Publications by authors named "Nina Mars"

Understanding perturbations in circulating lipid levels that often occur years or decades before clinical symptoms may enhance our understanding of disease mechanisms and provide novel intervention opportunities. Here, we assessed if polygenic scores (PGSs) for complex traits could detect lipid dysfunctions related to the traits and provide new biological insights. We constructed genome-wide PGSs (approximately 1 million genetic variants) for 50 complex traits in 7,169 Finnish individuals with routine clinical lipid profiles and lipidomics measurements (179 lipid species).

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Methods of estimating polygenic scores (PGSs) from genome-wide association studies are increasingly utilized. However, independent method evaluation is lacking, and method comparisons are often limited. Here, we evaluate polygenic scores derived via seven methods in five biobank studies (totaling about 1.

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Polygenic scores (PGSs) offer the ability to predict genetic risk for complex diseases across the life course; a key benefit over short-term prediction models. To produce risk estimates relevant to clinical and public health decision-making, it is important to account for varying effects due to age and sex. Here, we develop a novel framework to estimate country-, age-, and sex-specific estimates of cumulative incidence stratified by PGS for 18 high-burden diseases.

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Article Synopsis
  • Rheumatic diseases significantly affect reproductive health, leading to increased rates of childlessness and fewer children, particularly observed in conditions like systemic lupus erythematosus (SLE) and juvenile idiopathic arthritis (JIA).
  • A nationwide study evaluated over 5 million Finnish citizens, comparing individuals with 19 immune-mediated diseases (IMDs) against matched controls on reproductive health metrics, including adverse maternal and perinatal outcomes.
  • The findings highlighted that patients with rheumatic diseases face higher risks for complications such as pre-eclampsia and preterm delivery, with SLE and Sjögren's syndrome showing the largest increases in adverse pregnancy outcomes.
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Purpose: Family history (FH) and pathogenic variants (PVs) are used for guiding risk surveillance in selected high-risk women but little is known about their impact for breast cancer screening on population level. In addition, polygenic risk scores (PRSs) have been shown to efficiently stratify breast cancer risk through combining information about common genetic factors into one measure.

Methods: In longitudinal real-life data, we evaluate PRS, FH, and PVs for stratified screening.

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Cancer risk is influenced by inherited mutations, DNA replication errors, and environmental factors. However, the influence of genetic variation in immunosurveillance on cancer risk is not well understood. Leveraging population-level data from the UK Biobank and FinnGen, we show that heterozygosity at the -II loci is associated with reduced lung cancer risk in smokers.

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Objectives: To elucidate the risk and temporal relationship of cardiovascular (CV) comorbidities in rheumatic diseases.

Methods: Patients in the FinnGen study diagnosed between 2000 and 2014 with seropositive (n = 2368) or seronegative (n = 916) rheumatoid arthritis (RA), ankylosing spondylitis (AS, n = 715), psoriatic arthritis (PsA, n = 923), systemic lupus erythematosus (SLE, n = 190), primary Sjogren's syndrome (pSS, n = 412) or gout (n = 2034) were identified from healthcare registries. Each patient was matched based on age, sex, and birth region with twenty controls without any rheumatic conditions.

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Formalin-fixed paraffin-embedded (FFPE) tissues stored in biobanks and pathology archives are a vast but underutilized source for molecular studies on different diseases. Beyond being the "gold standard" for preservation of diagnostic human tissues, FFPE samples retain similar genetic information as matching blood samples, which could make FFPE samples an ideal resource for genomic analysis. However, research on this resource has been hindered by the perception that DNA extracted from FFPE samples is of poor quality.

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There are several established biomarkers for coronary heart disease (CHD), including blood pressure, cholesterol, and lipoproteins. It is of high interest to determine how a combined polygenic risk score (PRS) of CHD-associated biomarkers (BioPRS) can further improve genetic prediction of CHD. We developed CHDBioPRS, combining BioPRS with PRS of CHD in the UK Biobank and tested it on FinnGen.

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Background: Hereditary factors, including single genetic variants and family history, can be used for targeting colorectal cancer (CRC) screening, but limited data exist on the impact of polygenic risk scores (PRS) on risk-based CRC screening.

Methods: Using longitudinal health and genomics data on 453,733 Finnish individuals including 8801 CRC cases, we estimated the impact of a genome-wide CRC PRS on CRC screening initiation age through population-calibrated incidence estimation over the life course in men and women.

Results: Compared to the cumulative incidence of CRC at age 60 in Finland (the current age for starting screening in Finland), a comparable cumulative incidence was reached 5 and 11 years earlier in persons with high PRS (80-99% and >99%, respectively), while those with a low PRS (< 20%) reached comparable incidence 7 years later.

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Study Objectives: Over 10% of the population in Europe and in the United States use sleep medication to manage sleep problems. Our objective was to elucidate genetic risk factors and clinical correlates that contribute to sleep medication purchase and estimate the comorbid impact of sleep problems.

Methods: We performed epidemiological analysis for psychiatric diagnoses, and genetic association studies of sleep medication purchase in 797 714 individuals from FinnGen Release 7 (N = 311 892) and from the UK Biobank (N = 485 822).

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Importance: The clinical value of current multifactorial algorithms for individualized assessment of dementia risk remains unclear.

Objective: To evaluate the clinical value associated with 4 widely used dementia risk scores in estimating 10-year dementia risk.

Design, Setting, And Participants: This prospective population-based UK Biobank cohort study assessed 4 dementia risk scores at baseline (2006-2010) and ascertained incident dementia during the following 10 years.

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Background: Contrary to the presumption that type 1 diabetes leads to an absolute insulin deficiency, many individuals with type 1 diabetes have circulating C-peptide years after the diagnosis. We studied factors affecting random serum C-peptide concentration in individuals with type 1 diabetes and the association with diabetic complications.

Methods: Our longitudinal analysis included individuals newly diagnosed with type 1 diabetes from Helsinki University Hospital (Helsinki, Finland) with repeated random serum C-peptide and concomitant glucose measurements from within 3 months of diagnosis and at least once later.

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Article Synopsis
  • Immune system and blood-brain barrier dysfunction may play a role in developing Alzheimer's and other dementias, but the specific causal mechanisms are still unclear.
  • Researchers conducted a Mendelian randomization study involving 1,827 related biomarkers, identifying 127 potential causal risk factors linked to amyloid-β, tau, and autoimmunity.
  • Results from analyses suggest that treatment with anti-inflammatory methotrexate could reduce the risk of Alzheimer's in high-risk individuals, indicating that autoimmunity could be a modifiable factor in dementia-related diseases.
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  • Population isolates like Finland provide a unique advantage for genetic research by having concentrated deleterious alleles in low-frequency variants due to historical bottlenecks.
  • The FinnGen study aims to analyze data from 500,000 Finnish individuals, focusing on their genomes and health records, particularly as many participants are older and have disease-related data.
  • From the analysis of 224,737 participants and additional biobank data, researchers discovered 30 new associations and a total of 2,733 significant genetic links across various diseases, highlighting the importance of low-frequency variants in understanding common diseases.
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Background: Testosterone levels are linked with diverse characteristics of human health, yet, whether these associations reflect correlation or causation remains debated. Here, we provide a broad perspective on the role of genetically determined testosterone on complex diseases in both sexes.

Methods: Leveraging genetic and health registry data from the UK Biobank and FinnGen (total N = 625,650), we constructed polygenic scores (PGS) for total testosterone, sex-hormone binding globulin (SHBG) and free testosterone, associating these with 36 endpoints across different disease categories in the FinnGen.

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Little is known about the genetic determinants of medication use in preventing cardiometabolic diseases. Using the Finnish nationwide drug purchase registry with follow-up since 1995, we performed genome-wide association analyses of longitudinal patterns of medication use in hyperlipidemia, hypertension and type 2 diabetes in up to 193,933 individuals (55% women) in the FinnGen study. In meta-analyses of up to 567,671 individuals combining FinnGen with the Estonian Biobank and the UK Biobank, we discovered 333 independent loci (P < 5 × 10) associated with medication use.

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Inflammatory and infectious upper respiratory diseases (ICD-10: J30-J39), such as diseases of the sinonasal tract, pharynx and larynx, are growing health problems yet their genomic similarity is not known. We analyze genome-wide association to eight upper respiratory diseases (61,195 cases) among 260,405 FinnGen participants, meta-analyzing diseases in four groups based on an underlying genetic correlation structure. Aiming to understand which genetic loci contribute to susceptibility to upper respiratory diseases in general and its subtypes, we detect 41 independent genome-wide significant loci, distinguishing impact on sinonasal or pharyngeal diseases, or both.

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Aims: The aim of this study was to evaluate the effect of the intervention by proactively sharing a patient's high polygenic risk score (PRS) for coronary artery disease (CAD). Outcomes included: (i) reduction in cardiovascular disease (CVD) risk factors over 12 months; (ii) difference in purchased prescriptions of lipid-lowering and anti-hypertensive drugs between intervention group and control group subjects; and (iii) opinion of the participating physicians and subjects on PRS usefulness.

Methods And Results: This randomized controlled trial was conducted among middle-aged subjects with a top 20% CAD PRS in a family medicine setting.

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Family history is the standard indirect measure of inherited susceptibility in clinical care, whereas polygenic risk scores (PRSs) have more recently demonstrated potential for more directly capturing genetic risk in many diseases. Few studies have systematically compared how these overlap and complement each other across common diseases. Within FinnGen (N = 306,418), we leverage family relationships, up to 50 years of nationwide registries, and genome-wide genotyping to examine the interplay of family history and genome-wide PRSs.

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The impact of genetic variation on overall disease burden has not been comprehensively evaluated. We introduce an approach to estimate the effect of genetic risk factors on disability-adjusted life years (DALYs; 'lost healthy life years'). We use genetic information from 735,748 individuals and consider 80 diseases.

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Cardiovascular diseases are the leading cause of premature death and disability worldwide, with both genetic and environmental determinants. While genome-wide association studies have identified multiple genetic loci associated with cardiovascular diseases, exact genes driving these associations remain mostly uncovered. Due to Finland's population history, many deleterious and high-impact variants are enriched in the Finnish population giving a possibility to find genetic associations for protein-truncating variants that likely tie the association to a gene and that would not be detected elsewhere.

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Polygenic risk scores (PRS) measure genetic disease susceptibility by combining risk effects across the genome. For coronary artery disease (CAD), type 2 diabetes (T2D), and breast and prostate cancer, we performed cross-ancestry evaluation of genome-wide PRSs in six biobanks in Europe, the United States, and Asia. We studied transferability of these highly polygenic, genome-wide PRSs across global ancestries, within European populations with different health-care systems, and local population substructures in a population isolate.

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