Replicability and Prediction: Lessons and Challenges from GWAS

Exploring Drugs and Vaccines Associated with Altered Risks and Severity of COVID-19: A UK Biobank Cohort Study of All ATC Level-4 Drug Categories Reveals Repositioning Opportunities

Effective therapies for COVID-19 are still lacking, and drug repositioning is a promising approach to address this problem. Here, we adopted a medical informatics approach to repositioning. We leveraged a large prospective cohort, the UK-Biobank (UKBB, N ~ 397,000), and studied associations of prior use of all level-4 ATC drug categories (N = 819, including vaccines) with COVID-19 diagnosis and severity. Effects of drugs on the risk of infection, disease severity, and mortality were investigated separately. Logistic regression was conducted, controlling for main confounders. We observed strong and highly consistent protective associations with statins. Many top-listed protective drugs were also cardiovascular medications, such as angiotensin-converting enzyme inhibitors (ACEI), angiotensin receptor blockers (ARB), calcium channel blocker (CCB), and beta-blockers. Some other drugs showing protective associations included biguanides (metformin), estrogens, thyroid hormones, proton pump inhibitors, and testosterone-5-alpha reductase inhibitors, among others. We also observed protective associations by influenza, pneumococcal, and several other vaccines. Subgroup and interaction analyses were also conducted, which revealed differences in protective effects in various subgroups. For example, protective effects of flu/pneumococcal vaccines were weaker in obese individuals, while protection by statins was stronger in cardiovascular patients. To conclude, our analysis revealed many drug repositioning candidates, for example several cardiovascular medications. Further studies are required for validation.

Revealing modifier variations characterizations for elucidating the genetic basis of human phenotypic variations

Epistatic interactions complicate the identification of variants involved in phenotypic effect. In-depth knowledge in modifiers and in pathogenic variants would benefit the mechanistic studies on the genetic basis of complex traits. We systematically compared the modifier variants which have evidence of modifier effect with the pathogenic variants from multiple angles. Our study found that genomic loci of modifier variations differ from pathogenic loci in many aspects, such as population genetics statistics, epigenetic features, evolutionary characteristics and functional properties of the variations. Genes containing modifier variation(s) exhibit higher probability of being haploinsufficient and higher probability of recessive disease causation, and they are relatively more important in network communication. Furthermore, we reinforced that co-expression analysis is an effective methodology to predict functional associations between modifier genes and their potential target genes. In many aspects, we detected statistically significant differences between modifier variants/genes and pathogenic variants/genes, and investigated relationships between modifiers and their potential targets. Our results offer some actionable insights that may provide appropriate guidelines to clinical genetics and researchers to elucidate the molecular mechanism underlying the human phenotypic variation.

Protective association of the ε2/ε3 heterozygote with Alzheimer's disease is strengthened by TOMM40-APOE variants in men

INTRODUCTION

Despite advances, understanding the protective role of the apolipoprotein E (APOE) ε2 allele in Alzheimer's disease (AD) remains elusive.

METHODS

We examined associations of variants comprised of the TOMM40 rs8106922 and APOE rs405509, rs440446, and ε2-encoding rs7412 polymorphisms with AD in a sample of 2862 AD-affected and 169,516 AD-unaffected non-carriers of the ε4 allele.

RESULTS

Association of the ε2/ε3 heterozygote of men with AD is 38% (P = 1.65 × 10^-2 ) more beneficial when it is accompanied by rs8106922 major allele homozygote and rs405509 and rs440446 heterozygotes than by rs8106922 heterozygote and rs405509 and rs440446 major allele homozygotes. No difference in the beneficial associations of these two most common ε2/ε3-bearing variants with AD was identified in women. The role of ε2/ε3 heterozygote may be affected by different immunomodulation functions of rs8106922, rs405509, and rs440446 variants in a sex-specific manner.

DISCUSSION

Combination of TOMM40 and APOE variants defines a more homogeneous AD-protective ε2/ε3-bearing profile in men.

DeepCOMBI: explainable artificial intelligence for the analysis and discovery in genome-wide association studies

Deep learning has revolutionized data science in many fields by greatly improving prediction performances in comparison to conventional approaches. Recently, explainable artificial intelligence has emerged as an area of research that goes beyond pure prediction improvement by extracting knowledge from deep learning methodologies through the interpretation of their results. We investigate such explanations to explore the genetic architectures of phenotypes in genome-wide association studies. Instead of testing each position in the genome individually, the novel three-step algorithm, called DeepCOMBI, first trains a neural network for the classification of subjects into their respective phenotypes. Second, it explains the classifiers’ decisions by applying layer-wise relevance propagation as one example from the pool of explanation techniques. The resulting importance scores are eventually used to determine a subset of the most relevant locations for multiple hypothesis testing in the third step. The performance of DeepCOMBI in terms of power and precision is investigated on generated datasets and a 2007 study. Verification of the latter is achieved by validating all findings with independent studies published up until 2020. DeepCOMBI is shown to outperform ordinary raw P-value thresholding and other baseline methods. Two novel disease associations (rs10889923 for hypertension, rs4769283 for type 1 diabetes) were identified.

Accurate, ultra-low coverage genome reconstruction and association studies in Hybrid Swarm mapping populations

Genetic association studies seek to uncover the link between genotype and phenotype, and often utilize inbred reference panels as a replicable source of genetic variation. However, inbred reference panels can differ substantially from wild populations in their genotypic distribution, patterns of linkage-disequilibrium, and nucleotide diversity. As a result, associations discovered using inbred reference panels may not reflect the genetic basis of phenotypic variation in natural populations. To address this problem, we evaluated a mapping population design where dozens to hundreds of inbred lines are outbred for few generations, which we call the Hybrid Swarm. The Hybrid Swarm approach has likely remained underutilized relative to pre-sequenced inbred lines due to the costs of genome-wide genotyping. To reduce sequencing costs and make the Hybrid Swarm approach feasible, we developed a computational pipeline that reconstructs accurate whole genomes from ultra-low-coverage (0.05X) sequence data in Hybrid Swarm populations derived from ancestors with phased haplotypes. We evaluate reconstructions using genetic variation from the Drosophila Genetic Reference Panel as well as variation from neutral simulations. We compared the power and precision of Genome-Wide Association Studies using the Hybrid Swarm, inbred lines, recombinant inbred lines (RILs), and highly outbred populations across a range of allele frequencies, effect sizes, and genetic architectures. Our simulations show that these different mapping panels vary in their power and precision, largely depending on the architecture of the trait. The Hybrid Swam and RILs outperform inbred lines for quantitative traits, but not for monogenic ones. Taken together, our results demonstrate the feasibility of the Hybrid Swarm as a cost-effective method of fine-scale genetic mapping.

Life in Deserts: The Genetic Basis of Mammalian Desert Adaptation

Deserts are among the harshest environments on Earth. The multiple ages of different deserts and their global distribution provide a unique opportunity to study repeated adaptation at different timescales. Here, we summarize recent genomic research on the genetic mechanisms underlying desert adaptations in mammals. Several studies on different desert mammals show large overlap in functional classes of genes and pathways, consistent with the complexity and variety of phenotypes associated with desert adaptation to water and food scarcity and extreme temperatures. However, studies of desert adaptation are also challenged by a lack of accurate genotype-phenotype-environment maps. We encourage development of systems that facilitate functional analyses, but also acknowledge the need for more studies on a wider variety of desert mammals.

Quantifying genetic heterogeneity between continental populations for human height and body mass index

Genome-wide association studies (GWAS) in samples of European ancestry have identified thousands of genetic variants associated with complex traits in humans. However, it remains largely unclear whether these associations can be used in non-European populations. Here, we seek to quantify the proportion of genetic variation for a complex trait shared between continental populations. We estimated the between-population correlation of genetic effects at all SNPs (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$r_{g}$$\end{document}rg) or genome-wide significant SNPs (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$r_{{g\left( {GWS} \right)}}$$\end{document}rgGWS) for height and body mass index (BMI) in samples of European (EUR; \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$n = 49,839$$\end{document}n=49,839) and African (AFR; \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$n = 17,426$$\end{document}n=17,426) ancestry. The \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat{r}_{g}$$\end{document}r^g between EUR and AFR was 0.75 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{s}}.{\text{e}}. = 0.035$$\end{document}s.e.=0.035) for height and 0.68 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{s}}.{\text{e}}. = 0.062$$\end{document}s.e.=0.062) for BMI, and the corresponding \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat{r}_{{g\left( {GWS} \right)}}$$\end{document}r^gGWS was 0.82 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{s}}.{\text{e}}. = 0.030$$\end{document}s.e.=0.030) for height and 0.87 (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\text{s}}.{\text{e}}. = 0.064$$\end{document}s.e.=0.064) for BMI, suggesting that a large proportion of GWAS findings discovered in Europeans are likely applicable to non-Europeans for height and BMI. There was no evidence that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\hat{r}_{g}$$\end{document}r^g differs in SNP groups with different levels of between-population difference in allele frequency or linkage disequilibrium, which, however, can be due to the lack of power.

Using functional genomics to advance the understanding of psoriatic arthritis

Psoriatic arthritis (PsA) is a complex disease where susceptibility is determined by genetic and environmental risk factors. Clinically, PsA involves inflammation of the joints and the skin, and, if left untreated, results in irreversible joint damage. There is currently no cure and the few treatments available to alleviate symptoms do not work in all patients. Over the past decade, genome-wide association studies (GWAS) have uncovered a large number of disease-associated loci but translating these findings into functional mechanisms and novel targets for therapeutic use is not straightforward. Most variants have been predicted to affect primarily long-range regulatory regions such as enhancers. There is now compelling evidence to support the use of chromatin conformation analysis methods to discover novel genes that can be affected by disease-associated variants. Here, we will review the studies published in the field that have given us a novel understanding of gene regulation in the context of functional genomics and how this relates to the study of PsA and its underlying disease mechanism.

Genome diversity in Ukraine

Background

The main goal of this collaborative effort is to provide genome-wide data for the previously underrepresented population in Eastern Europe, and to provide cross-validation of the data from genome sequences and genotypes of the same individuals acquired by different technologies. We collected 97 genome-grade DNA samples from consented individuals representing major regions of Ukraine that were consented for public data release. BGISEQ-500 sequence data and genotypes by an Illumina GWAS chip were cross-validated on multiple samples and additionally referenced to 1 sample that has been resequenced by Illumina NovaSeq6000 S4 at high coverage.

Results

The genome data have been searched for genomic variation represented in this population, and a number of variants have been reported: large structural variants, indels, copy number variations, single-nucletide polymorphisms, and microsatellites. To our knowledge, this study provides the largest to-date survey of genetic variation in Ukraine, creating a public reference resource aiming to provide data for medical research in a large understudied population.

Conclusions

Our results indicate that the genetic diversity of the Ukrainian population is uniquely shaped by evolutionary and demographic forces and cannot be ignored in future genetic and biomedical studies. These data will contribute a wealth of new information bringing forth a wealth of novel, endemic and medically related alleles.

Interpretation of psychiatric genome-wide association studies with multispecies heterogeneous functional genomic data integration

Genome-wide association studies and other discovery genetics methods provide a means to identify previously unknown biological mechanisms underlying behavioral disorders that may point to new therapeutic avenues, augment diagnostic tools, and yield a deeper understanding of the biology of psychiatric conditions. Recent advances in psychiatric genetics have been made possible through large-scale collaborative efforts. These studies have begun to unearth many novel genetic variants associated with psychiatric disorders and behavioral traits in human populations. Significant challenges remain in characterizing the resulting disease-associated genetic variants and prioritizing functional follow-up to make them useful for mechanistic understanding and development of therapeutics. Model organism research has generated extensive genomic data that can provide insight into the neurobiological mechanisms of variant action, but a cohesive effort must be made to establish which aspects of the biological modulation of behavioral traits are evolutionarily conserved across species. Scalable computing, new data integration strategies, and advanced analysis methods outlined in this review provide a framework to efficiently harness model organism data in support of clinically relevant psychiatric phenotypes.

Renin-Angiotensin System and Alzheimer's Disease Pathophysiology: From the Potential Interactions to Therapeutic Perspectives

New roles of the Renin-Angiotensin System (RAS), apart from fluid homeostasis and Blood Pressure (BP) regulation, are being progressively unveiled, since the discoveries of RAS alternative axes and local RAS in different tissues, including the brain. Brain RAS is reported to interact with pathophysiological mechanisms of many neurological and psychiatric diseases, including Alzheimer's Disease (AD). Even though AD is the most common cause of dementia worldwide, its pathophysiology is far from elucidated. Currently, no treatment can halt the disease course. Successive failures of amyloid-targeting drugs have challenged the amyloid hypothesis and increased the interest in the inflammatory and vascular aspects of AD. RAS compounds, both centrally and peripherally, potentially interact with neuroinflammation and cerebrovascular regulation. This narrative review discusses the AD pathophysiology and its possible interaction with RAS, looking forward to potential therapeutic approaches. RAS molecules affect BP, cerebral blood flow, neuroinflammation, and oxidative stress. Angiotensin (Ang) II, via angiotensin type 1 receptors may promote brain tissue damage, while Ang-(1-7) seems to elicit neuroprotection. Several studies dosed RAS molecules in AD patients' biological material, with heterogeneous results. The link between AD and clinical conditions related to classical RAS axis overactivation (hypertension, heart failure, and chronic kidney disease) supports the hypothesized role of this system in AD. Additionally, RAStargeting drugs as Angiotensin Converting Enzyme inhibitors (ACEis) and Angiotensin Receptor Blockers (ARBs) seem to exert beneficial effects on AD. Results of randomized controlled trials testing ACEi or ARBs in AD are awaited to elucidate whether AD-RAS interaction has implications on AD therapeutics.

Drug response in association with pharmacogenomics and pharmacomicrobiomics: towards a better personalized medicine

Researchers have long been presented with the challenge imposed by the role of genetic heterogeneity in drug response. For many years, Pharmacogenomics and pharmacomicrobiomics has been investigating the influence of an individual's genetic background to drug response and disposition. More recently, the human gut microbiome has proven to play a crucial role in the way patients respond to different therapeutic drugs and it has been shown that by understanding the composition of the human microbiome, we can improve the drug efficacy and effectively identify drug targets. However, our knowledge on the effect of host genetics on specific gut microbes related to variation in drug metabolizing enzymes, the drug remains limited and therefore limits the application of joint host-microbiome genome-wide association studies. In this paper, we provide a historical overview of the complex interactions between the host, human microbiome and drugs. While discussing applications, challenges and opportunities of these studies, we draw attention to the critical need for inclusion of diverse populations and the development of an innovative and combined pharmacogenomics and pharmacomicrobiomics approach, that may provide an important basis in personalized medicine.

Genetic Variation and Hot Flashes: A Systematic Review

CONTEXT

Approximately 70% of women report experiencing vasomotor symptoms (VMS, hot flashes and/or night sweats). The etiology of VMS is not clearly understood but may include genetic factors.

EVIDENCE ACQUISITION

We searched PubMed and Embase in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidance. We included studies on associations between genetic variation and VMS. We excluded studies focused on medication interventions or prevention or treatment of breast cancer.

EVIDENCE SYNTHESIS

Of 202 unique citations, 18 citations met the inclusion criteria. Study sample sizes ranged from 51 to 17 695. Eleven of the 18 studies had fewer than 500 participants; 2 studies had 1000 or more. Overall, statistically significant associations with VMS were found for variants in 14 of the 26 genes assessed in candidate gene studies. The cytochrome P450 family 1 subfamily A member 1 (CYP1B1) gene was the focus of the largest number (n = 7) of studies, but strength and statistical significance of associations of CYP1B1 variants with VMS were inconsistent. A genome-wide association study reported statistically significant associations between 14 single-nucleotide variants in the tachykinin receptor 3 gene and VMS. Heterogeneity across trials regarding VMS measurement methods and effect measures precluded quantitative meta-analysis; there were few studies of each specific genetic variant.

CONCLUSIONS

Genetic variants are associated with VMS. The associations are not limited to variations in sex-steroid metabolism genes. However, studies were few and future studies are needed to confirm and extend these findings.

Haplotype architecture of the Alzheimer's risk in the APOE region via co-skewness

INTRODUCTION

As a multifactorial polygenic disorder, Alzheimer's disease (AD) can be associated with complex haplotypes or compound genotypes.

METHODS

We examined associations of 4960 single nucleotide polymorphism (SNP) triples, comprising 32 SNPs from five genes in the apolipoprotein E gene (APOE) region with AD in a sample of 2789 AD-affected and 16,334 unaffected subjects.

RESULTS

We identified a large number of 1127 AD-associated triples, comprising SNPs from all five genes, in support of definitive roles of complex haplotypes in predisposition to AD. These haplotypes may not include the APOE ε4 and ε2 alleles. For triples with rs429358 or rs7412, which encode these alleles, AD is characterized mainly by strengthening connections of the ε4 allele and weakening connections of the ε2 allele with the other alleles in this region.

DISCUSSION

Dissecting heterogeneity attributed to AD-associated complex haplotypes in the APOE region will target more homogeneous polygenic profiles of people at high risk of AD.

An integrative multi-omics network-based approach identifies key regulators for breast cancer

Although genome-wide association studies (GWASs) have successfully identified thousands of risk variants for human complex diseases, understanding the biological function and molecular mechanisms of the associated SNPs involved in complex diseases is challenging. Here we developed a framework named integrative multi-omics network-based approach (IMNA), aiming to identify potential key genes in regulatory networks by integrating molecular interactions across multiple biological scales, including GWAS signals, gene expression-based signatures, chromatin interactions and protein interactions from the network topology. We applied this approach to breast cancer, and prioritized key genes involved in regulatory networks. We also developed an abnormal gene expression score (AGES) signature based on the gene expression deviation of the top 20 rank-ordered genes in breast cancer. The AGES values are associated with genetic variants, tumor properties and patient survival outcomes. Among the top 20 genes, RNASEH2A was identified as a new candidate gene for breast cancer. Thus, our integrative network-based approach provides a genetic-driven framework to unveil tissue-specific interactions from multiple biological scales and reveal potential key regulatory genes for breast cancer. This approach can also be applied in other complex diseases such as ovarian cancer to unravel underlying mechanisms and help for developing therapeutic targets.

Beef heifer fertility: importance of management practices and technological advancements

The development of replacement heifers is at the core of cow-calf beef production systems. In 2020, the USDA, National Agricultural Statistics Service reported 5.771 million beef heifers, 500 pounds and over, are under development for cow replacement. A compilation of data from several studies indicate that between 85% and 95% of these heifers will become pregnant in their first breeding season. Several thousands of heifers being raised for replacement may not deliver a calf on their first breeding season and result in economic losses to cow-calf producers. Many management procedures have been developed to maximize the reproductive potential of beef heifers. Such approaches include, but are not limited to the following: nutritional management for controlled weight gain, identification of reproductive maturity by physiological and morphological indicators, and the implementation of an estrous synchronization program. The implementation of management strategies has important positive impact(s) on the reproductive efficiency of heifers. There are limitations, however, because some heifers deemed ready to enter their first breeding season do not become pregnant. In parallel, genetic selection for fertility-related traits in beef heifers have not promoted major genetic gains on this particular area, most likely due to low heritability of female fertility traits in cattle. Technologies such as antral follicle counting, DNA genotyping and RNA profiling are being investigated as a means to aid in the identification of heifers of low fertility potential. To date, many polymorphisms have been associated with heifer fertility, but no DNA markers have been identified across herds. Antral follicle count is an indication of the ovarian reserve and is an indicator of the reproductive health of a heifer. We have been working on the identification of transcriptome profiles in heifers associated with pregnancy outcome. Our current investigations integrating protein-coding transcript abundance and artificial intelligence have identified the potential for bloodborne transcript abundance to be used as indicators of fertility potential in beef heifers. In summary, there is an ongoing pressure for reducing costs and increasing efficiency in cow-calf production systems, and new technologies can help reduce the long-standing limitations in beef heifer fertility.

Quantitative and Qualitative Role of Antagonistic Heterogeneity in Genetics of Blood Lipids

Prevailing strategies in genome-wide association studies (GWAS) mostly rely on principles of medical genetics emphasizing one gene, one function, one phenotype concept. Here, we performed GWAS of blood lipids leveraging a new systemic concept emphasizing complexity of genetic predisposition to such phenotypes. We focused on total cholesterol, low- and high-density lipoprotein cholesterols, and triglycerides available for 29,902 individuals of European ancestry from seven independent studies, men and women combined. To implement the new concept, we leveraged the inherent heterogeneity in genetic predisposition to such complex phenotypes and emphasized a new counter intuitive phenomenon of antagonistic genetic heterogeneity, which is characterized by misalignment of the directions of genetic effects and the phenotype correlation. This analysis identified 37 loci associated with blood lipids but only one locus, FBXO33, was not reported in previous top GWAS. We, however, found strong effect of antagonistic heterogeneity that leaded to profound (quantitative and qualitative) changes in the associations with blood lipids in most, 25 of 37 or 68%, loci. These changes suggested new roles for some genes, which functions were considered as well established such as GCKR, SIK3 (APOA1 locus), LIPC, LIPG, among the others. The antagonistic heterogeneity highlighted a new class of genetic associations emphasizing beneficial and adverse trade-offs in predisposition to lipids. Our results argue that rigorous analyses dissecting heterogeneity in genetic predisposition to complex traits such as lipids beyond those implemented in current GWAS are required to facilitate translation of genetic discoveries into health care.

The reuse of public datasets in the life sciences: potential risks and rewards

The 'big data' revolution has enabled novel types of analyses in the life sciences, facilitated by public sharing and reuse of datasets. Here, we review the prodigious potential of reusing publicly available datasets and the associated challenges, limitations and risks. Possible solutions to issues and research integrity considerations are also discussed. Due to the prominence, abundance and wide distribution of sequencing data, we focus on the reuse of publicly available sequence datasets. We define 'successful reuse' as the use of previously published data to enable novel scientific findings. By using selected examples of successful reuse from different disciplines, we illustrate the enormous potential of the practice, while acknowledging the respective limitations and risks. A checklist to determine the reuse value and potential of a particular dataset is also provided. The open discussion of data reuse and the establishment of this practice as a norm has the potential to benefit all stakeholders in the life sciences.

Genome-wide landscape establishes novel association signals for metabolic traits in the Arab population

While the Arabian population has a high prevalence of metabolic disorders, it has not been included in global studies that identify genetic risk loci for metabolic traits. Determining the transferability of such largely Euro-centric established risk loci is essential to transfer the research tools/resources, and drug targets generated by global studies to a broad range of ethnic populations. Further, consideration of populations such as Arabs, that are characterized by consanguinity and a high level of inbreeding, can lead to identification of novel risk loci. We imputed published GWAS data from two Kuwaiti Arab cohorts (n = 1434 and 1298) to the 1000 Genomes Project haplotypes and performed meta-analysis for associations with 13 metabolic traits. We compared the observed association signals with those established for metabolic traits. Our study highlighted 70 variants from 9 different genes, some of which have established links to metabolic disorders. By relaxing the genome-wide significance threshold, we identified ‘novel’ risk variants from 11 genes for metabolic traits. Many novel risk variant association signals were observed at or borderline to genome-wide significance. Furthermore, 349 previously established variants from 187 genes were validated in our study. Pleiotropic effect of risk variants on multiple metabolic traits were observed. Fine-mapping illuminated rs7838666/CSMD1 rs1864163/CETP and rs112861901/[INTS10,LPL] as candidate causal variants influencing fasting plasma glucose and high-density lipoprotein levels. Computational functional analysis identified a variety of gene regulatory signals around several variants. This study enlarges the population ancestry diversity of available GWAS and elucidates new variants in an ethnic group burdened with metabolic disorders.

Lower peripheral helper T cell levels in the synovium are associated with a better response to anti-TNF therapy in rheumatoid arthritis

Background

The mechanisms by which only some rheumatoid arthritis (RA) patients respond favorably to TNF blockade are still poorly characterized. The goal of this study was to identify biological features that explain this differential response using a multilevel transcriptome analysis of the synovial membrane.

Methods

Synovial samples from 11 patients on anti-TNF therapy were obtained by arthroscopy at baseline and week 20. Analysis of the synovial transcriptome was performed at the gene, pathway, and cell-type levels. Newly characterized pathogenic cell types in RA, peripheral helper T cells (T_PH), and CD34-THY1+ fibroblasts were estimated using a cell-type deconvolution approach. T_PH association was validated using immunofluorescence. External validation was performed on an independent dataset.

Results

After multiple-test correction, 16 and 4 genes were differentially expressed at baseline and week 20, respectively. At the pathway level, 86 and 17 biological processes were significantly enriched at baseline and week 20, respectively. Longitudinal expression changes were associated with a drastic decrease of innate immune activity (P < 5e−30), and an activation of the bone and cartilage regeneration processes (P < 5e−10). Cell-type deconvolution revealed a significant association between low T_PH cells at baseline and a better response (P = 0.026). Lower T_PH cells were maintained in good responders up to week 20 (P = 0.032). Immunofluorescent analyses confirmed the accuracy of the cell-type estimation (r² = 0.58, P = 0.005) and an association with response. T_PH association with anti-TNF response was validated in an independent sample of RA patients (P = 0.0040).

Conclusions

A lower abundance in the synovial membrane of the pathogenic T cell type newly associated with RA, peripheral helper T lymphocyte, is associated with a good response to anti-TNF therapy. Major changes in the myeloid cell compartment were also observed in response to therapy. The results of this study could help develop more effective therapies aimed at treating the pathogenic mechanisms in RA that are currently not well targeted by anti-TNF agents.

Genetic and genomic analyses of embryo production in dairy cattle

The Canadian dairy industry has been using invivo and invitro assisted reproductive technologies to produce embryos. Technological improvements have helped increase the number and quality of embryos produced, but genetic and genomic tools for improving these traits have yet to be assessed for the Canadian Holstein population. Genetic parameters and a genome-wide association study were performed in Canadian Holstein for the total number of embryos (NE) and the number of viable embryos (VE). Results showed potential for genetic selection for both NE and VE, with heritability estimates (± s.e.) of approximately 0.15±0.01. Genetic correlations between the number of embryos produced using different procedures (invivo and invitro) suggested that a similar number of embryos should be expected from a donor regardless of the procedure used. A region on chromosome 11 of the bovine genome was found to be significantly associated with the number of embryos, indicating a potential regulatory role of this region on embryo production. Overall, these findings are of interest for the Canadian dairy industry because they provide useful information for breeders that are interested in producing embryos from the elite donors in their herds or in the population using assisted reproductive technologies.

Genetic architecture of complex traits and disease risk predictors

Genomic prediction of complex human traits (e.g., height, cognitive ability, bone density) and disease risks (e.g., breast cancer, diabetes, heart disease, atrial fibrillation) has advanced considerably in recent years. Using data from the UK Biobank, predictors have been constructed using penalized algorithms that favor sparsity: i.e., which use as few genetic variants as possible. We analyze the specific genetic variants (SNPs) utilized in these predictors, which can vary from dozens to as many as thirty thousand. We find that the fraction of SNPs in or near genic regions varies widely by phenotype. For the majority of disease conditions studied, a large amount of the variance is accounted for by SNPs outside of coding regions. The state of these SNPs cannot be determined from exome-sequencing data. This suggests that exome data alone will miss much of the heritability for these traits-i.e., existing PRS cannot be computed from exome data alone. We also study the fraction of SNPs and of variance that is in common between pairs of predictors. The DNA regions used in disease risk predictors so far constructed seem to be largely disjoint (with a few interesting exceptions), suggesting that individual genetic disease risks are largely uncorrelated. It seems possible in theory for an individual to be a low-risk outlier in all conditions simultaneously.

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.

Scleral HIF-1α is a prominent regulatory candidate for genetic and environmental interactions in human myopia pathogenesis

BACKGROUND

Myopia is a good model for understanding the interaction between genetics and environmental stimuli. Here we dissect the biological processes affecting myopia progression.

METHODS

Human Genetic Analyses: (1) gene set analysis (GSA) of new genome wide association study (GWAS) data for 593 individuals with high myopia (refraction ≤ -6 diopters [D]); (2) over-representation analysis (ORA) of 196 genes with de novo mutations, identified by whole genome sequencing of 45 high-myopia trio families, and (3) ORA of 284 previously reported myopia risk genes. Contributions of the enriched signaling pathways in mediating the genetic and environmental interactions during myopia development were investigated in vivo and in vitro.

RESULTS

All three genetic analyses showed significant enrichment of four KEGG signaling pathways, including amphetamine addiction, extracellular matrix (ECM) receptor interaction, neuroactive ligand-receptor interaction, and regulation of actin cytoskeleton pathways. In individuals with extremely high myopia (refraction ≤ -10 D), the GSA of GWAS data revealed significant enrichment of the HIF-1α signaling pathway. Using human scleral fibroblasts, silencing the key nodal genes within protein-protein interaction networks for the enriched pathways antagonized the hypoxia-induced increase in myofibroblast transdifferentiation. In mice, scleral HIF-1α downregulation led to hyperopia, whereas upregulation resulted in myopia. In human subjects, near work, a risk factor for myopia, significantly decreased choroidal blood perfusion, which might cause scleral hypoxia.

INTERPRETATION

Our study implicated the HIF-1α signaling pathway in promoting human myopia through mediating interactions between genetic and environmental factors.

FUNDING

National Natural Science Foundation of China grants; Natural Science Foundation of Zhejiang Province.

Ancestry effects on type 2 diabetes genetic risk inference in Hispanic/Latino populations

Background

Hispanic/Latino (HL) populations bear a disproportionately high burden of type 2 diabetes (T2D). The ability to predict T2D genetic risk using polygenic risk scores (PRS) offers great promise for improved screening and prevention. However, there are a number of complications related to the accurate inference of genetic risk across HL populations with distinct ancestry profiles. We investigated how ancestry affects the inference of T2D genetic risk using PRS in diverse HL populations from Colombia and the United States (US). In Colombia, we compared T2D genetic risk for the Mestizo population of Antioquia to the Afro-Colombian population of Chocó, and in the US, we compared European-American versus Mexican-American populations.

Methods

Whole genome sequences and genotypes from the 1000 Genomes Project and the ChocoGen Research Project were used for genetic ancestry inference and for T2D polygenic risk score (PRS) calculation. Continental ancestry fractions for HL genomes were inferred via comparison with African, European, and Native American reference genomes, and PRS were calculated using T2D risk variants taken from multiple genome-wide association studies (GWAS) conducted on cohorts with diverse ancestries. A correction for ancestry bias in T2D risk inference based on the frequencies of ancestral versus derived alleles was developed and applied to PRS calculations in the HL populations studied here.

Results

T2D genetic risk in Colombian and US HL populations is positively correlated with African and Native American ancestry and negatively correlated with European ancestry. The Afro-Colombian population of Chocó has higher predicted T2D risk than Antioquia, and the Mexican-American population has higher predicted risk than the European-American population. The inferred relative risk of T2D is robust to differences in the ancestry of the GWAS cohorts used for variant discovery. For trans-ethnic GWAS, population-specific variants and variants with same direction effects across populations yield consistent results. Nevertheless, the control for bias in T2D risk prediction confirms that explicit consideration of genetic ancestry can yield more reliable cross-population genetic risk inferences.

Conclusions

T2D associations that replicate across populations provide for more reliable risk inference, and modeling population-specific frequencies of ancestral and derived risk alleles can help control for biases in PRS estimation.

Update on NAFLD genetics: From new variants to the clinic

Non-alcoholic fatty liver disease (NAFLD) is the leading cause of liver diseases in high-income countries and the burden of NAFLD is increasing at an alarming rate. The risk of developing NAFLD and related complications is highly variable among individuals and is determined by environmental and genetic factors. Genome-wide association studies have uncovered robust and reproducible associations between variations in genes such as PNPLA3, TM6SF2, MBOAT7, GCKR, HSD17B13 and the natural history of NAFLD. These findings have provided compelling new insights into the biology of NAFLD and highlighted potentially attractive pharmaceutical targets. More recently the development of polygenic risk scores, which have shown promising results for the clinical risk prediction of other complex traits (such as cardiovascular disease and breast cancer), have provided new impetus for the clinical validation of genetic variants in NAFLD risk stratification. Herein, we review current knowledge on the genetic architecture of NAFLD, including gene-environment interactions, and discuss the implications for disease pathobiology, drug discovery and risk prediction. We particularly focus on the potential clinical translation of recent genetic advances, discussing methodological hurdles that must be overcome before these discoveries can be implemented in everyday practice.

Identification of SNPs involved in Zn and Cu accumulation in the Pacific oyster (Crassostrea gigas) by genome-wide association analysis

Oysters accumulate high concentrations of zinc (Zn) and copper (Cu), which can be transferred to human due to sea food consumption. Breeding new oyster varieties with low Zn and Cu accumulations is one important way to improve food safety. However, the genetic basis for metal accumulation in mollusks is not well understood. To address this issue, oysters collected in the field were used for genome-wide association study (GWAS) and then the identified genes were used for mRNA expressions analysis in laboratory. First, GWAS were conducted for Zn and Cu accumulation in 288 wild Pacific oysters (Crassostrea gigas) farmed in the same ocean environment. The oysters did not show obvious population structure or kinship but exhibited 8.43- and 10.0- fold changes of Zn and Cu contents respectively. GWAS have identified 11 and 12 single nucleotide polymorphisms (SNPs) associated with Zn and Cu, respectively, as well as 16 genes, which were Zn-containing proteins or participated in caveolae-dependent endocytosis. Second, the mRNA expressions of these 16 genes were observed under Zn and Cu exposure. After 9 days of Zn exposure, Zn contents increased 3.1-fold, while the mRNA expression of cell number regulator 3 increased 1.65-fold. Under 9 days of Cu exposure, Cu contents increased 1.97-fold, while the mRNA expression of caveolin-1 decreased 0.61-fold. These provide the evidence for their roles in regulating physiological levels of these two metals. The findings advance our understanding of the genetic basis of Zn and Cu accumulation in mollusks, which can be useful for breeding new, less toxic varieties of oysters.

Transposable elements contribute to the genomic response to insecticides in Drosophila melanogaster

Most of the genotype–phenotype analyses to date have largely centred attention on single nucleotide polymorphisms. However, transposable element (TE) insertions have arisen as a plausible addition to the study of the genotypic–phenotypic link because of to their role in genome function and evolution. In this work, we investigate the contribution of TE insertions to the regulation of gene expression in response to insecticides. We exposed four Drosophila melanogaster strains to malathion, a commonly used organophosphate insecticide. By combining information from different approaches, including RNA-seq and ATAC-seq, we found that TEs can contribute to the regulation of gene expression under insecticide exposure by rewiring cis-regulatory networks.

This article is part of a discussion meeting issue ‘Crossroads between transposons and gene regulation’.

Omics in Neurodegenerative Disease: Hope or Hype?

The past 15 years have seen a boom in the use and integration of 'omic' approaches (limited here to genomic, transcriptomic, and epigenomic techniques) to study neurodegenerative disease in an unprecedented way. We first highlight advances in and the limitations of using such approaches in the neurodegenerative disease literature, with a focus on Alzheimer's disease (AD), Parkinson's disease (PD), frontotemporal lobar degeneration (FTLD), and amyotrophic lateral sclerosis (ALS). We next discuss how these studies can advance human health in the form of generating leads for downstream mechanistic investigation or yielding polygenic risk scores (PRSs) for prognostication. However, we argue that these approaches constitute a new form of molecular description, analogous to clinical or pathological description, that alone does not hold the key to solving these complex diseases.

Why is Disease Penetration So Variable? Role of Genetic Modifiers of Lung Function in Alpha-1 Antitrypsin Deficiency

Individuals with alpha-1 antitrypsin deficiency (AATD) have marked heterogeneity in lung function, suspected to be related to a combination of both environmental (e.g., cigarette smoking) and genetic factors. Lung function is heritable in the general population and in persons with severe AATD. Several genetic modifiers of lung function in persons with AATD have been described; however, replication is lacking. A genome-wide association study (GWAS) of lung function in persons with AATD has yet to be performed and may inform whether genetic determinants of lung function are overlapping in persons with AATD and in the general population. As GWASs require large sample sizes for adequate power, genetic risk scores offer an alternate approach to assess the overlap of genetic determinants of lung function in the general population in persons with AATD. Where GWASs are limited to common genetic variant discovery, whole genome sequencing (for rare variant discovery) and integrative genomic studies (examining the influence of genetic variants on gene, protein, and metabolite levels) offer potential for an expanded discovery of genetic modifiers of lung function in AATD. In the following review we examine past descriptions of genetic modifiers of lung function in AATD and describe a path forward to further investigate and define the likely genetic modifiers of lung function in AATD.

Genetics' Piece of the PI: Inferring the Origin of Complex Traits and Diseases from Proteome-Wide Protein-Protein Interaction Dynamics

How do common and rare genetic polymorphisms contribute to quantitative traits or disease risk and progression? Multiple human traits have been extensively characterized at the genomic level, revealing their complex genetic architecture. However, it is difficult to resolve the mechanisms by which specific variants contribute to a phenotype. Recently, analyses of variant effects on molecular traits have uncovered intermediate mechanisms that link sequence variation to phenotypic changes. Yet, these methods only capture a fraction of genetic contributions to phenotype. Here, in reviewing the field, it is proposed that complex traits can be understood by characterizing the dynamics of biochemical networks within living cells, and that the effects of genetic variation can be captured on these networks by using protein-protein interaction (PPI) methodologies. This synergy between PPI methodologies and the genetics of complex traits opens new avenues to investigate the molecular etiology of human diseases and to facilitate their prevention or treatment.

Phosphoproteomics reveals conserved exercise-stimulated signaling and AMPK regulation of store-operated calcium entry

Exercise stimulates cellular and physiological adaptations that are associated with widespread health benefits. To uncover conserved protein phosphorylation events underlying this adaptive response, we performed mass spectrometry-based phosphoproteomic analyses of skeletal muscle from two widely used rodent models: treadmill running in mice and in situ muscle contraction in rats. We overlaid these phosphoproteomic signatures with cycling in humans to identify common cross-species phosphosite responses, as well as unique model-specific regulation. We identified > 22,000 phosphosites, revealing orthologous protein phosphorylation and overlapping signaling pathways regulated by exercise. This included two conserved phosphosites on stromal interaction molecule 1 (STIM1), which we validate as AMPK substrates. Furthermore, we demonstrate that AMPK-mediated phosphorylation of STIM1 negatively regulates store-operated calcium entry, and this is beneficial for exercise in Drosophila. This integrated cross-species resource of exercise-regulated signaling in human, mouse, and rat skeletal muscle has uncovered conserved networks and unraveled crosstalk between AMPK and intracellular calcium flux.

Genome-wide Associations Reveal Human-Mouse Genetic Convergence and Modifiers of Myogenesis, CPNE1 and STC2

Muscle bulk in adult healthy humans is highly variable even after height, age, and sex are accounted for. Low muscle mass, due to fewer and/or smaller constituent muscle fibers, would exacerbate the impact of muscle loss occurring in aging or disease. Genetic variability substantially influences muscle mass differences, but causative genes remain largely unknown. In a genome-wide association study (GWAS) on appendicular lean mass (ALM) in a population of 85,750 middle-aged (aged 38-49 years) individuals from the UK Biobank (UKB), we found 182 loci associated with ALM (p < 5 × 10-8). We replicated associations for 78% of these loci (p < 5 × 10-8) with ALM in a population of 181,862 elderly (aged 60-74 years) individuals from UKB. We also conducted a GWAS on hindlimb skeletal muscle mass of 1,867 mice from an advanced intercross between two inbred strains (LG/J and SM/J); this GWAS identified 23 quantitative trait loci. Thirty-eight positional candidates distributed across five loci overlapped between the two species. In vitro studies of positional candidates confirmed CPNE1 and STC2 as modifiers of myogenesis. Collectively, these findings shed light on the genetics of muscle mass variability in humans and identify targets for the development of interventions for treatment of muscle loss. The overlapping results between humans and the mouse model GWAS point to shared genetic mechanisms across species.

Genome-Wide Study Updates in the International Genetics and Translational Research in Transplantation Network (iGeneTRAiN)

The prevalence of end-stage renal disease (ESRD) and the number of kidney transplants performed continues to rise every year, straining the procurement of deceased and living kidney allografts and health systems. Genome-wide genotyping and sequencing of diseased populations have uncovered genetic contributors in substantial proportions of ESRD patients. A number of these discoveries are beginning to be utilized in risk stratification and clinical management of patients. Specifically, genetics can provide insight into the primary cause of chronic kidney disease (CKD), the risk of progression to ESRD, and post-transplant outcomes, including various forms of allograft rejection. The International Genetics & Translational Research in Transplantation Network (iGeneTRAiN), is a multi-site consortium that encompasses >45 genetic studies with genome-wide genotyping from over 51,000 transplant samples, including genome-wide data from >30 kidney transplant cohorts (n = 28,015). iGeneTRAiN is statistically powered to capture both rare and common genetic contributions to ESRD and post-transplant outcomes. The primary cause of ESRD is often difficult to ascertain, especially where formal biopsy diagnosis is not performed, and is unavailable in ∼2% to >20% of kidney transplant recipients in iGeneTRAiN studies. We overview our current copy number variant (CNV) screening approaches from genome-wide genotyping datasets in iGeneTRAiN, in attempts to discover and validate genetic contributors to CKD and ESRD. Greater aggregation and analyses of well phenotyped patients with genome-wide datasets will undoubtedly yield insights into the underlying pathophysiological mechanisms of CKD, leading the way to improved diagnostic precision in nephrology.

SNP eQTL status and eQTL density in the adjacent region of the SNP are associated with its statistical significance in GWA studies

Background

Over the relatively short history of Genome Wide Association Studies (GWASs), hundreds of GWASs have been published and thousands of disease risk-associated SNPs have been identified. Summary statistics from the conducted GWASs are often available and can be used to identify SNP features associated with the level of GWAS statistical significance. Those features could be used to select SNPs from gray zones (SNPs that are nominally significant but do not reach the genome-wide level of significance) for targeted analyses.

Methods

We used summary statistics from recently published breast and lung cancer and scleroderma GWASs to explore the association between the level of the GWAS statistical significance and the expression quantitative trait loci (eQTL) status of the SNP. Data from the Genotype-Tissue Expression Project (GTEx) were used to identify eQTL SNPs.

Results

We found that SNPs reported as eQTLs were more significant in GWAS (higher -log₁₀p) regardless of the tissue specificity of the eQTL. Pan-tissue eQTLs (those reported as eQTLs in multiple tissues) tended to be more significant in the GWAS compared to those reported as eQTL in only one tissue type. eQTL density in the ±5 kb adjacent region of a given SNP was also positively associated with the level of GWAS statistical significance regardless of the eQTL status of the SNP. We found that SNPs located in the regions of high eQTL density were more likely to be located in regulatory elements (transcription factor or miRNA binding sites).

When SNPs were stratified by the level of statistical significance, the proportion of eQTLs was positively associated with the mean level of statistical significance in the group. The association curve reaches a plateau around -log₁₀p ≈ 5. The observed associations suggest that quasi-significant SNPs (10^− 5 < p < 5 × 10^− 8) and SNPs at the genome wide level of statistical significance (p < 5 × 10^− 8) may have a similar proportions of risk associated SNPs.

Conclusions

The results of this study indicate that the SNP’s eQTL status, as well as eQTL density in the adjacent region are positively associated with the level of statistical significance of the SNP in GWAS.

What did we learn from multiple omics studies in asthma?

More than a decade has passed since the finalization of the Human Genome Project. Omics technologies made a huge leap from trendy and very expensive to routinely executed and relatively cheap assays. Simultaneously, we understood that omics is not a panacea for every problem in the area of human health and personalized medicine. Whilst in some areas of research omics showed immediate results, in other fields, including asthma, it only allowed us to identify the incredibly complicated molecular processes. Along with their possibilities, omics technologies also bring many issues connected to sample collection, analyses and interpretation. It is often impossible to separate the intrinsic imperfection of omics from asthma heterogeneity. Still, many insights and directions from applied omics were acquired-presumable phenotypic clusters of patients, plausible biomarkers and potential pathways involved. Omics technologies develop rapidly, bringing improvements also to asthma research. These improvements, together with our growing understanding of asthma subphenotypes and underlying cellular processes, will likely play a role in asthma management strategies.

Distribution of local ancestry and evidence of adaptation in admixed populations

Admixed American populations have different global proportions of European, Sub-Saharan African, and Native-American ancestry. However, individuals who display the same global ancestry could exhibit remarkable differences in the distribution of local ancestry blocks. We studied for the first time the distribution of local ancestry across the genome of 264 Brazilian admixed individuals, ascertained within the scope of the Brazilian Initiative on Precision Medicine. We found a decreased proportion of European ancestry together with an excess of Native-American ancestry on chromosome 8p23.1 and showed that this is due to haplotypes created by chromosomal inversion events. Furthermore, Brazilian non-inverted haplotypes were more similar to Native-American haplotypes than to European haplotypes, in contrast to what was found in other American admixed populations. We also identified signals of recent positive selection on chromosome 8p23.1, and one gene within this locus, PPP1R3B, is related to glycogenesis and has been associated with an increased risk of type 2 diabetes and obesity. These findings point to a selection event after admixture, which is still not entirely understood in recent admixture events.

Shared polygenic risk and causal inferences in amyotrophic lateral sclerosis

OBJECTIVE

To identify shared polygenic risk and causal associations in amyotrophic lateral sclerosis (ALS).

METHODS

Linkage disequilibrium score regression and Mendelian randomization were applied in a large-scale, data-driven manner to explore genetic correlations and causal relationships between >700 phenotypic traits and ALS. Exposures consisted of publicly available genome-wide association studies (GWASes) summary statistics from MR Base and LD-hub. The outcome data came from the recently published ALS GWAS involving 20,806 cases and 59,804 controls. Multivariate analyses, genetic risk profiling, and Bayesian colocalization analyses were also performed.

RESULTS

We have shown, by linkage disequilibrium score regression, that ALS shares polygenic risk genetic factors with a number of traits and conditions, including positive correlations with smoking status and moderate levels of physical activity, and negative correlations with higher cognitive performance, higher educational attainment, and light levels of physical activity. Using Mendelian randomization, we found evidence that hyperlipidemia is a causal risk factor for ALS and localized putative functional signals within loci of interest.

INTERPRETATION

Here, we have developed a public resource (https://lng-nia.shinyapps.io/mrshiny) which we hope will become a valuable tool for the ALS community, and that will be expanded and updated as new data become available. Shared polygenic risk exists between ALS and educational attainment, physical activity, smoking, and tenseness/restlessness. We also found evidence that elevated low-desnity lipoprotein cholesterol is a causal risk factor for ALS. Future randomized controlled trials should be considered as a proof of causality. Ann Neurol 2019;85:470-481.

Identification of evolutionarily conserved virulence factor by selective pressure analysis of Streptococcus pneumoniae

Evolutionarily conserved virulence factors can be candidate therapeutic targets or vaccine antigens. Here, we investigated the evolutionary selective pressures on 16 pneumococcal choline-binding cell-surface proteins since Streptococcus pneumoniae is one of the pathogens posing the greatest threats to human health. Phylogenetic and molecular analyses revealed that cbpJ had the highest codon rates to total numbers of codons under considerable negative selection among those examined. Our in vitro and in vivo assays indicated that CbpJ functions as a virulence factor in pneumococcal pneumonia by contributing to evasion of neutrophil killing. Deficiency of cbpL under relaxed selective pressure also caused a similar tendency but showed no significant difference in mouse intranasal infection. Thus, molecular evolutionary analysis is a powerful tool that reveals the importance of virulence factors in real-world infection and transmission, since calculations are performed based on bacterial genome diversity following transmission of infection in an uncontrolled population.

Comparison and assessment of family- and population-based genotype imputation methods in large pedigrees

Genotype imputation is widely used in genome-wide association studies to boost variant density, allowing increased power in association testing. Many studies currently include pedigree data due to increasing interest in rare variants coupled with the availability of appropriate analysis tools. The performance of population-based (subjects are unrelated) imputation methods is well established. However, the performance of family- and population-based imputation methods on family data has been subject to much less scrutiny. Here, we extensively compare several family- and population-based imputation methods on family data of large pedigrees with both European and African ancestry. Our comparison includes many widely used family- and population-based tools and another method, Ped_Pop, which combines family- and population-based imputation results. We also compare four subject selection strategies for full sequencing to serve as the reference panel for imputation: GIGI-Pick, ExomePicks, PRIMUS, and random selection. Moreover, we compare two imputation accuracy metrics: the Imputation Quality Score and Pearson's correlation R ² for predicting power of association analysis using imputation results. Our results show that (1) GIGI outperforms Merlin; (2) family-based imputation outperforms population-based imputation for rare variants but not for common ones; (3) combining family- and population-based imputation outperforms all imputation approaches for all minor allele frequencies; (4) GIGI-Pick gives the best selection strategy based on the R ² criterion; and (5) R ² is the best measure of imputation accuracy. Our study is the first to extensively evaluate the imputation performance of many available family- and population-based tools on the same family data and provides guidelines for future studies.