Genetic determinants of plasma protein levels in the Estonian population.

The proteome holds great potential as an intermediate layer between the genome and phenome. Previous protein quantitative trait locus studies have focused mainly on describing the effects of common genetic variations on the proteome. Here, we assessed the impact of the common and rare genetic variations as well as the copy number variants (CNVs) on 326 plasma proteins measured in up to 500 individuals. We identified 184 cis and 94 trans signals for 157 protein traits, which were further fine-mapped to credible sets for 101 cis and 87 trans signals for 151 proteins. Rare genetic variation contributed to the levels of 7 proteins, with 5 cis and 14 trans associations. CNVs were associated with the levels of 11 proteins (7 cis and 5 trans), examples including a 3q12.1 deletion acting as a hub for multiple trans associations; and a CNV overlapping NAIP, a sensor component of the NAIP-NLRC4 inflammasome which is affecting pro-inflammatory cytokine interleukin 18 levels. In summary, this work presents a comprehensive resource of genetic variation affecting the plasma protein levels and provides the interpretation of identified effects.

A Large-Scale Genome-Wide Study of Gene-Sleep Duration Interactions for Blood Pressure in 811,405 Individuals from Diverse Populations.

Although both short and long sleep duration are associated with elevated hypertension risk, our understanding of their interplay with biological pathways governing blood pressure remains limited. To address this, we carried out genome-wide cross-population gene-by-short-sleep and long-sleep duration interaction analyses for three blood pressure traits (systolic, diastolic, and pulse pressure) in 811,405 individuals from diverse population groups. We discover 22 novel gene-sleep duration interaction loci for blood pressure, mapped to genes involved in neurological, thyroidal, bone metabolism, and hematopoietic pathways. Non-overlap between short sleep (12) and long sleep (10) interactions underscores the plausibility of distinct influences of both sleep duration extremes in cardiovascular health. With several of our loci reflecting specificity towards population background or sex, our discovery sheds light on the importance of embracing granularity when addressing heterogeneity entangled in gene-environment interactions, and in therapeutic design approaches for blood pressure management.

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P < 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.

Lifeday coverage of oral anticoagulants and one-year relative survival in patients with atrial fibrillation: a population-based study in Estonia.

BACKGROUND: Routine oral anticoagulation (OAC) is recommended for almost all high-risk patients with atrial fibrillation, yet registries show that OACs are still underused. Our aim was to study the lifeday coverage (LDC) of OAC prescriptions and its relationship with one-year mortality rates of AF patients aged ≥ 65 in Estonia for the years 2019 and 2020. METHODS: Medical data for AF patients aged ≥ 65 years from 2018 and alive as of 01.01.2019 (cohort I) and new AF documentation from 2019 and alive as of 01.01.2020 (cohort II) was obtained from the Health Insurance Fund's electronic database. The data was linked to the nationwide Estonian Medical Prescription Centre's database of prescribed OACs. For LDC analysis, daily doses of guideline-recommended OACs were used. The patients were categorized into three LDC groups: 0%, 1-79%, and ≥ 80%. The data was linked to the Estonian Causes of Death Registry to establish the date of death and mortality rate for the whole Estonian population aged ≥ 65. RESULTS: There were 34,018 patients in cohort I and 9,175 patients with new AF documentation (cohort II), previously not included in cohort I. Of the patients, 77.7% and 68.6% had at least one prescription of OAC in cohorts I and II respectively. 57.4% in cohort I and 44.5% in cohort II had an LDC of ≥ 80%. The relative survival estimates at 1 year for LDC lifeday coverage groups 0%, 1-79%, and ≥ 80% were 91.2%, 98.2%, and 98.5% (cohort I), and 91.9%, 95.2%, and 97.6% (cohort II), respectively. CONCLUSIONS: Despite clear indications for OAC use, LDC is still insufficient and anticoagulation is underused for stroke prevention in Estonia. Further education of the medical community and patients is needed to achieve higher lifeday coverage of prescribed OACs.

Multi-ancestry genome-wide study in >2.5 million individuals reveals heterogeneity in mechanistic pathways of type 2 diabetes and complications.

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes. To characterise the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study (GWAS) data from 2,535,601 individuals (39.7% non-European ancestry), including 428,452 T2D cases. We identify 1,289 independent association signals at genome-wide significance (P<5×10-8) that map to 611 loci, of which 145 loci are previously unreported. We define eight non-overlapping clusters of T2D signals characterised by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial, and enteroendocrine cells. We build cluster-specific partitioned genetic risk scores (GRS) in an additional 137,559 individuals of diverse ancestry, including 10,159 T2D cases, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned GRS are more strongly associated with coronary artery disease and end-stage diabetic nephropathy than an overall T2D GRS across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings demonstrate the value of integrating multi-ancestry GWAS with single-cell epigenomics to disentangle the aetiological heterogeneity driving the development and progression of T2D, which may offer a route to optimise global access to genetically-informed diabetes care.

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.

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.

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.

Omics-informed CNV calls reduce false-positive rates and improve power for CNV-trait associations.

Copy-number variations (CNV) are believed to play an important role in a wide range of complex traits, but discovering such associations remains challenging. While whole-genome sequencing (WGS) is the gold-standard approach for CNV detection, there are several orders of magnitude more samples with available genotyping microarray data. Such array data can be exploited for CNV detection using dedicated software (e.g., PennCNV); however, these calls suffer from elevated false-positive and -negative rates. In this study, we developed a CNV quality score that weights PennCNV calls (pCNVs) based on their likelihood of being true positive. First, we established a measure of pCNV reliability by leveraging evidence from multiple omics data (WGS, transcriptomics, and methylomics) obtained from the same samples. Next, we built a predictor of omics-confirmed pCNVs, termed omics-informed quality score (OQS), using only PennCNV software output parameters. Promisingly, OQS assigned to pCNVs detected in close family members was up to 35% higher than the OQS of pCNVs not carried by other relatives (p < 3.0 × 10-90), outperforming other scores. Finally, in an association study of four anthropometric traits in 89,516 Estonian Biobank samples, the use of OQS led to a relative increase in the trait variance explained by CNVs of up to 56% compared with published quality filtering methods or scores. Overall, we put forward a flexible framework to improve any CNV detection method leveraging multi-omics evidence, applied it to improve PennCNV calls, and demonstrated its utility by improving the statistical power for downstream association analyses.

Markers of Inflammation, Oxidative Stress, and Fibrosis in Patients with Atrial Fibrillation.

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia in clinical practice. The pathogenesis of AF is linked to inflammatory reaction and oxidative stress, which leads to fibrosis of the atria and progression of the disease. The purpose of this study was to define the role of several biomarkers of inflammation, fibrosis, and oxidative stress (OxS). We included 75 patients with paroxysmal/persistent AF, who were admitted for electrical cardioversion or pulmonary vein isolation (PVI). High-sensitivity C-reactive protein (hsCRP), galectin-3 (Gal-3), myeloperoxidase (MPO), oxidized low-density lipoprotein (oxLDL), and N-terminal pro-brain natriuretic peptide (NT-proBNP) were measured before the procedures. We compared the results with those of 75 healthy age-, sex-, and blood pressure-matched individuals. The patients were followed up for 1 year after the intervention to establish the recurrence of AF and its association with the measured markers. Patients with AF had higher MPO (52.6 vs. 36.2 ng/ml, p < 0.001) and NT-proBNP (209.0 vs. 28.0 pg/ml, p < 0.001) compared to healthy subjects. Also, they showed significantly higher levels of hsCRP (1.5 vs. 1.1 mg/l, p = 0.001) and Gal-3 (11.4 vs. 9.7 mg/l, p = 0.003), while there was no difference found in oxLDL (71.5 vs. 71.7 U/l, p = 0.449). MPO (OR = 1.012, p = 0.014), hsCRP (OR = 1.265, p = 0.026), and weight (OR = 1.029, p = 0.013) were independently associated with AF in a multivariable logistic regression analysis. Patients with successful maintenance of sinus rhythm (SR) for one year had lower baseline MPO (40.5 vs. 84.3 ng/ml, p = 0.005) and NT-proBNP (127.5 vs. 694.0 pg/ml, p < 0.001) compared to patients with recurrent AF episodes, but there was no difference in hsCRP, Gal-3, or oxLDL between them. MPO (OR = 0.985, p = 0.010) was independently associated with AF recurrence during the follow-up period when adjusted for cofounders. Patients with AF had increased markers of inflammation and fibrosis, while there was no increase detected in the OxS marker oxLDL. MPO was independently associated with AF in a multivariate model. Inflammatory and fibrotic mechanisms are important factors in electrical and structural remodelling progress in the atria of patients with AF.

Multi-ancestry genetic study of type 2 diabetes highlights the power of diverse populations for discovery and translation.

We assembled an ancestrally diverse collection of genome-wide association studies (GWAS) of type 2 diabetes (T2D) in 180,834 affected individuals and 1,159,055 controls (48.9% non-European descent) through the Diabetes Meta-Analysis of Trans-Ethnic association studies (DIAMANTE) Consortium. Multi-ancestry GWAS meta-analysis identified 237 loci attaining stringent genome-wide significance (P < 5 × 10-9), which were delineated to 338 distinct association signals. Fine-mapping of these signals was enhanced by the increased sample size and expanded population diversity of the multi-ancestry meta-analysis, which localized 54.4% of T2D associations to a single variant with >50% posterior probability. This improved fine-mapping enabled systematic assessment of candidate causal genes and molecular mechanisms through which T2D associations are mediated, laying the foundations for functional investigations. Multi-ancestry genetic risk scores enhanced transferability of T2D prediction across diverse populations. Our study provides a step toward more effective clinical translation of T2D GWAS to improve global health for all, irrespective of genetic background.

A genome-wide association study of outcome from traumatic brain injury.

BACKGROUND: Factors such as age, pre-injury health, and injury severity, account for less than 35% of outcome variability in traumatic brain injury (TBI). While some residual outcome variability may be attributable to genetic factors, published candidate gene association studies have often been underpowered and subject to publication bias. METHODS: We performed the first genome- and transcriptome-wide association studies (GWAS, TWAS) of genetic effects on outcome in TBI. The study population consisted of 5268 patients from prospective European and US studies, who attended hospital within 24 h of TBI, and satisfied local protocols for computed tomography. FINDINGS: The estimated heritability of TBI outcome was 0·26. GWAS revealed no genetic variants with genome-wide significance (p < 5 × 10-8), but identified 83 variants in 13 independent loci which met a lower pre-specified sub-genomic statistical threshold (p < 10-5). Similarly, none of the genes tested in TWAS met tissue-wide significance. An exploratory analysis of 75 published candidate variants associated with 28 genes revealed one replicable variant (rs1800450 in the MBL2 gene) which retained significance after correction for multiple comparison (p = 5·24 × 10-4). INTERPRETATION: While multiple novel loci reached less stringent thresholds, none achieved genome-wide significance. The overall heritability estimate, however, is consistent with the hypothesis that common genetic variation substantially contributes to inter-individual variability in TBI outcome. The meta-analytic approach to the GWAS and the availability of summary data allows for a continuous extension with additional cohorts as data becomes available. FUNDING: A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.

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.

Five-year survival after elective open and endovascular aortic aneurysm repair.

BACKGROUND AND OBJECTIVE: Current evidence suggests short-term survival benefit from endovascular aneurysm repair (EVAR) versus open surgical repair (OSR) in elective abdominal aortic aneurysm (AAA) procedures, but this benefit is lost during long-term follow-up. The aim of this study was to compare short- and mid-term all-cause mortality in patients with non-ruptured aneurysm treated by OSR and EVAR; and to assess the rate of complications and reinterventions, as well as to evaluate their impact on survival. METHODS: The medical records of the non-ruptured AAA patients undergoing OSR or EVAR between 1 January 2011 and 31 December 2019 at Tartu University Hospital, Estonia, were retrospectively reviewed. We gathered survival data from the national registry (mean follow-up period was 3.7 ± 2.3 years). RESULTS: A total of 225 non-ruptured AAA patients were treated operatively out of whom 95 (42.2%) were EVAR and 130 (57.8%) were OSR procedures. The difference in estimated all-cause mortality between the OSR and EVAR groups at day 30 was statistically irrelevant (2.3% vs 0%; p = 0.140), but OSR patients showed statistically significantly higher 5 year survival compared with EVAR patients (75.3% vs 50.0%, p = 0.002). Complication and reintervention rates for the EVAR and OSR groups did not differ statistically (26.3% vs 16.9%, p = 0.122; 10.5% vs 11.5%, p = 0.981, respectively). Multivariate analysis revealed that greater aneurysm diameter (p = 0.012), EVAR procedure (p = 0.016), male gender (p = 0.023), and cerebrovascular diseases (p = 0.028) were independently positively associated with 5-year mortality. CONCLUSIONS: Thirty-day mortality, and complication and reintervention rates for EVAR and OSR after elective AAA repair were similar. Although the EVAR procedure is an independent risk factor for 5-year mortality, higher age and greater proportion of comorbidities among EVAR patients may influence not only the choice of treatment modality, but also prognosis.

Atrial fibrillation is associated with increased central blood pressure and arterial stiffness.

Atrial fibrillation (AF) is the most common arrhythmia in clinical practice and beta blockers (BBs) are the drugs of choice for rate or rhythm control in these patients. The purpose of this study was to describe differences in arterial stiffness (AS), central blood pressure (cBP), and the role of BBs on cBP in patients with AF compared to healthy individuals. The authors included 76 patients with paroxysmal/persistent AF. Carotid-femoral pulse wave velocity (PWV) and cBP were measured and compared with data from 75 healthy individuals. Patients with AF had higher PWV (8.0 m/s vs. 7.2 m/s, p < .001), central systolic blood pressure (cSBP) (118 mm Hg vs. 114 mm Hg, p = .033), central pulse pressure (cPP) (39 mm Hg vs. 37 mm Hg, p = .035) and lower pulse pressure amplification (PPA) (1.24 vs. 1.30, p = .015), without differences in peripheral blood pressure (pBP) and heart rate (HR). AF patients had significantly increased PWV (ß= 0.500, p = .010, adjusted R² = 0.37) after adjustment for confounding factors. The use of BBs significantly reduced PPA (ß = -0.059, p = .017, adjusted R² = 0.30). AF patients have higher PWV, cSBP, cPP, and lower PPA, compared to healthy patients. These findings support the role of AS in the development of AF. Use of BBs is related to a potential adverse effect on cBP.

Phylogenetic history of patrilineages rare in northern and eastern Europe from large-scale re-sequencing of human Y-chromosomes.

The most frequent Y-chromosomal (chrY) haplogroups in northern and eastern Europe (NEE) are well-known and thoroughly characterised. Yet a considerable number of men in every population carry rare paternal lineages with estimated frequencies around 5%. So far, limited sample-sizes and insufficient resolution of genotyping have obstructed a truly comprehensive look into the variety of rare paternal lineages segregating within populations and potential signals of population history that such lineages might convey. Here we harness the power of massive re-sequencing of human Y chromosomes to identify previously unknown population-specific clusters among rare paternal lineages in NEE. We construct dated phylogenies for haplogroups E2-M215, J2-M172, G-M201 and Q-M242 on the basis of 421 (of them 282 novel) high-coverage chrY sequences collected from large-scale databases focusing on populations of NEE. Within these otherwise rare haplogroups we disclose lineages that began to radiate ~1-3 thousand years ago in Estonia and Sweden and reveal male phylogenetic patterns testifying of comparatively recent local demographic expansions. Conversely, haplogroup Q lineages bear evidence of ancient Siberian influence lingering in the modern paternal gene pool of northern Europe. We assess the possible direction of influx of ancestral carriers for some of these male lineages. In addition, we demonstrate the congruency of paternal haplogroup composition of our dataset with two independent population-based cohorts from Estonia and Sweden.

Genotype-first approach to the detection of hereditary breast and ovarian cancer risk, and effects of risk disclosure to biobank participants.

Genotype-first approach allows to systematically identify carriers of pathogenic variants in BRCA1/2 genes conferring a high risk of familial breast and ovarian cancer. Participants of the Estonian biobank have expressed support for the disclosure of clinically significant findings. With an Estonian biobank cohort, we applied a genotype-first approach, contacted carriers, and offered return of results with genetic counseling. We evaluated participants' responses to and the clinical utility of the reporting of actionable genetic findings. Twenty-two of 40 contacted carriers of 17 pathogenic BRCA1/2 variants responded and chose to receive results. Eight of these 22 participants qualified for high-risk assessment based on National Comprehensive Cancer Network criteria. Twenty of 21 counseled participants appreciated being contacted. Relatives of 10 participants underwent cascade screening. Five of 16 eligible female BRCA1/2 variant carriers chose to undergo risk-reducing surgery, and 10 adhered to surveillance recommendations over the 30-month follow-up period. We recommend the return of results to population-based biobank participants; this approach could be viewed as a model for population-wide genetic testing. The genotype-first approach permits the identification of individuals at high risk who would not be identified by application of an approach based on personal and family histories only.

Differences in local population history at the finest level: the case of the Estonian population.

Several recent studies detected fine-scale genetic structure in human populations. Hence, groups conventionally treated as single populations harbour significant variation in terms of allele frequencies and patterns of haplotype sharing. It has been shown that these findings should be considered when performing studies of genetic associations and natural selection, especially when dealing with polygenic phenotypes. However, there is little understanding of the practical effects of such genetic structure on demography reconstructions and selection scans when focusing on recent population history. Here we tested the impact of population structure on such inferences using high-coverage (~30×) genome sequences of 2305 Estonians. We show that different regions of Estonia differ in both effective population size dynamics and signatures of natural selection. By analyzing identity-by-descent segments we also reveal that some Estonian regions exhibit evidence of a bottleneck 10-15 generations ago reflecting sequential episodes of wars, plague and famine, although this signal is virtually undetected when treating Estonia as a single population. Besides that, we provide a framework for relating effective population size estimated from genetic data to actual census size and validate it on the Estonian population. This approach may be widely used both to cross-check estimates based on historical sources as well as to get insight into times and/or regions with no other information available. Our results suggest that the history of human populations within the last few millennia can be highly region specific and cannot be properly studied without taking local genetic structure into account.

Translating genotype data of 44,000 biobank participants into clinical pharmacogenetic recommendations: challenges and solutions.

PURPOSE: Biomedical databases combining electronic medical records and phenotypic and genomic data constitute a powerful resource for the personalization of treatment. To leverage the wealth of information provided, algorithms are required that systematically translate the contained information into treatment recommendations based on existing genotype-phenotype associations. METHODS: We developed and tested algorithms for translation of preexisting genotype data of over 44,000 participants of the Estonian biobank into pharmacogenetic recommendations. We compared the results obtained by genome sequencing, exome sequencing, and genotyping using microarrays, and evaluated the impact of pharmacogenetic reporting based on drug prescription statistics in the Nordic countries and Estonia. RESULTS: Our most striking result was that the performance of genotyping arrays is similar to that of genome sequencing, whereas exome sequencing is not suitable for pharmacogenetic predictions. Interestingly, 99.8% of all assessed individuals had a genotype associated with increased risks to at least one medication, and thereby the implementation of pharmacogenetic recommendations based on genotyping affects at least 50 daily drug doses per 1000 inhabitants. CONCLUSION: We find that microarrays are a cost-effective solution for creating preemptive pharmacogenetic reports, and with slight modifications, existing databases can be applied for automated pharmacogenetic decision support for clinicians.