Adjustment for SNPs instead of demographic and clinical covariates in GWAS

Genome-wide association study (GWAS) is fundamentally designed to detect disease-causing genes. To reduce spurious associations or improve statistical power, about 80% of GWASs arbitrarily adjusted for demographic and clinical covariates. However, adjustment strategies in GWASs have not achieved consistent conclusions. Given the initial aim of GWAS that is to identify the causal association between a specific causal single-nucleotide polymorphism (SNP) and disease trait, we summarized all complex relationships of the target SNP, covariate and disease trait into 15 causal diagrams according to various roles of the covariate. Following each causal diagram, we conducted a series of theoretical justifications and statistical simulations. Our results demonstrate that it is unadvisable to adjust for any demographic or clinical covariates. We illustrate our point by applying GWASs for body mass index (BMI) and breast cancer, including adjusting and non-adjusting for age and smoking status. Genetic effects and P values might vary across different strategies. Instead, adjustments for SNPs (G') should be strongly recommended when G' are in linkage disequilibrium with the target SNP, and correlated with disease trait conditional on the target SNP. Specifically, adjustment for such G' can block all the confounding paths between the target SNP and disease trait, and avoid over-adjusting for colliders or intermediaries.

Consequence of adjustments for demographic or clinical covariates and a recommended solution in genome-wide association studies

Genome-wide association study (GWAS) is fundamentally designed to detect disease-causing genes. To reduce spurious associations or improve statistical power, about 80% of GWASs arbitrarily adjusted for demographic or clinical covariates. However, adjustment strategies in GWASs have not achieved consistent conclusions. Given the initial aim of GWAS that is to identify the causal association between a specific causal single-nucleotide polymorphism (SNP) and disease trait, we summarized all complex relationships of the target SNP, covariate and disease trait into 15 causal diagrams according to various roles of the covariate. Following each causal diagram, we conducted a series of theoretical justifications and statistical simulations. Our results demonstrate that it is unadvisable to adjust for any demographic or clinical covariates. We illustrate our point by applying GWASs for body mass index (BMI) and breast cancer, including adjusting and non-adjusting for age and smoking status. Genetic effects and P values might vary across different strategies. Instead, adjustments for SNPs (G') should be strongly recommended when G' are in linkage disequilibrium with the target SNP, and correlated with disease trait conditional on the target SNP. Specifically, adjustment for such G' can block all the confounding paths between the target SNP and disease trait, and avoid over-adjusting for colliders or intermediaries.

The “GEnomics of Musculo Skeletal Traits TranslatiOnal NEtwork”: Origins, Rationale, Organization, and Prospects

Musculoskeletal research has been enriched in the past ten years with a great wealth of new discoveries arising from genome wide association studies (GWAS). In addition to the novel factors identified by GWAS, the advent of whole-genome and whole-exome sequencing efforts in family based studies has also identified new genes and pathways. However, the function and the mechanisms by which such genes influence clinical traits remain largely unknown. There is imperative need to bring multidisciplinary expertise together that will allow translating these genomic discoveries into useful clinical applications with the potential of improving patient care. Therefore “GEnomics of MusculoSkeletal traits TranslatiOnal NEtwork” (GEMSTONE) aims to set the ground for the: 1) functional characterization of discovered genes and pathways; 2) understanding of the correspondence between molecular and clinical assessments; and 3) implementation of novel methodological approaches. This research network is funded by The European Cooperation in Science and Technology (COST). GEMSTONE includes six working groups (WG), each with specific objectives: WG1-Study populations and expertise groups: creating, maintaining and updating an inventory of experts and resources (studies and datasets) participating in the network, helping to assemble focus groups defined by phenotype, functional and methodological expertise. WG2-Phenotyping: describe ways to decompose the phenotypes of the different functional studies into meaningful components that will aid the interpretation of identified biological pathways. WG3 Monogenic conditions - human KO models: makes an inventory of genes underlying musculoskeletal monogenic conditions that aids the assignment of genes to GWAS signals and prioritizing GWAS genes as candidates responsible for monogenic presentations, through biological plausibility. WG4 Functional investigations: creating a roadmap of genes and pathways to be prioritized for functional assessment in cell and organism models of the musculoskeletal system. WG5 Bioinformatics seeks the integration of the knowledge derived from the distinct efforts, with particular emphasis on systems biology and artificial intelligence applications. Finally, WG6 Translational outreach: makes a synopsis of the knowledge derived from the distinct efforts, allowing to prioritize factors within biological pathways, use refined disease trait definitions and/or improve study design of future investigations in a potential therapeutic context (e.g. clinical trials) for musculoskeletal diseases.

Multiplex Real-Time PCR for genotyping Glutathione S-Transferase deletion polymorphisms v1

Glutathione S-transferases (GSTs) are enzymes that act in the conjugation of reactive metabolites to the reduced glutathione. The GSTM1 and GSTT1 deletion polymorphisms promote a detriment in the metabolic detoxification process of xenobiotics, due to present a non-functional null allele, causing oxidative stress, may be related to the pathophysiology of various diseases. Genetic association case-control studies usually determine whether a statistical association exists between the disease trait and the genetic marker, such as GST deletion polymorphism. Therefore, techniques to genotyping these polymorphisms through multiplex PCR are highly desired and of wider interest. This method allows for the detection of genotypes for genetic association studies in molecular pathology and it is more cost-effective than hybridization probes.

COVID-19 in individuals with sickle cell disease/trait compared with other Black individuals

In the United States, COVID-19 has disproportionately affected Black persons. Sickle cell disease (SCD) and sickle cell trait (SCT) are genetic conditions that occur predominantly among Black individuals. It is unknown if individuals with SCD/SCT are at higher risk of severe COVID-19 illness compared with Black individuals who do not have SCD/SCT. The objective of our study was to compare COVID-19 outcomes, including the disease manifestations, hospitalization, and death, among individuals with SCD/SCT vs Black individuals who do not have SCD/SCT. We leveraged electronic health record data from a multisite research network to identify Black patients with COVID-19 who have SCD/SCT and those who do not have SCD/SCT. During the study period of 20 January 2020 to 20 September 2020, there were 312 patients with COVID-19 and SCD and 449 patients with COVID-19 and SCT. There were 45 517 Black persons who were diagnosed with COVID-19 but who did not have SCD/SCT. After 1:1 propensity score matching (based on age, sex, and other preexisting comorbidities), patients with COVID-19 and SCD remained at a higher risk of hospitalization (relative risk [RR], 2.0; 95% CI, 1.5-2.7) and development of pneumonia (RR, 2.4; 95% CI, 1.6-3.4) and pain (RR, 3.4; 95% CI, 2.5-4.8) compared with Black persons without SCD/SCT. The case fatality rates for those with SCD compared with Black persons without SCD/SCT were not significantly different. There also were no significant differences in COVID-19 outcomes between individuals with SCT and Black persons without SCD/SCT within the matched cohorts.

A reference catalog of DNA palindromes in the human genome and their variations in 1000 Genomes

A palindrome in DNA is like a palindrome in language, but when read backwards, it is a complement of the forward sequence; effectively, the two halves of a sequence complement each other from its midpoint like in a double strand of DNA. Palindromes are distributed throughout the human genome and play significant roles in gene expression and regulation. Palindromic mutations are linked to many human diseases, such as neuronal disorders, mental retardation, and various cancers. In this work, we computed and analyzed the palindromic sequences in the human genome and studied their conservation in personal genomes using 1000 Genomes data. We found that ~30% of the palindromes exhibit variation, some of which are caused by rare variants. The analysis of disease/trait-associated single-nucleotide polymorphisms in palindromic regions showed that disease-associated risk variants are 14 times more likely to be present in palindromic regions than in other regions. The catalog of palindromes in the reference genome and 1000 Genomes is being made available here with details on their variations in each individual genome to serve as a resource for future and retrospective whole-genome studies identifying statistically significant palindrome variations associated with diseases or traits and their roles in disease mechanisms.

Experimental evidence of warming-induced disease emergence and its prediction by a trait-based mechanistic model

Predicting the effects of seasonality and climate change on the emergence and spread of infectious disease remains difficult, in part because of poorly understood connections between warming and the mechanisms driving disease. Trait-based mechanistic models combined with thermal performance curves arising from the metabolic theory of ecology (MTE) have been highlighted as a promising approach going forward; however, this framework has not been tested under controlled experimental conditions that isolate the role of gradual temporal warming on disease dynamics and emergence. Here, we provide experimental evidence that a slowly warming host–parasite system can be pushed through a critical transition into an epidemic state. We then show that a trait-based mechanistic model with MTE functional forms can predict the critical temperature for disease emergence, subsequent disease dynamics through time and final infection prevalence in an experimentally warmed system of Daphnia and a microsporidian parasite. Our results serve as a proof of principle that trait-based mechanistic models using MTE subfunctions can predict warming-induced disease emergence in data-rich systems—a critical step towards generalizing the approach to other systems.

Intricacies of aetiology in intrafamilial degenerative disease

The genetic underpinnings of late-onset degenerative disease have typically been determined by screening families for the segregation of genetic variants with the disease trait in affected, but not unaffected, individuals. However, instances of intrafamilial etiological heterogeneity, where pathogenic variants in a culprit gene are not shared among all affected family members, continue to emerge and confound gene-discovery and genetic counselling efforts. Discordant intrafamilial cases lacking a mutation shared by other affected family members are described as disease phenocopies. This description often results in an over-simplified acceptance of an environmental cause of disease in the phenocopy cases, while the role of intrafamilial genetic heterogeneity, shared de novo mutations or epigenetic aberrations in such families is often ignored. On a related note, it is now evident that the same disease-associated variant can be present in individuals exhibiting clinically distinct phenotypes, thereby genetically uniting seemingly unrelated syndromes to form a spectrum of disease. Herein, we discuss the intricacies of determining complex degenerative disease aetiology and suggest alternative mechanisms of disease transmission that may account for the apparent missing heritability of disease.

Genetic resistance and specificity in sister taxa of Daphnia: insights from the range of host susceptibilities

Background Host genetic diversity can affect various aspects of host-parasite interactions, including individual-level effects on parasite infectivity, production of transmission stages and virulence, as well as population-level effects that reduce disease spread and prevalence, and buffer against widespread epidemics. However, a key aspect of this diversity, the genetic variation in host susceptibility, has often been neglected in interpreting empirical data and in theoretical studies. Daphnia similis naturally coexists with its competitor Daphnia magna and is more resistant to the endoparasitic microsporidium Hamiltosporidium tvaerminnensis, as suggested by a previous survey of waterbodies, which detected this parasite in D. magna, but not in D. similis. However, under laboratory conditions D. similis was sometimes found to be susceptible. We therefore asked if there is genetic variation for disease trait expression, and if the genetic variation in disease traits in D. similis is different from that of D. magna. Methods We exposed ten clones of D. similis and ten clones of D. magna to three isolates of H. tvaerminnensis, and measured infection rates, parasite-induced host mortality and parasite spore production. Results The two Daphnia species differ in the range and variation of their susceptibilities. The parasite produced on average two-fold more spores when growing in D. magna clones than in D. similis clones. Conclusions We confirm that D. similis is indeed much more resistant than D. magna and suggest that this could create a dilution effect in habitats where both species coexist.