Health Genomics Research Articles

Toward building a comprehensive human pan-genome: The SEN-GENOME project

The human reference genome (GRCh38), primarily sourced from individuals of European descent, falls short in capturing the vast genetic diversity across global populations. Efforts to diversify the reference genome face challenges in accessibility and representation, exacerbating the scarcity of African genomic data crucial for studying diseases prevalent in these populations. Sherman etal. proposed constructing reference genomes tailored to distinct human sub-populations. Their African Pan-Genome initiative highlighted substantial genetic variation missing from the GRCh38 human reference genome, emphasizing the necessity for population-specific genomes. In response, local initiatives like the Senegalese Genome project (SEN-GENOME) have emerged to document the genomes of historically overlooked populations. SEN-GENOME embodies community-driven decentralized research. With meticulous recruitment criteria and ethical practices, it aims to sequence 1,000 genomes from 31 ethnolinguistic groups, in the fourteen administrative regions of Senegal, fostering local genomic research tailored to the region. The key to SEN-GENOME's success is its commitment to local governance of data, capacity building, and integration with broader pan-genome projects in Africa. Despite the complexities of data harmonization and sharing, our collaborative efforts are aligned with common goals, ensuring steady progress toward a comprehensive human pan-genome. We invite and welcome collaboration with other research entities to achieve this shared vision. In summary, local initiatives such as SEN-GENOME are pivotal in bridging genomic disparities, offering pathways to equitable and inclusive genomic research. Collaborative endeavors guided by a collective vision for human health will propel us toward a more encompassing understanding of the human genome and better health through genomic medicine.

RARE, BUT NOT INVISIBLE: ADVANCING GENOMICS RESEARCH A ND IMPLEMENTATION FOR UNDIAGNOSED DISEASES

Rare diseases comprise thousands of very diverse, chronic conditions that can cause disability and/or premature death. Each one affects a few people, but collectively, it is estimated that they impact up to 5% of the population. Most rare diseases are of genetic origin. The development of new genomic tools, such as massive or next-generation sequencing, has led to a revolution in discovery, diagnosis and therapeutic developments. However, access to these technologies is very limited in Chile. This article describes our work in advancing the implementation and evaluation of genomic strategies for people with rare diseases in Chile, as well as reflections and proposals for the development of genomics in health in our country.

Associations between subjective social status and predictors of interest in genetic testing among women diagnosed with breast cancer at a young age.

Genetic testing for gene mutations which elevate risk for breast cancer is particularly important for women diagnosed at a young age. Differences remain in access and utilization to testing across social groups, and research on the predictors of interest in genetic testing for women diagnosed at a young age is limited. We examined the relationships between subjective social status (SSS) and variables previously identified as possible predictors of genetic testing, including genome sequencing knowledge, genetic worry, cancer worry, health consciousness, decision-making preferences, genetic self-efficacy, genetic-related beliefs, and subjective numeracy, among a cohort of women who were diagnosed with breast cancer at a young age. In this sample (n = 1,076), those who had higher SSS had significantly higher knowledge about the limitations of genome sequencing (Odds Ratio (OR) = 1.11; 95% CI = 1.01-1.21) and significantly higher informational norms (OR = 1.93; 95% CI = 1.19-3.14) than those with lower SSS. Similarly, education (OR = 2.75; 95% CI = 1.79-4.22), health status (OR = 2.18; 95% CI = 1.44-3.31) were significant predictors among higher SSS women compared to lower SSS women in our multivariate analysis. Lower SSS women with low self-reported income (OR = 0.13; 95% CI = 0.08-0.20) had lower odds of genetic testing interest. Our results are consistent with some prior research utilizing proxy indicators for socioeconomic status, but our research adds the importance of using a multidimensional indicator such as SSS to examine cancer and genetic testing predictor outcomes. To develop interventions to improve genetic knowledge, researchers should consider the social status and contexts of women diagnosed with breast cancer at a young age (or before 40 years old) to ensure equity in the distribution of genetic testing benefits.

Abstract P494: Gene-Level Gene-Environment Interaction Testing Reveals Rare Variants With Large Impacts on the Omega-3 Fatty Acid-Inflammation Relationship

Dietary omega-3 fatty acid (dN3FA) intake affects plasma N3FA (pN3FA) concentrations, circulating biomarkers of chronic inflammation such as high-sensitivity C-reactive protein (hsCRP), and ultimately cardiometabolic disease risk. Genetic variation may modify the N3FA-inflammation relationship, facilitating applications in precision medicine and possibly explaining variable intervention trial responses. Here, we explored the dual hypothesis that pN3FA mediates the dN3FA-hsCRP relationship and that genetic variants across the frequency spectrum modify this association. Regression models in the UK Biobank (N = 342,120) tested main effects of oily fish intake (a primary dietary source of N3FA; measured by food frequency questionnaire) on hsCRP and its mediation by pN3FA (measured by nuclear magnetic resonance; N = 188,701). Three genome-wide interaction studies tested modification of the dN3FA-hsCRP (“full”), dN3FA-pN3FA (“upstream”), and pN3FA-hsCRP (“downstream”) associations. Regression covariates included demographics, lifestyle indicators, socioeconomic measures, and genetic principal components. Variant-specific GWIS were followed by gene-level enrichment testing using the MAGMA tool. Replication of gene-based signals was conducted in the Women’s Genome Health Study (WGHS; N = 23,294) by testing the interaction of the top variant in each gene with total dN3FA impacting hsCRP. Oily fish intake associated most strongly with hsCRP compared to other questionnaire-based estimates of fish or fish oil intake, with statistical evidence that plasma N3FA mediated approximately 100% of this diet-inflammation relationship. While the “full” genetic interaction analysis did not produce any FDR-significant gene-level interactions, the “upstream” analysis uncovered nine genes, including a cluster containing the biologically-relevant fatty acid desaturases FADS1 and FADS2 , and the “downstream” analysis uncovered four genes. Primary variant interaction effect sizes were small (e.g., -0.02 std. dev. bN3FA / std. dev. fish / allele for the top FADS1 variant rs174560), but in-depth follow-up at these genes revealed allelic spectra including rare variants with substantially larger effects (e.g., -0.11 for a FADS1 missense variant with allele frequency of 0.14%, after conditioning on rs174560). WGHS results supported the overall robustness of the findings (consistent interaction effect signs at 8/10 loci), replicated specific signals (p = 0.04 for FADS1 rs174560), and implicated additional inflammatory biomarkers (e.g., fibrinogen and ICAM-1 for the top GLTSCR1 variant). In conclusion, we report (1) the novel epidemiological finding that pN3FA fully mediates the dN3FA-hsCRP relationship, and (2) specific genes with large-effect rare variants that modify the upstream (absorption) and downstream (inflammatory pathways) components of this relationship.

Association between Asthma and Periodontitis.

The current study aimed to investigate the association between asthma and periodontitis in the Korean adult population. Data from the Korean Genome and Epidemiology Study Health Examinees between 2004 and 2016 were considered. Of the 173,209 participants, 2521 asthmatic and 132,806 control participants were selected. The participants were categorized according to their current status of asthma, as 'well-controlled', 'being treated', and 'not being treated'. The prevalence of periodontitis was found to be significantly higher in the participants with asthma (13.1%) than in the controls (7.3%). In the fully adjusted model, the patients with asthma had a higher odds ratio (OR = 1.79, 95% confidence interval [CI] = 1.59-2.02, p < 0.001) for periodontitis than those without asthma. The results were consistent across all the age and sex subgroups. The adjusted ORs for periodontitis were 2.15 (95% CI = 1.68-2.76, p < 0.001) in the 'well-controlled' asthma group, 1.44 (95% CI = 1.16-1.78, p < 0.001) in the 'being treated' asthma group, and 1.86 (95% CI = 1.55-2.22, p < 0.001) in the 'not being treated' asthma group compared to the control group. Overall, we found asthma to be associated with periodontitis in Korean adults, and the participants with well-controlled asthma had the highest ORs for periodontitis.

Genome-wide association study meta-analysis of dizygotic twinning illuminates genetic regulation of female fecundity.

Genome-wide association study meta-analysis of dizygotic twinning illuminates genetic regulation of female fecundity.

Revolutionizing Biological Science: The Synergy of Genomics in Health, Bioinformatics, Agriculture, and Artificial Intelligence.

With climate emergency, COVID-19, and the rise of planetary health scholarship, the binary of human and ecosystem health has been deeply challenged. The interdependence of human and nonhuman animal health is increasingly acknowledged and paving the way for new frontiers in integrative biology. The convergence of genomics in health, bioinformatics, agriculture, and artificial intelligence (AI) has ushered in a new era of possibilities and applications. However, the sheer volume of genomic/multiomics big data generated also presents formidable sociotechnical challenges in extracting meaningful biological, planetary health and ecological insights. Over the past few years, AI-guided bioinformatics has emerged as a powerful tool for managing, analyzing, and interpreting complex biological datasets. The advances in AI, particularly in machine learning and deep learning, have been transforming the fields of genomics, planetary health, and agriculture. This article aims to unpack and explore the formidable range of possibilities and challenges that result from such transdisciplinary integration, and emphasizes its radically transformative potential for human and ecosystem health. The integration of these disciplines is also driving significant advancements in precision medicine and personalized health care. This presents an unprecedented opportunity to deepen our understanding of complex biological systems and advance the well-being of all life in planetary ecosystems. Notwithstanding in mind its sociotechnical, ethical, and critical policy challenges, the integration of genomics, multiomics, planetary health, and agriculture with AI-guided bioinformatics opens up vast opportunities for transnational collaborative efforts, data sharing, analysis, valorization, and interdisciplinary innovations in life sciences and integrative biology.

Association between inflammatory potential of diet and periodontitis disease risks: Results from a Korean population-based cohort study.

To examine the association between a pro-inflammatory diet, estimated using the energy-adjusted dietary inflammatory index (E-DII), and the risk of periodontitis. Study subjects from the Korean Genome and Epidemiology Study Health Examinee (KoGES_HEXA) cohort were included for cross-sectional analysis (n = 168,378) using multivariate logistic regression and prospective analysis (n = 160,397) using Cox proportional hazard models respectively. DII and E-DII scores were calculated based on the intake reported on a validated semi-quantitative food frequency questionnaire (SQ-FFQ). Cox proportional hazard models revealed a significantly increased risk of incident periodontitis in individuals consuming high E-DII (more pro-inflammatory) diets in the total population (HRquartile4vs1 = 1.29; 95% CI: 1.13-1.48; ptrend <.001) and in both men (HRquartile4vs1 = 1.36; 95% CI: 1.07-1.73; ptrend = 0.02) and women (HRquartile4vs1 = 1.27; 95% CI: 1.08-1.50; ptrend = .002). The association remained significant even after excluding cases diagnosed early in the follow-up. In the cross-sectional analysis, a significant association was observed between the E-DII score and the prevalence of periodontitis among all study subjects (ORquartile4vs1 = 1.17; 95% CI: 1.03-1.34; ptrend = 0.01) and men (ORquartile4vs1 = 1.28; 95%CI: 1.01-1.63; ptrend <.001); however, the association did not reach statistical significance in women (ORquartile4vs1 = 1.13; 95% CI: 0.96-1.33; ptrend <.001). Findings from the current study support the hypothesis that diets with high pro-inflammatory potential increase the risk of periodontitis.

The association between meat intake and the risk of coronary heart disease in Korean men using the Framingham risk score: A prospective cohort study

Background and aimsResearch suggests that meat intake may increase the risk of coronary heart disease (CHD), but most studies take place in Western countries, where the types and amount of meat products consumed differ from those in Asian countries. We aimed to identify the association between meat intake and CHD risk in Korean male adults, using the Framingham risk score. Methods and resultsWe used data from the Korean Genome and Epidemiology Study (KoGES) Health Examinees (HEXA) study, including 13,293 Korean male adults. We estimated the association of meat intake with ≥20% 10-year CHD risk using Cox proportional hazards regression models to calculate the hazard ratios (HRs) and 95% confidence intervals (CIs). Subjects with the highest total meat intake had a 53% (model 4: HR 1.53, 95% CI 1.05–2.21) increased 10-year CHD risk compared to those with the lowest intake. Those with the highest red meat intake had a 55% (model 3: HR 1.55, 95% CI 1.16–2.06) increased 10-year CHD risk compared to those with the lowest intake. No association was observed between poultry or processed meat intake and 10-year CHD risk. ConclusionsConsumption of total meat and red meat was associated with a higher risk of CHD in Korean male adults. Further studies are needed to provide criteria for the appropriate meat intake by meat type to reduce CHD risk.

Candidate loci shared among periodontal disease, diabetes and bone density.

While periodontal disease (PD) has been associated with type 2 diabetes (T2D) and osteoporosis, the underlying genetic mechanisms for these associations remain largely unknown. The aim of this study is to apply cross-trait genetic analyses to investigate the potentially shared biology among PD, T2D, and bone mineral density (BMD) by assessing pairwise genetic correlations and searching for shared polymorphisms. We applied cross-trait genetic analyses leveraging genome-wide association study (GWAS) summary statistics for: Periodontitis/loose teeth from the UKBB/GLIDE consortium (PerioLT, N=506594), T2D from the DIAGRAM consortium (Neff=228825), and BMD from the GEFOS consortium (N=426824). Among all three, pair-wise genetic correlations were estimated with linkage disequilibrium (LD) score regression. Multi-trait meta-analysis of GWAS (MTAG) and colocalization analyses were performed to discover shared genome-wide significant variants (pMTAG <5x10-8). For replication, we conducted independent genetic analyses in the Women's Genome Health Study (WGHS), a prospective cohort study of middle-aged women of whom 14711 provided self-reported periodontal disease diagnosis, oral health measures, and periodontal risk factor data including incident T2D. Significant genetic correlations were identified between PerioLT/T2D (Rg=0.23; SE=0.04; p=7.4e-09) and T2D/BMD (Rg=0.09; SE=0.02; p=9.8e-06). Twenty-one independent pleiotropic variants were identified via MTAG (pMTAG<5x10-8 across all traits). Of these variants, genetic signals for PerioLT and T2D colocalized at one candidate variant (rs17522122; ProbH4 = 0.58), a 3'UTR variant of AKAP6. Colocalization between T2D/BMD and the original PerioLT GWAS p-values suggested 14 additional loci. In the independent WGHS sample, which includes responses to a validated oral health questionnaire for PD surveillance, the primary shared candidate (rs17522122) was associated with less frequent dental flossing [OR(95%CI)= 0.92 (0.87-0.98), p=0.007], a response that is correlated with worse PD status. Moreover, 4 additional candidate variants were indirectly supported by associations with less frequent dental flossing [rs75933965, 1.17(1.04-1.31), p=0.008], less frequent dental visits [rs77464186, 0.82(0.75-0.91), p=0.0002], less frequent dental prophylaxis [rs67111375, 0.91(0.83-0.99), p=0.03; rs77464186, 0.80(0.72-0.89), p=3.8e-05], or having bone loss around teeth [rs8047395, 1.09(1.03-1.15), p=0.005]. This integrative approach identified one colocalized locus and 14 additional candidate loci that are shared between T2D and PD/oral health by comparing effects across PD, T2D and BMD. Future research is needed to independently validate our findings.

FinnGen provides genetic insights from a well-phenotyped isolated population

Population isolates such as those in Finland benefit genetic research because deleterious alleles are often concentrated on a small number of low-frequency variants (0.1% ≤ minor allele frequency < 5%). These variants survived the founding bottleneck rather than being distributed over a large number of ultrarare variants. Although this effect is well established in Mendelian genetics, its value in common disease genetics is less explored1,2. FinnGen aims to study the genome and national health register data of 500,000 Finnish individuals. Given the relatively high median age of participants (63 years) and the substantial fraction of hospital-based recruitment, FinnGen is enriched for disease end points. Here we analyse data from 224,737 participants from FinnGen and study 15 diseases that have previously been investigated in large genome-wide association studies (GWASs). We also include meta-analyses of biobank data from Estonia and the United Kingdom. We identified 30 new associations, primarily low-frequency variants, enriched in the Finnish population. A GWAS of 1,932 diseases also identified 2,733 genome-wide significant associations (893 phenome-wide significant (PWS), P < 2.6 × 10–11) at 2,496 (771 PWS) independent loci with 807 (247 PWS) end points. Among these, fine-mapping implicated 148 (73 PWS) coding variants associated with 83 (42 PWS) end points. Moreover, 91 (47 PWS) had an allele frequency of <5% in non-Finnish European individuals, of which 62 (32 PWS) were enriched by more than twofold in Finland. These findings demonstrate the power of bottlenecked populations to find entry points into the biology of common diseases through low-frequency, high impact variants.

Prostasomes as interlocutor for zygotic epigenome health: role of prostasomesecretome in maintenance of zygotic epigenome

Prostasomes as transgenerational epigenetic tool box has not been established, its role in transferring small RNA, lncRNA as paternal messages is yet to be explored. The present study was undertaken to establish role of prostasomes in modulating testicular and vaginal environmental cues such as protein and RNA messages through to zygote and thereby actin gas interlocutor of paternal genome. The results from the study found out prostasomes fusion with spermatozoa takes place at the time of maturation and capacitation wherein it causes downregulation of ROS (Protein and mRNA) in terms of decreased NADPH and NOS activity significantly (p&lt;0.01), it was also found to modulate mitochondrial membrane potential significantly(p&lt;0.01). Prostasome supplementation lead to increased survival of spermatozoa in sp-TALP medium and was found to be superior to cryopreserved and fresh semen when used in routine in vitro fertilization (IVF) experiment. The study further envisages to establish prostasomes as repository of novel biomarkers for infertility in male and female and as diagnostic tool in in vitro fertilization and somatic cell nuclear transfer protocol and thereby establishing prostasomes as one of the fundamental vesicles influencing transgenerational transfer of RNA and protein to zygotic genome thereby influencing zygotic genome health.

Variance-quantitative trait loci enable systematic discovery of gene-environment interactions for cardiometabolic serum biomarkers

Gene-environment interactions represent the modification of genetic effects by environmental exposures and are critical for understanding disease and informing personalized medicine. These often induce differential phenotypic variance across genotypes; these variance-quantitative trait loci can be prioritized in a two-stage interaction detection strategy to greatly reduce the computational and statistical burden and enable testing of a broader range of exposures. We perform genome-wide variance-quantitative trait locus analysis for 20 serum cardiometabolic biomarkers by multi-ancestry meta-analysis of 350,016 unrelated participants in the UK Biobank, identifying 182 independent locus-biomarker pairs (p < 4.5×10−9). Most are concentrated in a small subset (4%) of loci with genome-wide significant main effects, and 44% replicate (p < 0.05) in the Women’s Genome Health Study (N = 23,294). Next, we test each locus-biomarker pair for interaction across 2380 exposures, identifying 847 significant interactions (p < 2.4×10−7), of which 132 are independent (p < 0.05) after accounting for correlation between exposures. Specific examples demonstrate interaction of triglyceride-associated variants with distinct body mass- versus body fat-related exposures as well as genotype-specific associations between alcohol consumption and liver stress at the ADH1B gene. Our catalog of variance-quantitative trait loci and gene-environment interactions is publicly available in an online portal.

The relevance of genomics in health visiting

Health Education England deems genomics a potentially powerful addition to a health visitor's toolkit for supporting families. Dave Hancock explains what you can expect to learn from their new resources

Identification of gene signatures for COAD using feature selection and Bayesian network approaches

The combination of TCGA and GTEx databases will provide more comprehensive information for characterizing the human genome in health and disease, especially for underlying the cancer genetic alterations. Here we analyzed the gene expression profile of COAD in both tumor samples from TCGA and normal colon tissues from GTEx. Using the SNR-PPFS feature selection algorithms, we discovered a 38 gene signatures that performed well in distinguishing COAD tumors from normal samples. Bayesian network of the 38 genes revealed that DEGs with similar expression patterns or functions interacted more closely. We identified 14 up-DEGs that were significantly correlated with tumor stages. Cox regression analysis demonstrated that tumor stage, STMN4 and FAM135B dysregulation were independent prognostic factors for COAD survival outcomes. Overall, this study indicates that using feature selection approaches to select key gene signatures from high-dimensional datasets can be an effective way for studying cancer genomic characteristics.

Accurate and efficient privacy-preserving string matching

The task of calculating similarities between strings held by different organisations without revealing these strings is an increasingly important problem in areas such as health informatics, national censuses, genomics, and fraud detection. Most existing privacy-preserving string matching approaches are either based on comparing sets of encoded characters allowing only exact matching of encoded strings, or they are aimed at long genomics sequences that have a small alphabet. The set-based privacy-preserving similarity functions that are commonly used to compare name and address strings in the context of privacy-preserving record linkage do not take the positions of sub-strings into account. As a result, two very different strings can potentially be considered as a match leading to wrongly linked records. Furthermore, existing set-based techniques cannot identify the length of the longest common sub-string across two strings. In this paper, we propose two new approaches for accurate and efficient privacy-preserving string matching that provide privacy against various attacks. In the first approach we apply hashing-based encoding on sub-strings (q-grams) to compare sensitive strings, while in the second approach we generate one-bit array from the sub-strings of a string to identify the longest common bit sequences. We evaluate our approaches on several data sets with different types of strings, and validate their privacy, accuracy, and complexity compared to three baseline techniques, showing that they outperform all baselines.

A Mild Causal Relationship Between Tea Consumption and Obesity in General Population: A Two-Sample Mendelian Randomization Study.

Evidence from observational studies for the effect of tea consumption on obesity is inconclusive. This study aimed to verify the causal association between tea consumption and obesity through a two-sample Mendelian randomization (MR) analysis in general population-based datasets. The genetic instruments, single nucleotide polymorphisms (SNPs) associated with tea consumption habits, were obtained from genome-wide association studies (GWAS): UK Biobank, Nurses’ Health Study, Health Professionals Follow-up Study, and Women’s Genome Health Study. The effect of the genetic instruments on obesity was analyzed using the UK Biobank dataset (among ∼500,000 participants). The causal relationship between tea consumption and obesity was analyzed by five methods of MR analyses: inverse variance weighted (IVW) method, MR-Egger regression method, weighted median estimator (WME), weighted mode, and simple mode. Ninety-one SNPs were identified as genetic instruments in our study. A mild causation was found by IVW (odds ratio [OR] = 0.998, 95% confidence interval [CI] = 0.996 to 1.000, p = 0.049]), which is commonly used in two-sample MR analysis, indicating that tea consumption has a statistically significant but medically weak effect on obesity control. However, the other four approaches did not show significance. Since there was no heterogeneity and pleiotropy in this study, the IVW approach has the priority of recommendation. Further studies are needed to clarify the effects of tea consumption on obesity-related health problems in detail.

Genome-wide association of individual vulnerability with alcohol-associated liver disease: A Korean genome and epidemiology study.

Background and aimsThe quantity of alcohol leading to alcohol‐associated liver disease (ALD) varies individually. Genetic backgrounds contributing to the divergence in individual susceptibility to alcohol‐induced liver damage have not been elucidated in detail.Approach and resultsBased on the Korean Genome and Epidemiology Study Health Examination (KoGES_HEXA) cohort data, 21,919 participants (40‐79 years old) were included and divided into cases and controls based on the ALD diagnostic criteria proposed by the American College of Gastroenterology. Data generated by a genome wide‐association study were analyzed using logistic regression to assess the risk of ALD development in nondrinkers, light drinkers, and heavy drinkers. We detected three loci, gamma‐glutamyltransferase 1 (GGT1), zinc protein finger 827 (ZNF827) and HNF1 homeobox A (HNF1A), which were significantly associated with ALD risk. The GGT1 rs2006227 minor allele was strongly associated with all groups. Among the minor alleles of single nucleotide polymorphisms (SNPs) in HNF1A, rs1183910 had the strongest association with a protective effect from ALD in light drinkers. However, this association was not observed in heavy drinkers. Five SNPs on chromosome 11 showed suggestive significance in protective effects against ALD.ConclusionsSNPs, including HNF1A rs1183910 minor allele, are the most promising genetic candidates for protection against ALD. The expression of genes contributing to ALD development may be altered by the amount of alcohol consumed.

Sequencing SARS-CoV-2 in a Malaria Research Laboratory in Mali, West Africa: The Road to Sequencing the First SARS-CoV-2 Genome in Mali

Next-generation sequencing (NGS) has become a necessary tool for genomic epidemiology. Even though the utility of genomics in human health has been proved, genomic surveillance has never been as important as during the COVID-19 pandemic. This has been demonstrated by the recent use of genomic surveillance to detect new variants of SARS-CoV-2 in the United Kingdom, South Africa, and Brazil. Until recently, Malian scientists did not have access to any local NGS platform, and samples had to be shipped abroad for sequencing. Here, we report on how we adapted a laboratory setup for Plasmodium research to generate the first complete SARS-CoV-2 genome locally. Total RNA underwent a library preparation using an Illumina TruSeq stranded RNA kit. A metagenomics sequencing was performed on an Illumina MiSeq platform, which was followed by bioinformatic analyses on a local server in Mali. We recovered a full genome of SARS-CoV-2 of 29 kb with an average depth coverage of 200×. We have demonstrated our capacity to generate a high-quality genome with limited resources and highlight the need to develop genomics capacity locally to solve health problems. We discuss challenges related to access to reagents during a pandemic period and propose some home-made solutions.

Phenotypic and Genotypic Associations Between Migraine and Lipoprotein Subfractions.

To evaluate phenotypic and genetic relationships between migraine and lipoprotein subfractions. We evaluated phenotypic associations between migraine and 19 lipoprotein subfraction measures in the Women's Genome Health Study (n = 22,788). We then investigated genetic relationships between these traits using summary statistics from the International Headache Genetics Consortium for migraine (ncase = 54,552, ncontrol = 297,970) and combined summary data for lipoprotein subfractions (n up to 47,713). There was a significant phenotypic association (odds ratio 1.27 [95% confidence interval 1.12-1.44]) and a significant genetic correlation at 0.18 (p = 0.001) between migraine and triglyceride-rich lipoproteins (TRLPs) concentration but not for low-density lipoprotein or high-density lipoprotein subfractions. Mendelian randomization (MR) estimates were largely null, implying that pleiotropy rather than causality underlies the genetic correlation between migraine and lipoprotein subfractions. Pleiotropy was further supported in cross-trait meta-analysis, revealing significant shared signals at 4 loci (chr2p21 harboring THADA, chr5q13.3 harboring HMGCR, chr6q22.31 harboring HEY2, and chr7q11.23 harboring MLXIPL) between migraine and lipoprotein subfractions. Three of these loci were replicated for migraine (p < 0.05) in a smaller sample from the UK Biobank. The shared signal at chr5q13.3 colocalized with expression of HMGCR, ANKDD1B, and COL4A3BP in multiple tissues. The study supports the association between certain lipoprotein subfractions, especially for TRLP, and migraine in populations of European ancestry. The corresponding shared genetic components may help identify potential targets for future migraine therapeutics. This study provides Class I evidence that migraine is significantly associated with some lipoprotein subfractions.