Metadata for Data dIscoverability aNd Study rEplicability in obseRVAtional Studies (MINERVA): Development and Pilot of a Metadata List and Catalogue in Europe.

PURPOSE: Metadata for data dIscoverability aNd study rEplicability in obseRVAtional studies (MINERVA), a European Medicines Agency-funded project (EUPAS39322), defined a set of metadata to describe real-world data sources (RWDSs) and piloted metadata collection in a prototype catalogue to assist investigators from data source discoverability through study conduct. METHODS: A list of metadata was created from a review of existing metadata catalogues and recommendations, structured interviews, a stakeholder survey, and a technical workshop. The prototype was designed to comply with the FAIR principles (findable, accessible, interoperable, reusable), using MOLGENIS software. Metadata collection was piloted by 15 data access partners (DAPs) from across Europe. RESULTS: A total of 442 metadata variables were defined in six domains: institutions (organizations connected to a data source); data banks (data collections sustained by an organization); data sources (collections of linkable data banks covering a common underlying population); studies; networks (of institutions); and common data models (CDMs). A total of 26 institutions were recorded in the prototype. Each DAP populated the metadata of one data source and its selected data banks. The number of data banks varied by data source; the most common data banks were hospital administrative records and pharmacy dispensation records (10 data sources each). Quantitative metadata were successfully extracted from three data sources conforming to different CDMs and entered into the prototype. CONCLUSIONS: A metadata list was finalized, a prototype was successfully populated, and a good practice guide was developed. Setting up and maintaining a metadata catalogue on RWDSs will require substantial effort to support discoverability of data sources and reproducibility of studies in Europe.

Genome-wide meta-analyses of restless legs syndrome yield insights into genetic architecture, disease biology and risk prediction.

Restless legs syndrome (RLS) affects up to 10% of older adults. Their healthcare is impeded by delayed diagnosis and insufficient treatment. To advance disease prediction and find new entry points for therapy, we performed meta-analyses of genome-wide association studies in 116,647 individuals with RLS (cases) and 1,546,466 controls of European ancestry. The pooled analysis increased the number of risk loci eightfold to 164, including three on chromosome X. Sex-specific meta-analyses revealed largely overlapping genetic predispositions of the sexes (rg = 0.96). Locus annotation prioritized druggable genes such as glutamate receptors 1 and 4, and Mendelian randomization indicated RLS as a causal risk factor for diabetes. Machine learning approaches combining genetic and nongenetic information performed best in risk prediction (area under the curve (AUC) = 0.82-0.91). In summary, we identified targets for drug development and repurposing, prioritized potential causal relationships between RLS and relevant comorbidities and risk factors for follow-up and provided evidence that nonlinear interactions are likely relevant to RLS risk prediction.

Transcriptome analysis reveals involvement of thiopurine S-methyltransferase in oxidation-reduction processes.

Thiopurine S-methyltransferase (TPMT) is an important enzyme involved in the deactivation of thiopurines and represents a major determinant of thiopurine-related toxicities. Despite its well-known importance in thiopurine metabolism, the understanding of its endogenous role is lacking. In the present study, we aimed to gain insight into the molecular processes involving TPMT by applying a data fusion approach to analyze whole-genome expression data. The RNA profiling was done on whole blood samples from 1017 adult male and female donors to the Estonian biobank using Illumina HTv3 arrays. Our results suggest that TPMT is closely related to genes involved in oxidoreductive processes. The in vitro experiments on different cell models confirmed that TPMT influences redox capacity of the cell by altering S-adenosylmethionine (SAM) consumption and consequently glutathione (GSH) synthesis. Furthermore, by comparing gene networks of subgroups of individuals, we identified genes, which could have a role in regulating TPMT activity. The biological relevance of identified genes and pathways will have to be further evaluated in molecular studies.

HLA allele-calling using multi-ancestry whole-exome sequencing from the UK Biobank identifies 129 novel associations in 11 autoimmune diseases.

The human leukocyte antigen (HLA) region on chromosome 6 is strongly associated with many immune-mediated and infection-related diseases. Due to its highly polymorphic nature and complex linkage disequilibrium patterns, traditional genetic association studies of single nucleotide polymorphisms do not perform well in this region. Instead, the field has adopted the assessment of the association of HLA alleles (i.e., entire HLA gene haplotypes) with disease. Often based on genotyping arrays, these association studies impute HLA alleles, decreasing accuracy and thus statistical power for rare alleles and in non-European ancestries. Here, we use whole-exome sequencing (WES) from 454,824 UK Biobank (UKB) participants to directly call HLA alleles using the HLA-HD algorithm. We show this method is more accurate than imputing HLA alleles and harness the improved statistical power to identify 360 associations for 11 auto-immune phenotypes (at least 129 likely novel), leading to better insights into the specific coding polymorphisms that underlie these diseases. We show that HLA alleles with synonymous variants, often overlooked in HLA studies, can significantly influence these phenotypes. Lastly, we show that HLA sequencing may improve polygenic risk scores accuracy across ancestries. These findings allow better characterization of the role of the HLA region in human disease.

Global Effect of Modifiable Risk Factors on Cardiovascular Disease and Mortality.

BACKGROUND: Five modifiable risk factors are associated with cardiovascular disease and death from any cause. Studies using individual-level data to evaluate the regional and sex-specific prevalence of the risk factors and their effect on these outcomes are lacking. METHODS: We pooled and harmonized individual-level data from 112 cohort studies conducted in 34 countries and 8 geographic regions participating in the Global Cardiovascular Risk Consortium. We examined associations between the risk factors (body-mass index, systolic blood pressure, non-high-density lipoprotein cholesterol, current smoking, and diabetes) and incident cardiovascular disease and death from any cause using Cox regression analyses, stratified according to geographic region, age, and sex. Population-attributable fractions were estimated for the 10-year incidence of cardiovascular disease and 10-year all-cause mortality. RESULTS: Among 1,518,028 participants (54.1% of whom were women) with a median age of 54.4 years, regional variations in the prevalence of the five modifiable risk factors were noted. Incident cardiovascular disease occurred in 80,596 participants during a median follow-up of 7.3 years (maximum, 47.3), and 177,369 participants died during a median follow-up of 8.7 years (maximum, 47.6). For all five risk factors combined, the aggregate global population-attributable fraction of the 10-year incidence of cardiovascular disease was 57.2% (95% confidence interval [CI], 52.4 to 62.1) among women and 52.6% (95% CI, 49.0 to 56.1) among men, and the corresponding values for 10-year all-cause mortality were 22.2% (95% CI, 16.8 to 27.5) and 19.1% (95% CI, 14.6 to 23.6). CONCLUSIONS: Harmonized individual-level data from a global cohort showed that 57.2% and 52.6% of cases of incident cardiovascular disease among women and men, respectively, and 22.2% and 19.1% of deaths from any cause among women and men, respectively, may be attributable to five modifiable risk factors. (Funded by the German Center for Cardiovascular Research (DZHK); ClinicalTrials.gov number, NCT05466825.).

Genome-wide meta-analysis identifies novel loci conferring risk of acne vulgaris.

Acne vulgaris is a common chronic skin disorder presenting with comedones, cystic structures forming within the distal hair follicle, and in most cases additionally with inflammatory skin lesions on the face and upper torso. We performed a genome-wide association study and meta-analysis of data from 34,422 individuals with acne and 364,991 controls from three independent European-ancestry cohorts. We replicated 19 previously implicated genome-wide significant risk loci and identified four novel loci [11q12.2 (FADS2), 12q21.1 (LGR5), 17q25.3 (FASN), and 22q12.1 (ZNRF3-KREMEN1)], bringing the total number of reported acne risk loci to 50. Our meta-analysis results explain 9.4% of the phenotypic variance of acne. A polygenic model of acne risk variants showed that individuals in the top 5% of the risk percentiles had a 1.62-fold (95% CI 1.47-1.78) increased acne risk relative to individuals with average risk (20-80% on the polygenic risk score distribution). Our findings highlight the Wnt and MAPK pathways as key factors in the genetic predisposition to acne vulgaris, together with the effects of genetic variation on the structure and maintenance of the hair follicle and pilosebaceous unit. Two novel loci, 11q12.2 and 17q25.3, contain genes encoding key enzymes involved in lipid biosynthesis pathways.

Genome-wide screen of otosclerosis in population biobanks: 27 loci and shared associations with skeletal structure.

Otosclerosis is one of the most common causes of conductive hearing loss, affecting 0.3% of the population. It typically presents in adulthood and half of the patients have a positive family history. The pathophysiology of otosclerosis is poorly understood. A previous genome-wide association study (GWAS) identified a single association locus in an intronic region of RELN. Here, we report a meta-analysis of GWAS studies of otosclerosis in three population-based biobanks comprising 3504 cases and 861,198 controls. We identify 23 novel risk loci (p < 5 × 10-8) and report an association in RELN and three previously reported candidate gene or linkage regions (TGFB1, MEPE, and OTSC7). We demonstrate developmental stage-dependent immunostaining patterns of MEPE and RUNX2 in mouse otic capsules. In most association loci, the nearest protein-coding genes are implicated in bone remodelling, mineralization or severe skeletal disorders. We highlight multiple genes involved in transforming growth factor beta signalling for follow-up studies.

Rare variant analyses across multiethnic cohorts identify novel genes for refractive error.

Refractive error, measured here as mean spherical equivalent (SER), is a complex eye condition caused by both genetic and environmental factors. Individuals with strong positive or negative values of SER require spectacles or other approaches for vision correction. Common genetic risk factors have been identified by genome-wide association studies (GWAS), but a great part of the refractive error heritability is still missing. Some of this heritability may be explained by rare variants (minor allele frequency [MAF] ≤ 0.01.). We performed multiple gene-based association tests of mean Spherical Equivalent with rare variants in exome array data from the Consortium for Refractive Error and Myopia (CREAM). The dataset consisted of over 27,000 total subjects from five cohorts of Indo-European and Eastern Asian ethnicity. We identified 129 unique genes associated with refractive error, many of which were replicated in multiple cohorts. Our best novel candidates included the retina expressed PDCD6IP, the circadian rhythm gene PER3, and P4HTM, which affects eye morphology. Future work will include functional studies and validation. Identification of genes contributing to refractive error and future understanding of their function may lead to better treatment and prevention of refractive errors, which themselves are important risk factors for various blinding conditions.

Lessons learned during the process of reporting individual genomic results to participants of a population-based biobank.

The return of individual genomic results (ROR) to research participants is still in its early phase, and insight on how individuals respond to ROR is scarce. Studies contributing to the evidence base for best practices are crucial before these can be established. Here, we describe a ROR procedure conducted at a population-based biobank, followed by surveying the responses of almost 3000 participants to a range of results, and discuss lessons learned from the process, with the aim of facilitating large-scale expansion. Overall, participants perceived the information that they received with counseling as valuable, even when the reporting of high risks initially caused worry. The face-to-face delivery of results limited the number of participants who received results. Although the participants highly valued this type of communication, additional means of communication need to be considered to improve the feasibility of large-scale ROR. The feedback collected sheds light on the value judgements of the participants and on potential responses to the receipt of genetic risk information. Biobanks in other countries are planning or conducting similar projects, and the sharing of lessons learned may provide valuable insight and aid such endeavors.

Genetic and modifiable risk factors combine multiplicatively in common disease.

BACKGROUND: The joint contribution of genetic and environmental exposures to noncommunicable diseases is not well characterized. OBJECTIVES: We modeled the cumulative effects of common risk alleles and their prevalence variations with classical risk factors. METHODS: We analyzed mathematically and statistically numbers and effect sizes of established risk alleles for coronary artery disease (CAD) and other conditions. RESULTS: In UK Biobank, risk alleles counts in the lowest (175.4) and highest decile (205.7) of the distribution differed by only 16.9%, which nevertheless increased CAD prevalence 3.4-fold (p < 0.01). Irrespective of the affected gene, a single risk allele multiplied the effects of all others carried by a person, resulting in a 2.9-fold stronger effect size in the top versus the bottom decile (p < 0.01) and an exponential increase in risk (R > 0.94). Classical risk factors shifted effect sizes to the steep upslope of the logarithmic function linking risk allele numbers with CAD prevalence. Similar phenomena were observed in the Estonian Biobank and for risk alleles affecting diabetes mellitus, breast and prostate cancer. CONCLUSIONS: Alleles predisposing to common diseases can be carried safely in large numbers, but few additional ones lead to sharp risk increments. Here, we describe exponential functions by which risk alleles combine interchangeably but multiplicatively with each other and with modifiable risk factors to affect prevalence. Our data suggest that the biological systems underlying these diseases are modulated by hundreds of genes but become only fragile when a narrow window of total risk, irrespective of its genetic or environmental origins, has been passed.

Precise, Genotype-First Breast Cancer Prevention: Experience With Transferring Monogenic Findings From a Population Biobank to the Clinical Setting.

Although hereditary breast cancer screening and management are well accepted and established in clinical settings, these efforts result in the detection of only a fraction of genetic predisposition at the population level. Here, we describe our experience from a national pilot study (2018-2021) in which 180 female participants of Estonian biobank (of >150,000 participants in total) were re-contacted to discuss personalized clinical prevention measures based on their genetic predisposition defined by 11 breast cancer-related genes. Our results show that genetic risk variants are relatively common in the average-risk Estonian population. Seventy-five percent of breast cancer cases in at-risk subjects occurred before the age of 50 years. Only one-third of subjects would have been eligible for clinical screening according to the current criteria. The participants perceived the receipt of genetic risk information as valuable. Fluent cooperation of project teams supported by state-of-art data management, quality control, and secure transfer can enable the integration of research results to everyday medical practice in a highly efficient, timely, and well-accepted manner. The positive experience in this genotype-first breast cancer study confirms the value of using existing basic genomic data from population biobanks for precise prevention.

Do Biobank Recall Studies Matter? Long-Term Follow-Up of Research Participants With Familial Hypercholesterolemia.

Recall-by-genotype (RbG) studies conducted with population-based biobank data remain urgently needed, and follow-up RbG studies, which add substance to this research approach, remain solitary. In such studies, potentially disease-related genotypes are identified and individuals with those genotypes are recalled for consultation to gather more detailed clinical phenotypic information and explain to them the meaning of their genetic findings. Familial hypercholesterolemia (FH) is among the most common autosomal-dominant single-gene disorders, with a global prevalence of 1 in 500 (Nordestgaard et al., Eur. Heart J., 2013, 34 (45), 3478-3490). Untreated FH leads to lifelong elevated LDL cholesterol levels, which can cause ischemic heart disease, with potentially fatal consequences at a relatively early age. In most cases, the pathogenesis of FH is based on a defect in one of three LDL receptor-related genes-APOB, LDLR, and PCSK9. We present our first long-term follow-up RbG study of FH, conducted within the Estonian Biobank (34 recalled participants from a pilot RbG study and 291 controls harboring the same APOB, LDLR, and PCSK9 variants that were included in the pilot study). The participants' electronic health record data (FH-related diagnoses, lipid-lowering treatment prescriptions) and pharmacogenomic risk of developing statin-induced myopathy were assessed. A survey was administered to recalled participants to discern the impact of the knowledge of their genetic findings on their lives 4-6 years later. Significant differences in FH diagnoses and lipid-lowering treatment prescriptions were found between the recalled participants and controls (34 and 291 participants respectively). Our study highlights the need for more consistent lipid-lowering treatment adherence checkups and encourage more follow-up RbG studies to be performed.

Differential and shared genetic effects on kidney function between diabetic and non-diabetic individuals.

Reduced glomerular filtration rate (GFR) can progress to kidney failure. Risk factors include genetics and diabetes mellitus (DM), but little is known about their interaction. We conducted genome-wide association meta-analyses for estimated GFR based on serum creatinine (eGFR), separately for individuals with or without DM (nDM = 178,691, nnoDM = 1,296,113). Our genome-wide searches identified (i) seven eGFR loci with significant DM/noDM-difference, (ii) four additional novel loci with suggestive difference and (iii) 28 further novel loci (including CUBN) by allowing for potential difference. GWAS on eGFR among DM individuals identified 2 known and 27 potentially responsible loci for diabetic kidney disease. Gene prioritization highlighted 18 genes that may inform reno-protective drug development. We highlight the existence of DM-only and noDM-only effects, which can inform about the target group, if respective genes are advanced as drug targets. Largely shared effects suggest that most drug interventions to alter eGFR should be effective in DM and noDM.

Spectrum and frequency of CHEK2 variants in breast cancer affected and general population in the Baltic states region, initial results and literature review.

BACKGROUND: While BRCA1/2 gene mutational spectrum and clinical features are widely studied, there is limited data on breast cancer-predisposing non-BRCA pathogenic/likely pathogenic variants (PV/LPVs) in the Baltic states region. According to previous studies, CHEK2 is the most frequent moderate-risk breast cancer predisposition gene. The study aimed to analyse the frequency and mutational spectrum of CHEK2 PV/LPVs in the Baltic states region and perform a literature review on the subject. METHODS: The study includes two cohorts - population-based Estonian biobank (EstBB) (N-152 349) and breast cancer affected cases from Latvia (N-105). In the cohort from Latvia, CHEK2, BRCA1, BRCA2, PALB2 testing with next-generation sequencing (NGS) was carried out in selected breast cancer cases. In the EstBB, the full SNP genotyped dataset Global Screening Array (GSA) (N-152 349) was used to screen CHEK2 PV/LPVs and variants c.319+2T > A (p.(?)), c.444+1G>A (p.(?)), c.433C > T (p.Arg145Trp), c.283C > T (p.Arg95*) in CHEK2 are reported from this dataset. In addition, a subset of the EstBB (N-4776) underwent whole-genome sequencing (WGS, N-2420) and whole-exome sequencing (WES, N-2356) and founder variants c.470T > C (p.Ile157Thr), c.444+1G>A (p.(?)), c.1100delC (p.Thr367Metfs*15) in CHEK2 were reported from this dataset. Moreover, a literature overview was performed on April 1, 2021, using the PubMed search of keywords 'CHEK2', 'breast cancer', 'Estonia', 'Lithuania', 'Latvia', 'Poland', 'Belarus' and 'Russia'. RESULTS: In the breast cancer affected cohort from Latvia 6 CHEK2 variants, classified as PV/LPVs, were observed (6/105; 5.7%), including recurrent ones c.470T > C (p.Ile157Thr) (1.9%) and del5395(ex9-10del; (p.Met304Leufs*16)) (1.9%), as well as single ones - c.1100delC (p.Thr367Metfs*15) (1%) and c.444+1G>A (p.(?)) (1%). From EstBB NGS data (N-4776) CHEK2 variant c.470T > C (p.Ile157Thr) was detected in 8.6% of cases, c.1100delC (p.Thr367Metfs*15) in 0.6% and c.444+1G>A (p.(?)) in 0.2% of cases. In the EstBB full cohort of SNP array data (N-152 349) CHEK2 variant c.444+1G>A (p.(?)) was detected in 0.02% of cases, c.319+2T > A (p.(?)) in 0.09% of cases, c.433C > T (p.Arg145Trp) in 0.02% of cases and c.283C > T (p.Arg95*) in <0.001% of cases. For the literature review altogether, 49 PubMed articles were found, 23 of which were relevant, representing CHEK2 PV/LPVs in the population of interest. Ten publications are from Poland, eight from Russia, three from Latvia and two from Belarus. CONCLUSIONS: This study is the first combined report on complete CHEK2 PV/LPVs screening in selected breast cancer affected cases in Latvia and large-scale population screening in Estonia, providing insight into the CHEK2 mutational spectrum in the Baltic states region. The initial results are in line with other studies that CHEK2 PV/LPVs frequency is around 5-6% of selected breast cancer cases. Here we report three CHEK2 PV/LPV - c.319+2T > A (p.(?)), c.433C > T (p.Arg145Trp), c.283C > T (p.Arg95*), that are novel for the Baltic states region. This is also the first report on c.1100delC (p.Thr367Metfs*15) and c.444+1G>A (p.(?)) from the Baltic states. High population frequency of c.470T > C (p. Ile157Thr) (8.6%) continues to question the variant's pathogenicity in particular populations. Other findings are concordant with previous reports from Latvia and neighbouring populations.

Gut metagenome associations with extensive digital health data in a volunteer-based Estonian microbiome cohort.

Microbiome research is starting to move beyond the exploratory phase towards interventional trials and therefore well-characterized cohorts will be instrumental for generating hypotheses and providing new knowledge. As part of the Estonian Biobank, we established the Estonian Microbiome Cohort which includes stool, oral and plasma samples from 2509 participants and is supplemented with multi-omic measurements, questionnaires, and regular linkages to national electronic health records. Here we analyze stool data from deep metagenomic sequencing together with rich phenotyping, including 71 diseases, 136 medications, 21 dietary questions, 5 medical procedures, and 19 other factors. We identify numerous relationships (n = 3262) with different microbiome features. In this study, we extend the understanding of microbiome-host interactions using electronic health data and show that long-term antibiotic usage, independent from recent administration, has a significant impact on the microbiome composition, partly explaining the common associations between diseases.

Impact of the pre-examination phase on multicenter metabolomic studies.

The development of metabolomics in clinical applications has been limited by the lack of validation in large multicenter studies. Large population cohorts and their biobanks are a valuable resource for acquiring insights into molecular disease mechanisms. Nevertheless, most of their collections are not tailored for metabolomics and have been created without specific attention to the pre-analytical requirements for high-quality metabolome assessment. Thus, comparing samples obtained by different pre-analytical procedures remains a major challenge. Here, 1H NMR-based analyses are used to demonstrate how human serum and plasma samples collected with different operating procedures within several large European cohort studies from the Biobanking and Biomolecular Resources Infrastructure - Large Prospective Cohorts (BBMRI-LPC) consortium can be easily revealed by supervised multivariate statistical analyses at the initial stages of the process, to avoid biases in the downstream analysis. The inter-biobank differences are discussed in terms of deviations from the validated CEN/TS 16945:2016 / ISO 23118:2021 norms. It clearly emerges that biobanks must adhere to the evidence-based guidelines in order to support wider-scale application of metabolomics in biomedicine, and that NMR spectroscopy is informative in comparing the quality of different sample sources in multi cohort/center studies.