Connecting cohorts of Finnish biobanks creates a research resource for the study of healthy ageing.

AIMS: Connecting cohorts with biobanks is a Finnish biobank collaboration, creating an infrastructure for the study of healthy ageing. We aimed to develop a model for data integration and harmonisation between different biobanks with procedures for joint access. METHODS: The heart of the collaboration is the integrated datasets formed by using data from three biobanks: (a) Arctic Biobank, hosting regional birth cohorts and cohorts of elderly; (b) hospital-affiliated Borealis Biobank of Northern Finland; and (c) THL Biobank, hosting population-based cohorts. The datasets were created by developing a data dictionary, harmonising cohort data and with a joint pseudonymisation process. RESULTS: The connecting cohorts with biobanks resource at its widest consists altogether of almost 1.4 million individuals from collaborating biobanks. Utilising data from 107,000 cohort participants, we created harmonised datasets that contain attributes describing metabolic risk and frailty for studies of healthy ageing. These data can be complemented with medical data available from Biobank Borealis and with samples taken at hospital settings for approximately 38,000 cohort participants. In addition, the harmonised connecting cohorts with biobanks datasets can be expanded with supplementary data and samples from the collaborating biobanks. CONCLUSIONS: The connecting cohorts with biobanks datasets provide a unique resource for research on ageing-related personalised healthcare and for real-world evidence studies. Following the FAIR principles on findability, accessibility, interoperability, and reusability, the reused and harmonised datasets are findable and made accessible for researchers. The same approach can be further utilised to develop additional datasets for other research topics.

Update of the Minimum Information About BIobank Data Sharing (MIABIS) Core Terminology to the 3rd Version.

Introduction: The Minimum Information About BIobank Data Sharing (MIABIS) is a biobank-specific terminology enabling the sharing of biobank-related data for different purposes across a wide range of database implementations. After 4 years in use and with the first version of the individual-level MIABIS component Sample, Sample donor, and Event, it was necessary to revise the terminology, especially to include biobanks that work more in the data domain than with samples. Materials & Methods: Nine use-cases representing different types of biobanks, studies, and networks participated in the development work. They represent types of data, specific sample types, or levels of organization that were not included earlier in MIABIS. To support our revision of the Biobank entity, we conducted a survey of European biobanks to chart the services they provide. An important stakeholder group for biobanks include researchers as the main users of biobanks. To be able to render MIABIS more researcher-friendly, we collected different sample/data requests to analyze the terminology adjustment needs in detail. During the update process, the Core terminology was iteratively reviewed by a large group of experts until a consensus was reached. Results: With this update, MIABIS was adjusted to encompass data-driven biobanks and to include data collections, while also describing the services and capabilities biobanks offer to their users, besides the retrospective samples. The terminology was also extended to accommodate sample and data collections of nonhuman origin. Additionally, a set of organizational attributes was compiled to describe networks. Discussion: The usability of MIABIS Core v3 was increased by extending it to cover more topics of the biobanking domain. Additionally, the focus was on a more general terminology and harmonization of attributes with the individual-level entities Sample, Sample donor, and Event to keep the overall terminology minimal. With this work, the internal semantics of the MIABIS terminology was improved.

Overlap of Genetic Loci for Central Serous Chorioretinopathy With Age-Related Macular Degeneration.

Importance: Central serous chorioretinopathy (CSC) is a serous maculopathy of unknown etiology. Two of 3 previously reported CSC genetic risk loci are also associated with AMD. Improved understanding of CSC genetics may broaden our understanding of this genetic overlap and unveil mechanisms in both diseases. Objective: To identify novel genetic risk factors for CSC and compare genetic risk factors for CSC and AMD. Design, Setting, and Participants: Using International Classification of Diseases, Ninth (ICD-9) and Tenth (ICD-10) Revision code-based inclusion and exclusion criteria, patients with CSC and controls were identified in both the FinnGen study and the Estonian Biobank (EstBB). Also included in a meta-analysis were previously reported patients with chronic CSC and controls. Data were analyzed from March 1 to September 31, 2022. Main Outcomes and Measures: Genome-wide association studies (GWASs) were performed in the biobank-based cohorts followed by a meta-analysis of all cohorts. The expression of genes prioritized by the polygenic priority score and nearest-gene methods were assessed in cultured choroidal endothelial cells and public ocular single-cell RNA sequencing data sets. The predictive utility of polygenic scores (PGSs) for CSC and AMD were evaluated in the FinnGen study. Results: A total of 1176 patients with CSC and 526 787 controls (312 162 female [59.3%]) were included in this analysis: 552 patients with CSC and 343 461 controls were identified in the FinnGen study, 103 patients with CSC and 178 573 controls were identified in the EstBB, and 521 patients with chronic CSC and 3577 controls were included in a meta-analysis. Two previously reported CSC risk loci were replicated (near CFH and GATA5) and 3 novel loci were identified (near CD34/46, NOTCH4, and PREX1). The CFH and NOTCH4 loci were associated with AMD but in the opposite direction. Prioritized genes showed increased expression in cultured choroidal endothelial cells compared with other genes in the loci (median [IQR] of log 2 [counts per million], 7.3 [0.6] vs 4.7 [3.7]; P = .004) and were differentially expressed in choroidal vascular endothelial cells in single-cell RNA sequencing data (mean [SD] fold change, 2.05 [0.38] compared with other cell types; P < 7.1 × 10-20). A PGS for AMD was predictive of reduced CSC risk (odds ratio, 0.76; 95% CI, 0.70-0.83 per +1 SD in AMD-PGS; P = 7.4 × 10-10). This association may have been mediated by loci containing complement genes. Conclusions and Relevance: In this 3-cohort genetic association study, 5 genetic risk loci for CSC were identified, highlighting a likely role for genes involved in choroidal vascular function and complement regulation. Results suggest that polygenic AMD risk was associated with reduced risk of CSC and that this genetic overlap was largely due to loci containing complement genes.

Shared environment and colorectal cancer: A Nordic pedigree registry-based cohort study.

Risk of colorectal cancer (CRC) increases in relatives of patients with CRC. The extent to which this is attributable to genetic predisposition or shared environment is unclear. We explored this question using nationwide cohorts from Denmark, Finland and Sweden. From 1977 to 2013, we identified 359 879 individuals with a CRC diagnosis and 2 258 870 of their relatives who we followed for CRC incidence. We calculated standardized incidence ratios (SIR) and 95% confidence intervals (CI) for CRC in individuals with an affected relative. We used nationwide household and pedigree data along with national SIR estimates to calculate risk ratios (RR) for the contribution of shared household environment, childhood environment and genetic relationship to CRC risk in those with an affected relative. SIR of CRC was increased for individuals with an affected relative, across all countries and ages. For those with an affected parent, the SIR was 1.65 (95% CI: 1.61-1.69), 1.98 (95% CI: 1.87-2.09), for those with an affected sibling and 2.14 (95% CI: 1.84-2.49) for those with an affected halfsibling. In those <65 years old, shared childhood (RR: 1.41, 95% CI: 1.26-1.57) and household (RR: 2.08, 95% CI: 1.25-3.46) environments were significantly greater contributors to familial risk of CRC than genetics (RR: 0.88, 95% CI: 0.53-1.46). This large-scale Nordic population-based study of excess risk of CRC among relatives of those with CRC addresses the difficult disentangling of shared environment from genetic predisposition in the heritability of CRC. We found shared environment to be the most important contributor to CRC risk.

Extending the Minimum Information About BIobank Data Sharing Terminology to Describe Samples, Sample Donors, and Events.

Introduction: The Minimum Information About BIobank data Sharing (MIABIS) was initiated in 2012. MIABIS aims to create a common biobank terminology to facilitate data sharing in biobanks and sample collections. The MIABIS Core terminology consists of three components describing biobanks, sample collections, and studies, in which information on samples and sample donors is provided at aggregated form. However, there is also a need to describe samples and sample donors at an individual level to allow more elaborate queries on available biobank samples and data. Therefore the MIABIS terminology has now been extended with components describing samples and sample donors at an individual level. Materials and Methods: The components were defined according to specific scope and use cases by a large group of experts, and through several cycles of reviews, according to the new MIABIS governance model of BBMRI-ERIC (Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium). The guiding principles applied in developing these components included the following terms: model should consider only samples of human origin, model should be applicable to all types of samples and all sample donors, and model should describe the current status of samples stored in a given biobank. Results: A minimal set of standard attributes for defining samples and sample donors is presented here. We added an "event" component to describe attributes that are not directly describing samples or sample donors but are tightly related to them. To better utilize the generic data model, we suggest a procedure by which interoperability can be promoted, using specific MIABIS profiles. Discussion: The MIABIS sample and donor component extensions and the new generic data model complement the existing MIABIS Core 2.0 components, and substantially increase the potential usability of this terminology for better describing biobank samples and sample donors. They also support the use of individual level data about samples and sample donors to obtain accurate and detailed biobank availability queries.

Pan-European Data Harmonization for Biobanks in ADOPT BBMRI-ERIC.

BACKGROUND: High-quality clinical data and biological specimens are key for medical research and personalized medicine. The Biobanking and Biomolecular Resources Research Infrastructure-European Research Infrastructure Consortium (BBMRI-ERIC) aims to facilitate access to such biological resources. The accompanying ADOPT BBMRI-ERIC project kick-started BBMRI-ERIC by collecting colorectal cancer data from European biobanks. OBJECTIVES: To transform these data into a common representation, a uniform approach for data integration and harmonization had to be developed. This article describes the design and the implementation of a toolset for this task. METHODS: Based on the semantics of a metadata repository, we developed a lexical bag-of-words matcher, capable of semiautomatically mapping local biobank terms to the central ADOPT BBMRI-ERIC terminology. Its algorithm supports fuzzy matching, utilization of synonyms, and sentiment tagging. To process the anonymized instance data based on these mappings, we also developed a data transformation application. RESULTS: The implementation was used to process the data from 10 European biobanks. The lexical matcher automatically and correctly mapped 78.48% of the 1,492 local biobank terms, and human experts were able to complete the remaining mappings. We used the expert-curated mappings to successfully process 147,608 data records from 3,415 patients. CONCLUSION: A generic harmonization approach was created and successfully used for cross-institutional data harmonization across 10 European biobanks. The software tools were made available as open source.

Genome-wide association study and meta-analysis in Northern European populations replicate multiple colorectal cancer risk loci.

Genome-wide association studies have been successful in elucidating the genetic basis of colorectal cancer (CRC), but there remains unexplained variability in genetic risk. To identify new risk variants and to confirm reported associations, we conducted a genome-wide association study in 1,701 CRC cases and 14,082 cancer-free controls from the Finnish population. A total of 9,068,015 genetic variants were imputed and tested, and 30 promising variants were studied in additional 11,647 cases and 12,356 controls of European ancestry. The previously reported association between the single-nucleotide polymorphism (SNP) rs992157 (2q35) and CRC was independently replicated (p = 2.08 × 10-4 ; OR, 1.14; 95% CI, 1.06-1.23), and it was genome-wide significant in combined analysis (p = 1.50 × 10-9 ; OR, 1.12; 95% CI, 1.08-1.16). Variants at 2q35, 6p21.2, 8q23.3, 8q24.21, 10q22.3, 10q24.2, 11q13.4, 11q23.1, 14q22.2, 15q13.3, 18q21.1, 20p12.3 and 20q13.33 were associated with CRC in the Finnish population (false discovery rate < 0.1), but new risk loci were not found. These results replicate the effects of multiple loci on the risk of CRC and identify shared risk alleles between the Finnish population isolate and outbred populations.

BiobankUniverse: automatic matchmaking between datasets for biobank data discovery and integration.

MOTIVATION: Biobanks are indispensable for large-scale genetic/epidemiological studies, yet it remains difficult for researchers to determine which biobanks contain data matching their research questions. RESULTS: To overcome this, we developed a new matching algorithm that identifies pairs of related data elements between biobanks and research variables with high precision and recall. It integrates lexical comparison, Unified Medical Language System ontology tagging and semantic query expansion. The result is BiobankUniverse, a fast matchmaking service for biobanks and researchers. Biobankers upload their data elements and researchers their desired study variables, BiobankUniverse automatically shortlists matching attributes between them. Users can quickly explore matching potential and search for biobanks/data elements matching their research. They can also curate matches and define personalized data-universes. AVAILABILITY AND IMPLEMENTATION: BiobankUniverse is available at http://biobankuniverse.com or can be downloaded as part of the open source MOLGENIS suite at http://github.com/molgenis/molgenis. CONTACT: m.a.swertz@rug.nl. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

A Decentralized IT Architecture for Locating and Negotiating Access to Biobank Samples.

There is a need among researchers for the easy discoverability of biobank samples. Currently, there is no uniform way for finding samples and negotiate access. Instead, researchers have to communicate with each biobank separately. We present the architecture for the BBMRI-CS IT platform, whose goal is to facilitate sample location and access. We chose a decentral approach, which allows for strong data protection and provides the high flexibility needed in the highly heterogeneous landscape of European biobanks. This is the first implementation of a decentral search in the biobank field. With the addition of a Negotiator component, it also allows for easy communication and a follow-through of the lengthy approval process for accessing samples.

Common Genetic Variation Near Melatonin Receptor 1A Gene Linked to Job-Related Exhaustion in Shift Workers.

Study Objectives: Tolerance to shift work varies; only some shift workers suffer from disturbed sleep, fatigue, and job-related exhaustion. Our aim was to explore molecular genetic risk factors for intolerance to shift work. Methods: We assessed intolerance to shift work with job-related exhaustion symptoms in shift workers using the emotional exhaustion subscale of the Maslach Burnout Inventory-General Survey, and carried out a genome-wide association study (GWAS) using Illumina's Human610-Quad BeadChip (n = 176). The most significant findings were further studied in three groups of Finnish shift workers (n = 577). We assessed methylation in blood cells with the Illumina HumanMethylation450K BeadChip, and examined gene expression levels in the publicly available eGWAS Mayo data. Results: The second strongest signal identified in the GWAS (p = 2.3 × 10E-6) was replicated in two of the replication studies with p < .05 (p = 2.0 × 10E-4 when combining the replication studies) and indicated an association of job-related exhaustion in shift workers with rs12506228, located downstream of the melatonin receptor 1A gene (MTNR1A). The risk allele was also associated with reduced in silico gene expression levels of MTNR1A in brain tissue and suggestively associated with changes in DNA methylation in the 5' regulatory region of MTNR1A. Conclusions: These findings suggest that a variant near MTNR1A may be associated with job-related exhaustion in shift workers. The risk variant may exert its effect via epigenetic mechanisms, potentially leading to reduced melatonin signaling in the brain. These results could indicate a link between melatonin signaling, a key circadian regulatory mechanism, and tolerance to shift work.

Toward Global Biobank Integration by Implementation of the Minimum Information About BIobank Data Sharing (MIABIS 2.0 Core).

Biobanks are the biological back end of data-driven medicine, but lack standards and generic solutions for interoperability and information harmonization. The move toward a global information infrastructure for biobanking demands semantic interoperability through harmonized services and common ontologies. To tackle this issue, the Minimum Information About BIobank data Sharing (MIABIS) was developed in 2012 by the Biobanking and BioMolecular Resources Research Infrastructure of Sweden (BBMRI.se). The wide acceptance of the first version of MIABIS encouraged evolving it to a more structured and descriptive standard. In 2013 a working group was formed under the largest infrastructure for health in Europe, Biobanking and BioMolecular Resources Research Infrastructure (BBMRI-ERIC), with the remit to continue the development of MIABIS (version 2.0) through a multicountry governance process. MIABIS 2.0 Core has been developed with 22 attributes describing Biobanks, Sample Collections, and Studies according to a modular structure that makes it easier to adhere to and to extend the standard. This integration standard will make a great contribution to the discovery and exploitation of biobank resources and lead to a wider and more efficient use of valuable bioresources, thereby speeding up the research on human diseases. Many within the European Union have accepted MIABIS 2.0 Core as the "de facto" biobank information standard.

Genome-Wide Association Study for Incident Myocardial Infarction and Coronary Heart Disease in Prospective Cohort Studies: The CHARGE Consortium.

BACKGROUND: Data are limited on genome-wide association studies (GWAS) for incident coronary heart disease (CHD). Moreover, it is not known whether genetic variants identified to date also associate with risk of CHD in a prospective setting. METHODS: We performed a two-stage GWAS analysis of incident myocardial infarction (MI) and CHD in a total of 64,297 individuals (including 3898 MI cases, 5465 CHD cases). SNPs that passed an arbitrary threshold of 5×10-6 in Stage I were taken to Stage II for further discovery. Furthermore, in an analysis of prognosis, we studied whether known SNPs from former GWAS were associated with total mortality in individuals who experienced MI during follow-up. RESULTS: In Stage I 15 loci passed the threshold of 5×10-6; 8 loci for MI and 8 loci for CHD, for which one locus overlapped and none were reported in previous GWAS meta-analyses. We took 60 SNPs representing these 15 loci to Stage II of discovery. Four SNPs near QKI showed nominally significant association with MI (p-value<8.8×10-3) and three exceeded the genome-wide significance threshold when Stage I and Stage II results were combined (top SNP rs6941513: p = 6.2×10-9). Despite excellent power, the 9p21 locus SNP (rs1333049) was only modestly associated with MI (HR = 1.09, p-value = 0.02) and marginally with CHD (HR = 1.06, p-value = 0.08). Among an inception cohort of those who experienced MI during follow-up, the risk allele of rs1333049 was associated with a decreased risk of subsequent mortality (HR = 0.90, p-value = 3.2×10-3). CONCLUSIONS: QKI represents a novel locus that may serve as a predictor of incident CHD in prospective studies. The association of the 9p21 locus both with increased risk of first myocardial infarction and longer survival after MI highlights the importance of study design in investigating genetic determinants of complex disorders.

Genome-wide association study of sleep duration in the Finnish population.

Sleep duration is genetically regulated, but the genetic variants are largely unknown. We aimed to identify such genes using a genome-wide association study (GWAS) combined with RNA expression at the population level, and with experimental verification. A GWAS was performed in a Finnish sample (n = 1941), and variants with suggestive association (P < 5 × 10(-5) ) were tested in a follow-up sample from the same population with sleep duration (n = 6834) and time in bed (n = 1720). Variants with pointwise association of P < 0.05 in the follow-up sample were analysed further. First, we correlated genotypes with transcript expression levels with sleep duration (n = 207). The expression levels of significant transcripts were further studied in experimental sleep restriction. Of the 31 variants with P < 5 × 10(-5) in the discovery sample, three variants showed nominal allelic association (P < 0.05) in the follow-up sample: rs10914351, near PTPRU (P = 0.049), rs1037079 in PCDH7-CENTD1 (P = 0.011) and rs2031573 near KLF6 (P = 0.044). The risk alleles for shorter sleep (rs2031573 and rs1037079) were also associated with higher KLF6 and PCDH7 expression levels (P < 0.05). Experimental sleep restriction increased the expression of KLF6 (P < 0.01). These data suggest that rs2031573 near KLF6 or related loci and rs1037079 between PCDH7-CENTD1 or related loci may contribute to the regulation of sleep duration via gene expression. These results illustrate the utility of combining different analytical approaches to identify genetic determinants for traits related to sleep physiology. However, additional studies are needed in order to understand the roles of KLF6 and PCDH7 in sleep regulation.

µ-Opioid receptor gene (OPRM1) polymorphism A118G: lack of association in Finnish populations with alcohol dependence or alcohol consumption.

AIMS: The molecular epidemiological studies on the association of the opioid receptor µ-1 (OPRM1) polymorphism A118G (Asn40Asp, rs1799971) and alcohol use disorders have given conflicting results. The aim of this study was to test the possible association of A118G polymorphism and alcohol use disorders and alcohol consumption in three large cohort-based study samples. METHODS: The association between the OPRM1 A118G (Asn40Asp, rs1799971) polymorphism and alcohol use disorders and alcohol consumption was analyzed using three different population-based samples: (a) a Finnish cohort study, Health 2000, with 503 participants having a DSM-IV diagnosis for alcohol dependence and/or alcohol abuse and 506 age- and sex-matched controls; (b) a Finnish cohort study, FINRISK (n = 2360) and (c) the Helsinki Birth Cohort Study (n = 1384). The latter two populations lacked diagnosis-based phenotypes, but included detailed information on alcohol consumption. RESULTS: We found no statistically significant differences in genotypic or allelic distribution between controls and subjects with alcohol dependence or abuse diagnoses. Likewise no significant effects were observed between the A118G genotype and alcohol consumption. CONCLUSION: These results suggest that A118G (Asn40Asp) polymorphism may not have a major effect on the development of alcohol use disorders at least in the Finnish population.

Ischemic stroke is associated with the ABO locus: the EuroCLOT study.

OBJECTIVE: End-stage coagulation and the structure/function of fibrin are implicated in the pathogenesis of ischemic stroke. We explored whether genetic variants associated with end-stage coagulation in healthy volunteers account for the genetic predisposition to ischemic stroke and examined their influence on stroke subtype. METHODS: Common genetic variants identified through genome-wide association studies of coagulation factors and fibrin structure/function in healthy twins (n = 2,100, Stage 1) were examined in ischemic stroke (n = 4,200 cases) using 2 independent samples of European ancestry (Stage 2). A third clinical collection having stroke subtyping (total 8,900 cases, 55,000 controls) was used for replication (Stage 3). RESULTS: Stage 1 identified 524 single nucleotide polymorphisms (SNPs) from 23 linkage disequilibrium blocks having significant association (p < 5 × 10(-8)) with 1 or more coagulation/fibrin phenotypes. The most striking associations included SNP rs5985 with factor XIII activity (p = 2.6 × 10(-186)), rs10665 with FVII (p = 2.4 × 10(-47)), and rs505922 in the ABO gene with both von Willebrand factor (p = 4.7 × 10(-57)) and factor VIII (p = 1.2 × 10(-36)). In Stage 2, the 23 independent SNPs were examined in stroke cases/noncases using MOnica Risk, Genetics, Archiving and Monograph (MORGAM) and Wellcome Trust Case Control Consortium 2 collections. SNP rs505922 was nominally associated with ischemic stroke (odds ratio = 0.94, 95% confidence interval = 0.88-0.99, p = 0.023). Independent replication in Meta-Stroke confirmed the rs505922 association with stroke, beta (standard error, SE) = 0.066 (0.02), p = 0.001, a finding specific to large-vessel and cardioembolic stroke (p = 0.001 and p = < 0.001, respectively) but not seen with small-vessel stroke (p = 0.811). INTERPRETATION: ABO gene variants are associated with large-vessel and cardioembolic stroke but not small-vessel disease. This work sheds light on the different pathogenic mechanisms underpinning stroke subtype.

A genome-wide association study of monozygotic twin-pairs suggests a locus related to variability of serum high-density lipoprotein cholesterol.

Genome-wide association analysis on monozygotic twin-pairs offers a route to discovery of gene environment interactions through testing for variability loci associated with sensitivity to individual environment/lifestyle. We present a genome-wide scan of loci associated with intra-pair differences in serum lipid and apolipoprotein levels. We report data for 1,720 monozygotic female twin-pairs from GenomEUtwin project with 2.5 million SNPs, imputed or genotyped, and measured serum lipid fractions for both twins. We found one locus associated with intra-pair differences in high-density lipoprotein cholesterol, rs2483058 in an intron of SRGAP2, where twins carrying the C allele are more sensitive to environmental factors(P=3.98 x 10-8). We followed up the association in further genotyped monozygotic twins (N= 1,261),which showed a moderate association for the variant (P= 0.200, same direction of an effect). In addition,we report a new association on the level of apolipoprotein A-ll (P= 4.03 x 1 o-8).

Effect of short-term carbohydrate overfeeding and long-term weight loss on liver fat in overweight humans.

BACKGROUND: Cross-sectional studies have identified a high intake of simple sugars as an important dietary factor predicting nonalcoholic fatty liver disease (NAFLD). OBJECTIVE: We examined whether overfeeding overweight subjects with simple sugars increases liver fat and de novo lipogenesis (DNL) and whether this is reversible by weight loss. DESIGN: Sixteen subjects [BMI (kg/m²): 30.6 ± 1.2] were placed on a hypercaloric diet (>1000 kcal simple carbohydrates/d) for 3 wk and, thereafter, on a hypocaloric diet for 6 mo. The subjects were genotyped for rs739409 in the PNPLA3 gene. Before and after overfeeding and after hypocaloric diet, metabolic variables and liver fat (measured by proton magnetic resonance spectroscopy) were measured. The ratio of palmitate (16:0) to linoleate (18:2n-6) in serum and VLDL triglycerides was used as an index of DNL. RESULTS: Carbohydrate overfeeding increased weight (±SEM) by 2% (1.8 ± 0.3 kg; P < 0.0001) and liver fat by 27% from 9.2 ± 1.9% to 11.7 ± 1.9% (P = 0.005). DNL increased in proportion to the increase in liver fat and serum triglycerides in subjects with PNPLA3-148IIbut not PNPLA3-148MM. During the hypocaloric diet, the subjects lost 4% of their weight (3.2 ± 0.6 kg; P < 0.0001) and 25% of their liver fat content (from 11.7 ± 1.9% to 8.8 ± 1.8%; P < 0.05). CONCLUSIONS: Carbohydrate overfeeding for 3 wk induced a >10-fold greater relative change in liver fat (27%) than in body weight (2%). The increase in liver fat was proportional to that in DNL. Weight loss restores liver fat to normal. These data indicate that the human fatty liver avidly accumulates fat during carbohydrate overfeeding and support a role for DNL in the pathogenesis of NAFLD. This trial was registered at www.hus.fi as 235780.

Genetic markers enhance coronary risk prediction in men: the MORGAM prospective cohorts.

BACKGROUND: More accurate coronary heart disease (CHD) prediction, specifically in middle-aged men, is needed to reduce the burden of disease more effectively. We hypothesised that a multilocus genetic risk score could refine CHD prediction beyond classic risk scores and obtain more precise risk estimates using a prospective cohort design. METHODS: Using data from nine prospective European cohorts, including 26,221 men, we selected in a case-cohort setting 4,818 healthy men at baseline, and used Cox proportional hazards models to examine associations between CHD and risk scores based on genetic variants representing 13 genomic regions. Over follow-up (range: 5-18 years), 1,736 incident CHD events occurred. Genetic risk scores were validated in men with at least 10 years of follow-up (632 cases, 1361 non-cases). Genetic risk score 1 (GRS1) combined 11 SNPs and two haplotypes, with effect estimates from previous genome-wide association studies. GRS2 combined 11 SNPs plus 4 SNPs from the haplotypes with coefficients estimated from these prospective cohorts using 10-fold cross-validation. Scores were added to a model adjusted for classic risk factors comprising the Framingham risk score and 10-year risks were derived. RESULTS: Both scores improved net reclassification (NRI) over the Framingham score (7.5%, p = 0.017 for GRS1, 6.5%, p = 0.044 for GRS2) but GRS2 also improved discrimination (c-index improvement 1.11%, p = 0.048). Subgroup analysis on men aged 50-59 (436 cases, 603 non-cases) improved net reclassification for GRS1 (13.8%) and GRS2 (12.5%). Net reclassification improvement remained significant for both scores when family history of CHD was added to the baseline model for this male subgroup improving prediction of early onset CHD events. CONCLUSIONS: Genetic risk scores add precision to risk estimates for CHD and improve prediction beyond classic risk factors, particularly for middle aged men.

A meta-analysis of genome-wide association studies of the electrocardiographic early repolarization pattern.

BACKGROUND: The early repolarization pattern (ERP) is common and associated with risk of sudden cardiac death. ERP is heritable, and mutations have been described in syndromatic cases. OBJECTIVE: To conduct a meta-analysis of genome-wide association studies to identify common genetic variants influencing ERP. METHODS: We ascertained ERP on the basis of electrocardiograms in 3 large community-based cohorts from Europe and the United States: the Framingham Heart Study, the Health 2000 Study, and the KORA F4 Study. We analyzed genome-wide association studies in participants with and without ERP by logistic regression assuming an additive genetic model and meta-analyzed individual cohort results. We then sought to strengthen support for findings that reached P ≤ 1 × 10(-5) in independent individuals by direct genotyping or in-silico analysis of genome-wide data. We meta-analyzed the results from both stages. RESULTS: Of 7482 individuals in the discovery stage, 452 showed ERP (ERP positive: mean age 46.9 ± 8.9 years, 30.3% women; ERP negative: 47.5 ± 9.4 years, 54.2% women). After meta-analysis, 8 single nucleotide polymorphisms reached P ≤ 1 × 10(-5): The most significant finding was intergenic rs11653989 (odds ratio 0.47; 95% confidence interval 0.36-0.61; P = 6.9 × 10(-9)). The most biologically relevant finding was intronic to KCND3: rs17029069 (odds ratio 1.46; 95% confidence interval 1.25-1.69; P = 8.5 × 10(-7)). In the replication step (7151 individuals), none of the 8 variants replicated, and combined meta-analysis results failed to reach genome-wide significance. CONCLUSIONS: In a genome-wide association study, we were not able to reliably identify genetic variants predisposing to ERP, presumably due to insufficient statistical power and phenotype heterogeneity. The reported heritability of ERP warrants continued investigation in larger well-phenotyped populations.