from primary data, which can then provide an evidence-based outcome. Meta-analysis generates quantitative data by calculating effect sizes, which include odd ratios, relative risks, proportions, correlation coefficients, and so forth. The study of single-nucleotide polymorphisms (SNPs) and the association with the interested outcome is one discipline that has resulted in inconsistent relations. Therefore, the meta-analysis aimed to summarize the relevant data on SNPs associated with the outcome of interest. Herein, we describe a comprehensive meta-analysis on Toll-like receptor-9 polymorphism and the risk of cervical cancer.

An interleukin-1 polymorphism additionally intensified by atopy as prognostic factor for aseptic non-mechanical complications in metal knee and hip arthroplasty

Background

In contrast to infection or mechanical issues joint replacement failure following inflammatory adverse reactions is poorly understood.

Objective

To assess the association of IL-1β polymorphisms and history of allergy with aseptic non-mechanical complications following arthroplasty.

Methods

In 102 patients with aseptic non-mechanically caused symptomatic knee or hip arthroplasty (SA) and 93 patients with asymptomatic arthroplasty (AA) questionnaire-based history, patch test with at least standard series, lymphocyte transformation test (LTT) with nickel, cobalt and chromium and interleukin-1 polymorphism analysis were done. Three polymorphisms of the IL1B gene [IL-1b -3954 (rs1143634), IL-1b -511 (rs16944) and IL-1b -31 (rs1143627)] and one polymorphism of the IL1RN gene [IL1RN intron 2, variable number of tandem repeats, VNTR (rs2234663)] were assessed by PCR and gel electrophoresis.

Results

We found no significant difference in smoking history and atopy but 25% versus 10% of self-reported metal allergy in SA versus AA; the patch test (respective, LTT) for metal sensitivity was more often positive in SA patients. The allele 498 bp of the IL1RN polymorphism occurred significantly more often in the SA group (37% versus 11%; p < 0.0001). Upon additional presence of atopy, the difference was even greater (60% vs 10%) (p < 0.000001). There was no association of IL-1 polymorphisms with metal allergy.

Conclusion

The IL1RN VNTR allele 498 bp was strongly associated with SA. In patients with a history of atopy, presence of the IL1RN VNTR allele 498 bp led to a four-fold higher SA prevalence compared to patients without this allele.

Integrating genome-wide association studies and population genomics analysis reveals the genetic architecture of growth and backfat traits in pigs

Growth and fat deposition are complex traits, which can affect economical income in the pig industry. Due to the intensive artificial selection, a significant genetic improvement has been observed for growth and fat deposition in pigs. Here, we first investigated genomic-wide association studies (GWAS) and population genomics (e.g., selection signature) to explore the genetic basis of such complex traits in two Large White pig lines (n = 3,727) with the GeneSeek GGP Porcine HD array (n = 50,915 SNPs). Ten genetic variants were identified to be associated with growth and fatness traits in two Large White pig lines from different genetic backgrounds by performing both within-population GWAS and cross-population GWAS analyses. These ten significant loci represented eight candidate genes, i.e., NRG4, BATF3, IRS2, ANO1, ANO9, RNF152, KCNQ5, and EYA2. One of them, ANO1 gene was simultaneously identified for both two lines in BF100 trait. Compared to single-population GWAS, cross-population GWAS was less effective for identifying SNPs with population-specific effect, but more powerful for detecting SNPs with population-shared effects. We further detected genomic regions specifically selected in each of two populations, but did not observe a significant enrichment for the heritability of growth and backfat traits in such regions. In summary, the candidate genes will provide an insight into the understanding of the genetic architecture of growth-related traits and backfat thickness, and may have a potential use in the genomic breeding programs in pigs.

The failure of drug repurposing for COVID-19 as an effect of excessive hypothesis testing and weak mechanistic evidence

The current strategy of searching for an effective treatment for COVID-19 relies mainly on repurposing existing therapies developed to target other diseases. Conflicting results have emerged in regard to the efficacy of several tested compounds but later results were negative. The number of conducted and ongoing trials and the urgent need for a treatment pose the risk that false-positive results will be incorrectly interpreted as evidence for treatments' efficacy and a ground for drug approval. Our purpose is twofold. First, we show that the number of drug-repurposing trials can explain the false-positive results. Second, we assess the evidence for treatments' efficacy from the perspective of evidential pluralism and argue that considering mechanistic evidence is particularly needed in cases when the evidence from clinical trials is conflicting or of low quality. Our analysis is an application of the program of Evidence Based Medicine Plus (EBM+) to the drug repurposing trials for COVID. Our study shows that if decision-makers applied EBM+, authorizing the use of ineffective treatments would be less likely. We analyze the example of trials assessing the efficacy of hydroxychloroquine as a treatment for COVID-19 and mechanistic evidence in favor of and against its therapeutic power to draw a lesson for decision-makers and drug agencies on how excessive hypothesis testing can lead to spurious findings and how studying negative mechanistic evidence can be helpful in discriminating genuine from spurious results.

Pharmacogenomics in drug-induced cardiotoxicity: Current status and the future

Drug-induced cardiotoxicity (DICT) is an important concern of drug safety in both drug development and clinical application. The clinical manifestations of DICT include cardiomyopathy, arrhythmia, myocardial ischemia, heart failure, and a series of cardiac structural and functional changes. The occurrence of DICT has negative impacts on the life quality of the patients, brings additional social and economic burden. It is important to identify the potential factors and explore the mechanisms of DICT. Traditional cardiovascular risk factors can only partially explain the risk of DICT. Pharmacogenomic studies show accumulated evidence of genetics in DICT and suggest the potential to guide precision therapy to reduce risk of cardiotoxicity. The comprehensive application of technologies such as third-generation sequencing, human induced pluripotent stem (iPS) cells and genome editing has promoted the in-depth understanding of the functional role of susceptible genes in DICT. This paper reviewed drugs that cause DICT, the clinical manifestations and laboratory tests, as well as the related content of genetic variations associated with the risk of DICT, and further discussed the implication of new technologies in pharmacogenomics of DICT.

Does persistence to methotrexate treatment in early rheumatoid arthritis have a familial component?

Objectives

To assess whether persistence to treatment with methotrexate (MTX) in early rheumatoid arthritis (RA) is shared among first-degree relatives with RA and to estimate any underlying heritability.

Methods

First-degree relative pairs diagnosed with RA 1999–2018 and starting MTX (in monotherapy) as their first disease-modifying anti-rheumatic drug (DMARD) treatment were identified by linking the Swedish Rheumatology Quality Register to national registers. Short- and long-term persistence to MTX was defined as remaining on treatment at 1 and 3 years, respectively, with no additional DMARDs added. We assessed familial aggregation through relative risks (RR) using log-binomial regression with robust standard errors and estimated heritability using tetrachoric correlations. We also explored the familial aggregation of EULAR treatment response after 3 and 6 months. To mimic the clinical setting, we also tested the association between having a family history of MTX persistence and persistence within the index patient.

Results

Familial persistence was not associated with persistence at 1 (RR=1.02, 95% CI 0.87–1.20), only at 3 (RR=1.41, 95% CI 1.14–1.74) years. Heritability at 1 and 3 years was estimated to be 0.08 (95% CI 0–0.43) and 0.58 (95% CI 0.27–0.89), respectively. No significant associations were found between family history and EULAR response at 3 and 6 months, neither overall nor in the clinical setting analysis.

Conclusions

Our findings imply a familial component, including a possible genetic element, within the long-term persistence to MTX following RA diagnosis. Whether this component is reflective of characteristics of the underlying RA disease or determinants for sustained response to MTX in itself will require further investigation.

Evaluating the role of common risk variation in the recurrence risk of schizophrenia in multiplex schizophrenia families

Multiplex families have higher recurrence risk of schizophrenia compared to the families of sporadic cases, but the source of this increased recurrence risk is unknown. We used schizophrenia genome-wide association study data (N = 156,509) to construct polygenic risk scores (PRS) in 1005 individuals from 257 multiplex schizophrenia families, 2114 ancestry-matched sporadic cases, and 2205 population controls, to evaluate whether increased PRS can explain the higher recurrence risk of schizophrenia in multiplex families compared to ancestry-matched sporadic cases. Using mixed-effects logistic regression with family structure modeled as a random effect, we show that SCZ PRS in familial cases does not differ significantly from sporadic cases either with, or without family history (FH) of psychotic disorders (All sporadic cases p = 0.90, FH+ cases p = 0.88, FH- cases p = 0.82). These results indicate that increased burden of common schizophrenia risk variation as indexed by current SCZ PRS, is unlikely to account for the higher recurrence risk of schizophrenia in multiplex families. In the absence of elevated PRS, segregation of rare risk variation or environmental influences unique to the families may explain the increased familial recurrence risk. These findings also further validate a genetically influenced psychosis spectrum, as shown by a continuous increase of common SCZ risk variation burden from unaffected relatives to schizophrenia cases in multiplex families. Finally, these results suggest that common risk variation loading are unlikely to be predictive of schizophrenia recurrence risk in the families of index probands, and additional components of genetic risk must be identified and included in order to improve recurrence risk prediction.

No replication of previously reported association with genetic variants in the T cell receptor alpha (TRA) locus for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS)

Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a disease with a variety of symptoms such as post-exertional malaise, fatigue, and pain, but where aetiology and pathogenesis are unknown. An increasing number of studies have implicated the involvement of the immune system in ME/CFS. Furthermore, a hereditary component is suggested by the reported increased risk for disease in relatives, and genetic association studies are being performed to identify potential risk variants. We recently reported an association with the immunologically important human leucocyte antigen (HLA) genes HLA-C and HLA-DQB1 in ME/CFS. Furthermore, a genome-wide genetic association study in 42 ME/CFS patients reported significant association signals with two variants in the T cell receptor alpha (TRA) locus (P value <5 × 10^-8). As the T cell receptors interact with the HLA molecules, we aimed to replicate the previously reported findings in the TRA locus using a large Norwegian ME/CFS cohort (409 cases and 810 controls) and data from the UK biobank (2105 cases and 4786 controls). We investigated numerous SNPs in the TRA locus, including the two previously ME/CFS-associated variants, rs11157573 and rs17255510. No associations were observed in the Norwegian cohort, and there was no significant association with the two previously reported SNPs in any of the cohorts. However, other SNPs showed signs of association (P value <0.05) in the UK Biobank cohort and meta-analyses of Norwegian and UK biobank cohorts, but none survived correction for multiple testing. Hence, our research did not identify any reliable associations with variants in the TRA locus.

Association between G2677T/A polymorphism in ABCB1 gene and the risk of drug resistance epilepsy: An updated systematic review and meta-analysis

PURPOSE

Epilepsy is a common serious brain condition characterized by the abnormal electrical activity of neurons. In most cases, epileptic patients respond to antiepileptic drugs. Approximately, one-third of patients prove medically intractable. The ABCB1 gene is a superfamily of ATP-binding cassette (ABC) transporters that encode a drug-transport protein, lead to cells and organs protects and eliminates toxic agents. We performed this meta-analysis to assess the association between G2677T/A in the ABCB1 gene and the risk of drug resistance in epileptic patients.

METHODS

Two online libraries (PubMed and Scopus) were used to identify studies that report the relationship between G2677T/A polymorphism in the MDR1 gene and the risk of antiepileptic drug resistance. The meta-analysis was performed using Review Manager 5.3 software. The pooled odds ratios and 95 % confidence intervals (CIs) were calculated using a random or fixed effects model according to the heterogeneity between studies.

RESULTS

A total of 33 eligible studies were included in this meta-analysis which 4192 patients were drug-resistant and 5079 patients were drug-responsive. As a result, a significant association was observed in overall population for the genetic model GG+GA vs AA (OR with 95 % CI = 0,56 [0.34,0.93]; P = 0.02). The subgroup ethnicity analysis showed a significant decrease in the risk of AEDs resistance in the Caucasian population.

CONCLUSION

In conclusion, our analysis demonstrates that G2677T/A polymorphism in the ABCB1 gene decreases the risk of drug resistance. More studies are needed in the different ethnic groups to clarify the role of polymorphism in AEDs resistance.

Synthesis of genetic association studies on autism spectrum disorders using a genetic model-free approach

BACKGROUND

Autism spectrum disorder (ASD) is a clinically and genetically heterogeneous group of neurodevelopmental disorders. Despite the extensive efforts of scientists, the etiology of ASD is far from completely elucidated. In an effort to enlighten the genetic architecture of ASDs, a meta-analysis of all available genetic association studies (GAS) was conducted.

METHODS

We searched in the Human Genome Epidemiology Navigator (HuGE Navigator) and PubMed for available case-control GAS of ASDs. The threshold for meta-analysis was two studies per genetic variant. The association between genotype distribution and ASDs was examined using the generalized linear odds ratio (ORG). For variants with available allele frequencies, the examined model was the allele contrast.

RESULTS

Overall, 57 candidate genes and 128 polymorphisms were investigated in 159 articles. In total 28 genetic polymorphisms have been shown to be associated with ASDs, that are harbored in 19 genes. Statistically significant results were revealed for the variants of the following genes adenosine deaminase (ADA), bone marrow stromal cell antigen-1 (CD157/BST1), Dopamine receptor D1 (DRD1), engrailed homolog 2 (EN2), met proto-oncogene (MET), methylenetetrahydrofolate reductase (MTHFR), solute carrier family 6 member 4 (SLC6A4), Synaptosomal-associated protein, 25kDa (SNAP-25) and vitamin D receptor (VDR). In the allele contrast model of cases versus healthy controls, significant associations were observed for Adrenoceptor Alpha 1B (ADRA1B), acetyl serotonin O - methyltransferase (ASMT), complement component 4B (C4B), dopamine receptor D3 (DRD3), met proto-oncogene (MET), neuroligin 4, X-linked (NLGN4), neurexin 1 (NRXN1), oxytocin receptor (OXTR), Serine/Threonine-Protein Kinase PFTAIRE-1 (PFTK1), Reelin (RELN) and Ras-like without CAAX 2 (RIT2).

CONCLUSION

These significant findings provide further evidence for genetic factors' implication in ASDs offering new perspectives in means of prevention and prognosis.

Associations between AGT M235T Polymorphism and Cancer: An Updated Meta-Analysis

We assessed the relationship between AGT gene M235T polymorphism and the susceptibility to cancer by performing an updated meta-analysis. This study retrospectively searched related articles in the electronic databases. Afterwards, we determined combined odds ratios (ORs) and related 95% confidence intervals (CIs) by the fixed- or random-effects model. The present meta-analysis enrolled altogether 9 articles. On the whole, the relationship between AGT M235T polymorphism and the cancer risk was not significant among the entire population (TT vs. MM: OR = 1.28, 95%CI = 0.80 − 2.04; TM vs. MM: OR = 0.90, 95%CI = 0.53 − 1.52; recessive model: OR = 1.13, 95%CI = 0.83 − 1.52; dominant model: OR = 0.93, 95%CI = 0.55 − 1.57). Subgroup analysis by ethnicity, cancer type, and study quality for the relationship between the AGT M235T polymorphism and cancer risk showed no significant association. According to findings in the present meta-analysis, AGT M235T polymorphism may not be related to cancer susceptibility.

Protecting against researcher bias in secondary data analysis: challenges and potential solutions

Analysis of secondary data sources (such as cohort studies, survey data, and administrative records) has the potential to provide answers to science and society's most pressing questions. However, researcher biases can lead to questionable research practices in secondary data analysis, which can distort the evidence base. While pre-registration can help to protect against researcher biases, it presents challenges for secondary data analysis. In this article, we describe these challenges and propose novel solutions and alternative approaches. Proposed solutions include approaches to (1) address bias linked to prior knowledge of the data, (2) enable pre-registration of non-hypothesis-driven research, (3) help ensure that pre-registered analyses will be appropriate for the data, and (4) address difficulties arising from reduced analytic flexibility in pre-registration. For each solution, we provide guidance on implementation for researchers and data guardians. The adoption of these practices can help to protect against researcher bias in secondary data analysis, to improve the robustness of research based on existing data.

Optimizing Research Output: How Can Psychological Research Methods Be Improved?

Recent evidence suggests that research practices in psychology and many other disciplines are far less effective than previously assumed, which has led to what has been called a "crisis of confidence" in psychological research (e.g., Pashler & Wagenmakers 2012). In response to the perceived crisis, standard research practices have come under intense scrutiny, and various changes have been suggested to improve them. The burgeoning field of metascience seeks to use standard quantitative data-gathering and modeling techniques to understand the reasons for inefficiency, to assess the likely effects of suggested changes, and ultimately to tell psychologists how to do better science. We review the pros and cons of suggested changes, highlighting the many complex research trade-offs that must be addressed to identify better methods. Expected final online publication date for the Annual Review of Psychology, Volume 73 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

A Scoping Review of the Methodology Used in Studies of Genetic Influences on the Development of Keloid or Hypertrophic Scarring in Adults and Children After Acute Wounding

Significance: Keloid and hypertrophic scarring are common following acute wounds. However, the variability in scarring outcomes between individuals and in particular, the association between genetic factors and scarring, is not well understood. This scoping review aims to summarize the methodology used in studies of genetic influences on the development of keloid or hypertrophic scarring in adults and children after acute wounding. The objectives were to determine the study designs used, the characteristics of participants included, the tools used to assess scarring and the length of follow-up after wounding.

Recent Advances: The review was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Medline, Excerpta Medica Database (EMBASE), Web of Science, Biosciences Information Service (BIOSIS), Prospective Register of Systematic Reviews (PROSPERO), The Human Genetic Epidemiology (HuGE) Navigator (database of genetic association studies), and the genome-wide association study Catalog were searched from January 2008 to April 2020. Cohort studies and case–control studies that examined the association between one or more genetic variations and the development of keloid or hypertrophic scarring were eligible for inclusion. A narrative synthesis that grouped studies by wound type was conducted.

Critical Issues: Nine studies met the inclusion criteria (five in burns, four surgical wounds, and none in other types of acute wounds). Seven assessed hypertrophic scarring, one keloid scarring, and one both scar types. Seven studies used a prospective cohort design. All studies used subjective methods (clinician or patient observation) to assess scarring. There was considerable variation in how scar scales were operationalized.

Future Directions: This review identified a small body of evidence on genetic susceptibility to scarring after acute wounding. Further studies are needed, and in a wide range of populations, including patients with wounds caused by trauma.

A Permissioned Blockchain-Based Clinical Trial Service Platform to Improve Trial Data Transparency

The clinical research faces numerous challenges, from patient enrollment to data privacy concerns and regulatory requirements to spiraling costs. Blockchain technology has the potential to overcome these challenges, thus making clinical trials transparent and enhancing public trust in a fair and open process with all stakeholders because of its distinct features such as data immutability and transparency. This paper proposes a permissioned blockchain platform to ensure clinical data transparency and provides secure clinical trial-related solutions. We explore the core functionalities of blockchain applied to clinical trials and illustrate its general principle concretely. These clinical trial operations are automated using the smart contract, which ensures traceability, prevents a posteriori reconstruction, and securely automates the clinical trial. A web-based user interface is also implemented to visualize the data from the blockchain and ease the interaction with the blockchain network. A proof of concept is implemented on Hyperledger Fabric in the case study of clinical management for multiple clinical trials to demonstrate the designed approach's feasibility. Lastly, the experiment results demonstrate the efficiency and usability of the proposed platform.

Endocannabinoid Gene × Gene Interaction Association to Alcohol Use Disorder in Two Adolescent Cohorts

Genetic markers of the endocannabinoid system have been linked to a variety of addiction-related behaviors that extend beyond cannabis use. In the current study we investigate the relationship between endocannabinoid (eCB) genetic markers and alcohol use disorder (AUD) in European adolescents (14-18 years old) followed in the IMAGEN study (n = 2,051) and explore replication in a cohort of North American adolescents from Canadian Saguenay Youth Study (SYS) (n = 772). Case-control status is represented by a score of more than 7 on the Alcohol Use Disorder Identification Test (AUDIT). First a set-based test method was used to examine if a relationship between the eCB system and AUDIT case/control status exists at the gene level. Using only SNPs that are both independent and significantly associated to case-control status, we perform Fisher's exact test to determine SNP level odds ratios in relation to case-control status and then perform logistic regressions as post-hoc analysis, while considering various covariates. Generalized multifactor dimensionality reduction (GMDR) was used to analyze the most robust SNP×SNP interaction of the five eCB genes with positive AUDIT screen. While no gene-sets were significantly associated to AUDIT scores after correction for multiple tests, in the case/control analysis, 7 SNPs were significantly associated with AUDIT scores of > 7 (p < 0.05; OR<1). Two SNPs remain significant after correction by false discovery rate (FDR): rs9343525 in CNR1 (pcorrected =0.042, OR = 0.73) and rs507961 in MGLL (pcorrected = 0.043, OR = 0.78). Logistic regression showed that both rs9353525 (CNR1) and rs507961 (MGLL) remained significantly associated with positive AUDIT screens (p < 0.01; OR < 1) after correction for multiple covariables and interaction of covariable × SNP. This result was not replicated in the SYS cohort. The GMDR model revealed a significant three-SNP interaction (p = 0.006) involving rs484061 (MGLL), rs4963307 (DAGLA), and rs7766029 (CNR1) predicted case-control status, after correcting for multiple covariables in the IMAGEN sample. A binomial logistic regression of the combination of these three SNPs by phenotype in the SYS cohort showed a result in the same direction as seen in the IMAGEN cohort (BETA = 0.501, p = 0.06). While preliminary, the present study suggests that the eCB system may play a role in the development of AUD in adolescents.

Personality traits and polymorphisms of genes coding neurotransmitter receptors or transporters: review of single gene and genome-wide association studies

BACKGROUND

The most popular tool used for measuring personality traits is the Five-Factor Model (FFM). It includes neuroticism, extraversion, openness, agreeableness and conscientiousness. Many studies indicated the association of genes encoding neurotransmitter receptors/transporters with personality traits. The relationship connecting polymorphic DNA sequences and FFM features has been described in the case of genes encoding receptors of cannabinoid and dopaminergic systems. Moreover, dopaminergic system receives inputs from other neurotransmitters, like GABAergic or serotoninergic systems.

METHODS

We searched PubMed Central (PMC), Science Direct, Scopus, Cochrane Library, Web of Science and EBSCO databases from their inception to November 19, 2020, to identify original studies, as well as peer-reviewed studies examining the FFM and its association with gene polymorphisms affecting the neurotransmitter functions in central nervous system.

RESULTS

Serotonin neurons modulate dopamine function. In gene encoding serotonin transporter protein, SLC6A4, was found polymorphism, which was correlated with openness to experience (in Sweden population), and high scores of neuroticism and low levels of agreeableness (in Caucasian population). The genome-wide association studies (GWASs) found an association of 5q34-q35, 3p24, 3q13 regions with higher scores of neuroticism, extraversion and agreeableness. However, the results for chromosome 3 regions are inconsistent, which was shown in our review paper.

CONCLUSIONS

GWASs on polymorphisms are being continued in order to determine and further understand the relationship between the changes in DNA and personality traits.

MiRNA Polymorphisms and Hepatocellular Carcinoma Susceptibility: A Systematic Review and Network Meta-Analysis

Background

Hepatocellular carcinoma (HCC) is an intractable public health threat worldwide, representing the second leading cause of cancer-related mortality, with limited early detection and therapeutic options. Recent findings have revealed that the susceptibility of HCC is closely related to microRNA (miRNA). We performed this systematic review with a network meta-analysis to investigated four single nucleotide polymorphisms (SNPs) that most regularly reported in miRNAs, exploring their involvement in HCC susceptibility and interaction with hepatitis B virus (HBV).

Methods

Databases were reviewed for related studies published up to May 2019 to identify all studies that compared genotypes of miR-146a rs2910164, miR-149 rs2292832, miR-196a2 rs11614913, and miR-499 rs3746444 with no language and date restrictions. A pairwise meta-analysis was performed to estimate pooled odds ratios and 95% confidence intervals incorporating heterogeneity to assess the relationship between four miRNA polymorphisms and HCC. To further clarify the effect of polymorphisms on HCC, a Bayesian network meta-analysis was conducted to combine the effective sizes of direct and indirect comparisons. Calculations were performed by R version 3.6.1 and STATA 14.0. All steps were performed according to PRISMA guidelines.

Results

A total of 20 studies were enrolled in this network meta-analysis, providing 5,337 hepatocellular carcinoma cases and 6,585 controls. All included studies had an acceptable quality. Pairwise meta-analysis demonstrated that miR-196a2 rs11614913 was significantly associated with the susceptibility of HCC, while the other three SNPs were not found to have a significant association. In the analysis of HCC patients under different HBV infection status, only miR-196a2 revealed correlation of threefold risk. The network results showed no significant difference in the distribution of genotype frequencies except for miR-196a2, which appeared to have the highest superiority index when comparing and ranking four SNPs.

Conclusion

MiR-196a2 rs11614913 was significantly associated with the susceptibility of HCC, especially for HBV- related HCC, and that individuals with TC/CC were more susceptible. No significant association was found in the other three miRNA genes. MiR-196a2 could serve as the best predictor of susceptibility in HCC.

Prevalence of the Factor V Leiden Mutation Arg534Gln in Western Region of Saudi Arabia: Functional Alteration and Association Study With Different Populations

The rare Gln534 (Factor V Leiden; FVL) allele (1:169,519,049 T>C) is associated with an increased risk of venous thrombosis. The purpose of this study was to measure the prevalence of Factor V Leiden mutation in thrombophilia patients with deep vein thrombosis. Also, we investigated the functional and structural characteristics of this mutation p.(Arg534Gln) to be examined the cumulative impact on venous thrombosis risk as well correlated with different populations by Genome Wide Association Studies (GWAS). A total of 108 patients with idiopathic deep vein thrombosis were examined for Factor V Leiden gene mutation. Our preliminary data show that about 10% of patients were detected with the heterozygous and homozygous form of the Factor V Leiden mutation. An association analysis confirmed that the Factor V SNP variant (rs6025) was highly associated (P-value 4.91 x10-^ -39) with an increased risk of venous thrombosis. Also, we found that the recognized SNP was important among HapMap populations. Our results indicated that among the 3 populations (Asian, African, and American) studied, this association was highest in the African population based on the r(2) significant threshold (P-value 5e-190). In addition, this mutation was located at the domain F5/8 type A 2, which can disturb this domain and abolish its function. Because of aspartic acid nearby wild type position as form in the salt bridge due to this discharge will disturb the ionic interaction made by the wild type residue Arg534. This residue was not found to be in contact with other domains of which the function was known. However, contact with other molecules or domains (THPH2: MIM: 188055) were still possible and might be affected by this mutation that may cause thrombophilia due to activated protein C resistance.

Mendelian Randomization in Cardiovascular Research: Establishing Causality When There Are Unmeasured Confounders

Mendelian randomization is an epidemiological approach to making causal inferences using observational data. It makes use of the natural randomization that occurs in the generation of an individual's genetic makeup in a way that is analogous to the study design of a randomized controlled trial and uses instrumental variable analysis where the genetic variant(s) are the instrument (analogous to random allocation to treatment group in an randomized controlled trial). As with any instrumental variable, there are 3 assumptions that must be made about the genetic instrument: (1) it is associated (not necessarily causally) with the exposure (relevance condition); (2) it is associated with the outcome only through the exposure (exclusion restriction condition); and (3) it does not share a common cause with the outcome (ie, no confounders of the genetic instrument and outcome, independence condition). Using the example of type II diabetes and coronary artery disease, we demonstrate how the method may be used to investigate causality and discuss potential benefits and pitfalls. We conclude that although Mendelian randomization studies can usually not establish causality on their own, they may usefully contribute to the evidence base and increase our certainty about the effectiveness (or otherwise) of interventions to reduce cardiovascular disease.

The generalizability crisis

Most theories and hypotheses in psychology are verbal in nature, yet their evaluation overwhelmingly relies on inferential statistical procedures. The validity of the move from qualitative to quantitative analysis depends on the verbal and statistical expressions of a hypothesis being closely aligned - that is, that the two must refer to roughly the same set of hypothetical observations. Here, I argue that many applications of statistical inference in psychology fail to meet this basic condition. Focusing on the most widely used class of model in psychology - the linear mixed model - I explore the consequences of failing to statistically operationalize verbal hypotheses in a way that respects researchers' actual generalization intentions. I demonstrate that although the "random effect" formalism is used pervasively in psychology to model intersubject variability, few researchers accord the same treatment to other variables they clearly intend to generalize over (e.g., stimuli, tasks, or research sites). The under-specification of random effects imposes far stronger constraints on the generalizability of results than most researchers appreciate. Ignoring these constraints can dramatically inflate false-positive rates, and often leads researchers to draw sweeping verbal generalizations that lack a meaningful connection to the statistical quantities they are putatively based on. I argue that failure to take the alignment between verbal and statistical expressions seriously lies at the heart of many of psychology's ongoing problems (e.g., the replication crisis), and conclude with a discussion of several potential avenues for improvement.

Psychosocial adversity and emotional instability: an application of gene–environment interaction models

A central idea in personality theory is that events in childhood have an effect on the development of personality. The present study applied models of gene–environment interaction that demonstrate how environmental conditions may moderate genetic variability in a population and/or the influence of other environmental effects. Results showed that perceived levels of family conflict and maternal indulgence moderated the genetic influences underlying emotional instability, a central feature of borderline personality disorder. The analyses identified a wide variety of environmental influences that moderate the variability in the liability to emotional instability, such as perceived levels of parental bonding, family functioning, and exposure to nonassaultive traumatic events. Copyright © 2005 John Wiley & Sons, Ltd.

Lipid levels linked to symptomatic aortic valve stenosis: evidence from Mendelian randomization?

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Interaction between adverse childhood experiences and polygenic risk in patients with bipolar disorder

The interaction between genes and environment often occurs when they depend on one another. We hypothesized that adverse childhood experiences (ACEs) would interact with genetic predispositions to bipolar disorder (BD), demonstrating earlier age at onset (AAO) and worse clinical outcomes. We aimed to clarify the effects of the interaction between ACEs and genetic susceptibility using polygenic risk score (PRS) on AAO and clinical outcomes. Single nucleotide polymorphisms and clinical data, including ACEs, were obtained from the Bipolar Genomic Study, which contains a large sample of BD participants. A total of 1615 subjects with BD I were obtained and divided into two groups according to the presence or absence of ACEs and an additional four groups based on the number of ACEs (none versus one versus two versus ≥ three types). ACEs was evaluated using the childhood life events scale (CLES). BD-PRS was obtained from the Psychiatric Genomics Consortium, which compared BD patients and healthy controls. The BD-PRS was higher in the group with ACEs than without ACEs at most p-value thresholds. In multivariate linear regression analyses, both groups with more ACEs and higher BD-PRS were independently and interactively associated with an earlier AAO of BD; however, only greater ACEs were associated with worsened clinical outcome. These findings highlight the clinical importance of evaluating ACEs and polygenic risk in research of the etiology of BD.

Severity of self-reported depressive symptoms in a healthy sample is modulated by trait Harm Avoidance, not by 5-HTTLPR polymorphism

BACKGROUND

The length of the serotonin transporter polymorphic region (5-HTTLPR) has been suggested to be associated with risk for developing depression, though with inconsistent evidence. Likewise, the personality trait Harm Avoidance (HA) has been linked to vulnerability for developing depression. However, no study has investigated whether there is an interaction effect between 5-HTTLPR and trait HA on depressive symptoms in healthy individuals.

METHODS

A total of 319 healthy individuals were included in this cross-sectional study. All participants were genotyped for the 5-HTTLPR polymorphism and completed self-reported measures of personality trait HA with the Temperament and Character Inventory (TCI), and of depression with the Major Depression Inventory (MDI). Linear regression analyses were used to test interaction effects between 5-HTTLPR and HA on MDI. Post hoc analyses were further performed to investigate main effects of HA and possible interaction effects between 5-HTTLPR and HA sub-scales on MDI.

RESULTS

No significant interaction effect between 5-HTTLPR and HA on MDI was found. A significant main effect of trait HA on MDI was found, indicating that personality trait HA is a viable vulnerability factor for even sub-clinical depressive symptoms.

CONCLUSION

This study finds a strong significant relationship between HA and MDI. Moreover, the present study supports the line of research indicating that candidate gene-by-interactions does not increase vulnerability for developing depression even at a sub-clinical level.

Find the Needle in the Haystack, Then Find It Again: Replication and Validation in the 'Omics Era

Advancements in high-throughput technologies have made it feasible to study thousands of biological pathways simultaneously for a holistic assessment of health and disease risk via ‘omics platforms. A major challenge in ‘omics research revolves around the reproducibility of findings—a feat that hinges upon balancing false-positive associations with generalizability. Given the foundational role of reproducibility in scientific inference, replication and validation of ‘omics findings are cornerstones of this effort. In this narrative review, we define key terms relevant to replication and validation, present issues surrounding each concept with historical and contemporary examples from genomics (the most well-established and upstream ‘omics), discuss special issues and unique considerations for replication and validation in metabolomics (an emerging field and most downstream ‘omics for which best practices remain yet to be established), and make suggestions for future research leveraging multiple ‘omics datasets.

Genetic Architecture and Molecular Neuropathology of Human Cocaine Addiction

We integrated genomic and bioinformatic analyses, using data from the largest genome-wide association study of cocaine dependence (CD; n = 6546; 82.37% with CD; 57.39% male) and the largest postmortem gene-expression sample of individuals with cocaine use disorder (CUD; n = 36; 51.35% with CUD; 100% male). Our genome-wide analyses identified one novel gene (NDUFB9) associated with the genetic predisposition to CD in African-Americans. The genetic architecture of CD was similar across ancestries. Individual genes associated with CD demonstrated modest overlap across European-Americans and African-Americans, but the genetic liability for CD converged on many similar tissue types (brain, heart, blood, liver) across ancestries. In a separate sample, we investigated the neuronal gene expression associated with CUD by using RNA sequencing of dorsal-lateral prefrontal cortex neurons. We identified 133 genes differentially expressed between CUD case patients and cocaine-free control subjects, including previously implicated candidates for cocaine use/addiction (FOSB, ARC, KCNJ9/GIRK3, NR4A2, JUNB, and MECP2). Differential expression analyses significantly correlated across European-Americans and African-Americans. While genes significantly associated with CD via genome-wide methods were not differentially expressed, two of these genes (NDUFB9 and C1qL2) were part of a robust gene coexpression network associated with CUD involved in neurotransmission (GABA, acetylcholine, serotonin, and dopamine) and drug addiction. We then used a "guilt-by-association" approach to unravel the biological relevance of NDUFB9 and C1qL2 in the context of CD. In sum, our study furthers the understanding of the genetic architecture and molecular neuropathology of human cocaine addiction and provides a framework for translating biological meaning into otherwise obscure genome-wide associations.SIGNIFICANCE STATEMENT Our study further clarifies the genetic and neurobiological contributions to cocaine addiction, provides a rapid approach for generating testable hypotheses for specific candidates identified by genome-wide research, and investigates the cross-ancestral biological contributions to cocaine use disorder/dependence for individuals of European-American and African-American ancestries.

Human In Vitro Models for Assessing the Genomic Basis of Chemotherapy-Induced Cardiovascular Toxicity

Chemotherapy-induced cardiovascular toxicity (CICT) is a well-established risk for cancer survivors and causes diseases such as heart failure, arrhythmia, vascular dysfunction, and atherosclerosis. As our knowledge of the precise cardiovascular risks of each chemotherapy agent has improved, it has become clear that genomics is one of the most influential predictors of which patients will experience cardiovascular toxicity. Most recently, GWAS-led, top-down approaches have identified novel genetic variants and their related genes that are statistically related to CICT. Importantly, the advent of human-induced pluripotent stem cell (hiPSC) models provides a system to experimentally test the effect of these genomic findings in vitro, query the underlying mechanisms, and develop novel strategies to mitigate the cardiovascular toxicity liabilities due to these mechanisms. Here we review the cardiovascular toxicities of chemotherapy drugs, discuss how these can be modeled in vitro, and suggest how these models can be used to validate genetic variants that predispose patients to these effects.

Integrated case-control and somatic-germline interaction analyses of soft-tissue sarcoma

PURPOSE

The contribution of rare genetic variation in the development of soft-tissue sarcoma (STS) remains underexplored. To address this gap, we conducted a whole-exome case-control and somatic-germline interaction study to identify and characterise STS susceptible genes.

METHODS

The study involved 219 STS cases from The Cancer Genome Atlas and 3507 controls. All cases and controls were matched genetically onEuropean ancestry based on the 1000 Genomes project. Cross-platform technological stratification was performed with XPAT and gene-based association tests with VAAST 2.

RESULTS

NF1 exhibited the strongest genome-wide signal across the six subtypes, with p=1×10^-5. We also observed nominally significant association signals for three additional genes of interest, TP53 (p=0.0025), RB1 (p=0.0281), and MSH2 (p=0.0085). BAG1, which has not previously been implicated in STS, exhibited the strongest genome-wide signal after NF1, with p=6×10^-5. The association signals for NF1 and MSH2 were driven primarily by truncating variants, with ORs of 39 (95% CI: 7.1 to 220) for NF1 and 33 (95% CI: 2.4 to 460) for MSH2. In contrast, the association signals for RB1 and BAG1 were driven primarily by predicted damaging missense variants, with estimated ORs of 12 (95% CI: 2.4 to 59) for RB1 and 20 (95% CI: 1.4 to 300) for BAG1.

CONCLUSIONS

Our results confirm that pathogenic variants in NF1, RB1 and TP53 confer large increases in the risk of developing multiple STS subtypes, provide support for the role of MSH2 in STS susceptibility and identify BAG1 as a novel candidate STS risk gene.

hiPSCs in cardio-oncology: deciphering the genomics

The genomic predisposition to oncology-drug-induced cardiovascular toxicity has been postulated for many decades. Only recently has it become possible to experimentally validate this hypothesis via the use of patient-specific human-induced pluripotent stem cells (hiPSCs) and suitably powered genome-wide association studies (GWAS). Identifying the individual single nucleotide polymorphisms (SNPs) responsible for the susceptibility to toxicity from a specific drug is a daunting task as this precludes the use of one of the most powerful tools in genomics: comparing phenotypes to close relatives, as these are highly unlikely to have been treated with the same drug. Great strides have been made through the use of candidate gene association studies (CGAS) and increasingly large GWAS studies, as well as in vivo whole-organism studies to further our mechanistic understanding of this toxicity. The hiPSC model is a powerful technology to build on this work and identify and validate causal variants in mechanistic pathways through directed genomic editing such as CRISPR. The causative variants identified through these studies can then be implemented clinically to identify those likely to experience cardiovascular toxicity and guide treatment options. Additionally, targets identified through hiPSC studies can inform future drug development. Through careful phenotypic characterization, identification of genomic variants that contribute to gene function and expression, and genomic editing to verify mechanistic pathways, hiPSC technology is a critical tool for drug discovery and the realization of precision medicine in cardio-oncology.

Genetic association between −93A/G polymorphism in the Fyn kinase gene and alcohol dependence in Spanish men

Background

Fyn tyrosine kinase is a member of the Scr family that phosphorylates the NR2A and NR2B subunits of the NMDA receptors reducing the inhibitory effects of ethanol and therefore may regulate the individual sensitivity to ethanol.

Objectives

To investigate whether there is any relationship between the polymorphism at position −93 of the Fyn kinase gene and the susceptibility to develop alcoholism.

Methods

We studied the distribution of genotypes and alleles of the polymorphism −93A/G (137346 T/C) in the 5′ UTR region of the fyn gene in 207 male heavy drinkers (119 with alcohol dependence and 88 with alcohol abuse) and 100 control subjects from Castilla y León (Spain).

Results

The frequency of G allele carriers was higher in alcohol dependents than in alcohol abusers (47.9% vs 30.6%; p = 0.015; OR = 2.077; 95% CI 1.165–3.704).

Conclusion

Our results show that the −93G allele of Fyn kinase gene is associated with higher risk to develop alcohol dependence in Spanish men.

The Association of Aquaporin-1 Gene with Marathon Running Performance Level: a Confirmatory Study Conducted in Male Hispanic Marathon Runners

Background

Replication studies are essential for identifying credible associations between alleles and phenotypes. Validation of genotype-phenotype associations in the sports and exercise field is rare. An initial genetic association study suggested that rs1049305 (C > G) in the 3′ untranslated region (3′UTR) of the aquaporin-1 (AQP1) gene was associated with marathon running (MR) performance level in Hispanic males. To validate this finding, we conducted a replication analysis in an independent case-control sample of Hispanic male marathon runners (n = 1430; cases n = 713 and controls n = 717). A meta-analysis was utilized to test the extent of the association between the initial results and the present report. It also provided to test the heterogeneity (variation) between the two studies.

Results

The replication study showed a statistically significant (p ≤ 0.05) association between rs1049305 (C > G) of the AQP1 gene and MR performance level. Association test results using a fixed effect model for the combined, original study and the present report, yielded an odds ratio = 1.28, 95% confidence interval = 1.13–1.45, p = 0.0001. The extent of the measures of heterogeneity was Tau-squared = 0, H statistic = 1, I² statistic = 0, and Cochran’s Q test (Q = 0.29; p value 0.59), indicated the variation between studies were due to chance and not to differences in heterogeneity between the two studies. Within the limitations of the present replication, contrast of two studies and its effects on meta-analysis, the findings were robust.

Conclusion

This study successfully replicated the results of Martínez et al. (Med Sportiva 13:251-5, 2009). The meta-analysis provided further epidemiological credibility for the hypothesis of association between the DNA rs1049305 (C > G) variation in the 3′UTR of the AQP1 gene and MR running performance level in Hispanics male marathon runners. It is not precluded that a linked DNA structure in the surrounding molecular neighborhood could be of influence by been part of the overly complex phenotype of MR performance level.

Mendelian Randomization analysis of the causal effect of adiposity on hospital costs

Estimates of the marginal effect of measures of adiposity such as body mass index (BMI) on healthcare costs are important for the formulation and evaluation of policies targeting adverse weight profiles. Most estimates of this association are affected by endogeneity bias. We use a novel identification strategy exploiting Mendelian Randomization - random germline genetic variation modelled using instrumental variables - to identify the causal effect of BMI on inpatient hospital costs. Using data on over 300,000 individuals, the effect size per person per marginal unit of BMI per year varied according to specification, including £21.22 (95% confidence interval (CI): £14.35-£28.07) for conventional inverse variance weighted models to £18.85 (95% CI: £9.05-£28.65) for penalized weighted median models. Effect sizes from Mendelian Randomization models were larger in most cases than non-instrumental variable multivariable adjusted estimates (£13.47, 95% CI: £12.51-£14.43). There was little evidence of non-linearity. Within-family estimates, intended to address dynastic biases, were imprecise.

Mendel's laws, Mendelian randomization and causal inference in observational data: substantive and nomenclatural issues

We respond to criticisms of Mendelian randomization (MR) by Mukamal, Stampfer and Rimm (MSR). MSR consider that MR is receiving too much attention and should be renamed. We explain how MR links to Mendel's laws, the origin of the name and our lack of concern regarding nomenclature. We address MSR's substantive points regarding MR of alcohol and cardiovascular disease, an issue on which they dispute the MR findings. We demonstrate that their strictures with respect to population stratification, confounding, weak instrument bias, pleiotropy and confounding have been addressed, and summarise how the field has advanced in relation to the issues they raise. We agree with MSR that "the hard problem of conducting high-quality, reproducible epidemiology" should be addressed by epidemiologists. However we see more evidence of confrontation of this issue within MR, as opposed to conventional observational epidemiology, within which the same methods that have demonstrably failed in the past are simply rolled out into new areas, leaving their previous failures unexamined.

A Systematic Review and Meta-Analysis for the Association of Gene Polymorphisms in RAN with Cancer Risk

As an important component of miRNA processing genes, RAN gene encodes the ras-related nuclear protein, which is a unique member of the Ras superfamily of GTPases. The mutations in RAN gene are very likely to play a critical role in pathology-related changes to miRNA transport and expression and thus participate in tumor genesis and development. Currently, accumulating studies have explored the association between RAN SNPs and cancer risk. However, the results are conflicting. In the present study, we performed a systematic review for the association of RAN SNPs with overall cancer risk. Meanwhile, a meta-analysis was conducted based on available data, aiming at clarifying the association between RAN SNPs and cancer susceptibility. After literature search and data extraction, 17 studies containing four RAN SNPs were involved in the systematic review. And 12 studies with two highly studied SNPs (RAN rs14035 C>T and rs3803012 A>G) were included in the final meta-analysis, consisting of 7662 cases and 9807 controls. The results showed that the rs14035 polymorphism was linked to a decreased cancer risk in overall subjects and hospital-based (HB) subgroup, while the rs3803012 polymorphism conferred to an increased cancer risk in overall subjects and population-based (PB) subgroup. Our findings suggested that the two SNPs had the potential to be predictive biomarkers for cancer risk. The study would provide novel clues for the identification of miRNA-related genetic biomarkers applied to predicting cancer susceptibility.

Genetic Associations with Aging Muscle: A Systematic Review

The age-related decline in skeletal muscle mass, strength and function known as 'sarcopenia' is associated with multiple adverse health outcomes, including cardiovascular disease, stroke, functional disability and mortality. While skeletal muscle properties are known to be highly heritable, evidence regarding the specific genes underpinning this heritability is currently inconclusive. This review aimed to identify genetic variants known to be associated with muscle phenotypes relevant to sarcopenia. PubMed, Embase and Web of Science were systematically searched (from January 2004 to March 2019) using pre-defined search terms such as "aging", "sarcopenia", "skeletal muscle", "muscle strength" and "genetic association". Candidate gene association studies and genome wide association studies that examined the genetic association with muscle phenotypes in non-institutionalised adults aged ≥50 years were included. Fifty-four studies were included in the final analysis. Twenty-six genes and 88 DNA polymorphisms were analysed across the 54 studies. The ACTN3, ACE and VDR genes were the most frequently studied, although the IGF1/IGFBP3, TNFα, APOE, CNTF/R and UCP2/3 genes were also shown to be significantly associated with muscle phenotypes in two or more studies. Ten DNA polymorphisms (rs154410, rs2228570, rs1800169, rs3093059, rs1800629, rs1815739, rs1799752, rs7412, rs429358 and 192 bp allele) were significantly associated with muscle phenotypes in two or more studies. Through the identification of key gene variants, this review furthers the elucidation of genetic associations with muscle phenotypes associated with sarcopenia.

Association Analysis of 14 Candidate Gene Polymorphism with Depression and Stress among Gestational Diabetes Mellitus

The association of candidate genes and psychological symptoms of depression, anxiety, and stress among women with gestational diabetes mellitus (GDM) in Malaysia was determined in this study, followed by the determination of their odds of getting psychological symptoms, adjusted for socio-demographical background, maternal, and clinical characteristics. Single nucleotide polymorphisms (SNPs) recorded a significant association between SNP of EPHX2 (rs17466684) and depression symptoms (AOR = 7.854, 95% CI = 1.330–46.360) and stress symptoms (AOR = 7.664, 95% CI = 1.579–37.197). Associations were also observed between stress symptoms and SNP of OXTR (rs53576) and (AOR = 2.981, 95% CI = 1.058–8.402) and SNP of NRG1 (rs2919375) (AOR = 9.894, 95% CI = 1.159–84.427). The SNP of EPHX2 (rs17466684) gene polymorphism is associated with depression symptoms among Malaysian women with GDM. SNP of EPHX2 (rs17466684), OXTR (rs53576) and NRG1 (rs2919375) are also associated with stress symptoms.

Genetics of rheumatic fever and rheumatic heart disease

Rheumatic heart disease (RHD) is a complication of group A streptococcal infection that results from a complex interaction between the genetic make-up of the host, the infection itself and several other environmental factors, largely reflecting poverty. RHD is estimated to affect 33.4 million people and results in 10.5 million disability-adjusted life-years lost globally. The disease has long been considered heritable but still little is known about the host genetic factors that increase or reduce the risk of developing RHD. In the 1980s and 1990s, several reports linked the disease to the human leukocyte antigen (HLA) locus on chromosome 6, followed in the 2000s by reports implicating additional candidate regions elsewhere in the genome. Subsequently, the search for susceptibility loci has been reinvigorated by the use of genome-wide association studies (GWAS) through which millions of variants can be tested for association in thousands of individuals. Early findings implicate not only HLA, particularly the HLA-DQA1 to HLA-DQB1 region, but also the immunoglobulin heavy chain locus, including the IGHV4-61 gene segment, on chromosome 14. In this Review, we assess the emerging role of GWAS in assessing RHD, outlining both the advantages and disadvantages of this approach. We also highlight the potential use of large-scale, publicly available data and the value of international collaboration to facilitate comprehensive studies that produce findings that have implications for clinical practice.