Cohort Profile: The National FINRISK Study

Comparison of various strategies to define the optimal target population for liver fibrosis screening: A population-based cohort study

BACKGROUND & AIMS

Liver fibrosis screening is recommended in high-risk populations, but the optimal definition of "high risk" remains to be established. We compared the performance of several risk-stratification strategies in a population-based setting.

METHODS

Data were obtained from the Finnish population-based health examination surveys Health 2000 and FINRISK 2002-2012. The Chronic Liver Disease Risk Score (CLivD) was compared to previously published risk-stratification strategies based on elevated liver enzymes, alcohol use, diabetes, fatty liver index, body mass index, and/or metabolic risk factors for their ability to detect either advanced liver fibrosis or incident severe liver events. Advanced fibrosis was defined as an Enhanced Liver Fibrosis (ELF^TM ) score >9.8 in the Health 2000 study (n = 6084), and incident liver events were ascertained from registry linkage in the combined FINRISK 2002-2012 and Health 2000 cohort (n = 26,957).

RESULTS

Depending on the cohort, 53%-60% of the population was considered at risk using the CLivD strategy (low-intermediate-high risk, excluding the minimal-risk category), compared to 30%-32% according to the other risk-stratification strategies. The CLivD captured 85%-91% of cases in the population with advanced liver fibrosis and 90% of incident severe liver events within 10 years from baseline. This compares to 33%-44% and 56%-67% captured by the other risk-stratification strategies, respectively. The 10-year cumulative incidence of liver events varied by risk-stratification strategy (1.0%-1.4%).

CONCLUSIONS

Compared to previously reported traditional risk factor-based strategies, use of the CLivD captured substantially more cases with advanced liver disease in the population and may be superior for targeting further fibrosis screening.

Alcohol Drinking Patterns and Laboratory Indices of Health: Does Type of Alcohol Preferred Make a Difference?

Although excessive alcohol consumption is a highly prevalent public health problem the data on the associations between alcohol consumption and health outcomes in individuals preferring different types of alcoholic beverages has remained unclear. We examined the relationships between the amounts and patterns of drinking with the data on laboratory indices of liver function, lipid status and inflammation in a national population-based health survey (FINRISK). Data on health status, alcohol drinking, types of alcoholic beverages preferred, body weight, smoking, coffee consumption and physical activity were recorded from 22,432 subjects (10,626 men, 11,806 women), age range 25-74 years. The participants were divided to subgroups based on the amounts of regular alcohol intake (abstainers, moderate and heavy drinkers), patterns of drinking (binge or regular) and the type of alcoholic beverage preferred (wine, beer, cider or long drink, hard liquor or mixed). Regular drinking was found to be more typical in wine drinkers whereas the subjects preferring beer or hard liquor were more often binge-type drinkers and cigarette smokers. Alcohol use in all forms was associated with increased frequencies of abnormalities in the markers of liver function, lipid status and inflammation even at rather low levels of consumption. The highest rates of abnormalities occurred, however, in the subgroups of binge-type drinkers preferring beer or hard liquor. These results demonstrate that adverse consequences of alcohol occur even at moderate average drinking levels especially in individuals who engage in binge drinking and in those preferring beer or hard liquor. Further emphasis should be placed on such patterns of drinking in policies aimed at preventing alcohol-induced adverse health outcomes.

Methylation status of VTRNA2-1/nc886 is stable across populations, monozygotic twin pairs and in majority of tissues

Aims & methods: The aim of this study was to characterize the methylation level of a polymorphically imprinted gene, VTRNA2-1/nc886, in human populations and somatic tissues.48 datasets, consisting of more than 30 tissues and >30,000 individuals, were used. Results: nc886 methylation status is associated with twin status and ethnic background, but the variation between populations is limited. Monozygotic twin pairs present concordant methylation, whereas ∼30% of dizygotic twin pairs present discordant methylation in the nc886 locus. The methylation levels of nc886 are uniform across somatic tissues, except in cerebellum and skeletal muscle. Conclusion: The nc886 imprint may be established in the oocyte, and, after implantation, the methylation status is stable, excluding a few specific tissues.

Recontacting biobank participants to collect lifestyle, behavioural and cognitive information via online questionnaires: lessons from a pilot study within FinnGen

OBJECTIVES

To recontact biobank participants and collect cognitive, behavioural and lifestyle information via a secure online platform.

DESIGN

Biobank-based recontacting pilot study.

SETTING

Three Finnish biobanks (Helsinki, Auria, Tampere) recruiting participants from February 2021 to July 2021.

PARTICIPANTS

All eligible invitees were enrolled in FinnGen by their biobanks (Helsinki, Auria, Tampere), had available genetic data and were >18 years old. Individuals with severe neuropsychiatric disease or cognitive or physical disabilities were excluded. Lastly, 5995 participants were selected based on their polygenic score for cognitive abilities and invited to the study. Among invitees, 1115 had successfully participated and completed the study questionnaire(s).

OUTCOME MEASURES

The primary outcome was the participation rate among study invitees. Secondary outcomes included questionnaire completion rate, quality of data collected and comparison of participation rate boosting strategies.

RESULTS

The overall participation rate was 18.6% among all invitees and 23.1% among individuals aged 18-69. A second reminder letter yielded an additional 9.7% participation rate in those who did not respond to the first invitation. Recontacting participants via an online healthcare portal yielded lower participation than recontacting via physical letter. The completion rate of the questionnaire and cognitive tests was high (92% and 85%, respectively), and measurements were overall reliable among participants. For example, the correlation (r) between self-reported body mass index and that collected by the biobanks was 0.92.

CONCLUSION

In summary, this pilot suggests that recontacting FinnGen participants with the goal to collect a wide range of cognitive, behavioural and lifestyle information without additional engagement results in a low participation rate, but with reliable data. We suggest that such information be collected at enrolment, if possible, rather than via post hoc recontacting.

Implementation of individualised polygenic risk score analysis: a test case of a family of four

Background

Polygenic risk scores (PRS) have been widely applied in research studies, showing how population groups can be stratified into risk categories for many common conditions. As healthcare systems consider applying PRS to keep their populations healthy, little work has been carried out demonstrating their implementation at an individual level.

Case presentation

We performed a systematic curation of PRS sources from established data repositories, selecting 15 phenotypes, comprising an excess of 37 million SNPs related to cancer, cardiovascular, metabolic and autoimmune diseases. We tested selected phenotypes using whole genome sequencing data for a family of four related individuals. Individual risk scores were given percentile values based upon reference distributions among 1000 Genomes Iberians, Europeans, or all samples. Over 96 billion allele effects were calculated in order to obtain the PRS for each of the individuals analysed here.

Conclusions

Our results highlight the need for further standardisation in the way PRS are developed and shared, the importance of individual risk assessment rather than the assumption of inherited averages, and the challenges currently posed when translating PRS into risk metrics.

Attribution of diabetes to the development of severe liver disease in the general population

BACKGROUND AND AIMS

Diabetes is associated with advanced liver disease and predicts mortality regardless of the primary aetiology of the liver disease. Even a family history of diabetes has been linked to advanced liver fibrosis in non-alcoholic fatty liver disease (NAFLD). However, the fraction of liver-related outcomes in the general population that are attributable to diabetes remains unclear.

METHODS

The population attributable fraction (PAF) of diabetes for liver disease as a time-dependent exposure was estimated in the Finnish FINRISK study (n = 28 787) and the British Whitehall II study (n = 7855). We also assessed the predictive ability of a family history of diabetes for liver-related outcomes. Incident diabetes data were from drug purchase/reimbursement and healthcare registries (FINRISK) or follow-up examinations (Whitehall II). Incident severe liver outcomes were identified through linkage with national healthcare registries.

RESULTS

Diabetes was associated with a two-fold risk of liver-related outcomes in both the FINRISK (HR, 1.92; p < .001) and Whitehall II (HR, 2.37; p < .001) cohorts, and this remained significant after adjusting for multiple confounders. PAF analyses demonstrated that diabetes explained 12-14% of the risk for severe liver-related outcomes after 10 and 20 years of follow-up. Also, maternal diabetes increased the risk of liver-related outcomes in the FINRISK (HR, 1.43; p = .044) and Whitehall II (HR, 2.04; p = .051) cohorts.

CONCLUSION

Approximately 12%-14% of severe liver-related outcomes are attributable to diabetes at the population level. The association between maternal diabetes and liver disease might suggest a mitochondrial genetic mechanism.

Association between arterial hypertension and liver outcomes using polygenic risk scores: a population-based study

Arterial hypertension (HTA) is associated with liver disease, but causality remains unclear. We investigated whether genetic predisposition to HTA is associated with liver disease in the population, and if antihypertensive medication modifies this association. Participants of the Finnish health-examination surveys, FINRISK 1992–2012 and Health 2000 (n = 33,770), were linked with national electronic healthcare registers for liver-related outcomes (K70-K77, C22.0) and with the drug reimbursement registry for new initiation of antihypertensive medication during follow-up. Genetic predisposition to HTA was defined by polygenic risk scores (PRSs). During a median 12.9-year follow-up (409,268.9 person-years), 441 liver-related outcomes occurred. In the fully-adjusted Cox-regression models, both measured systolic blood pressure and clinically defined HTA were associated with liver-related outcomes. PRSs for systolic and diastolic blood pressure were significantly associated with liver-related outcomes (HR/SD 1.19, 95% CI 1.01–1.24, and 1.12, 95% CI 1.01–1.25, respectively). In the highest quintile of the systolic blood pressure PRS, new initiation of antihypertensive medication was associated with reduced rates of liver-related outcomes (HR 0.55, 95% CI 0.31–0.97). HTA and a genetic predisposition for HTA are associated with liver-related outcomes in the population. New initiation of antihypertensive medication attenuates this association in persons with high genetic risk for HTA.

The impact of Mendelian sleep and circadian genetic variants in a population setting

Rare variants in ten genes have been reported to cause Mendelian sleep conditions characterised by extreme sleep duration or timing. These include familial natural short sleep (ADRB1, DEC2/BHLHE41, GRM1 and NPSR1), advanced sleep phase (PER2, PER3, CRY2, CSNK1D and TIMELESS) and delayed sleep phase (CRY1). The association of variants in these genes with extreme sleep conditions were usually based on clinically ascertained families, and their effects when identified in the population are unknown. We aimed to determine the effects of these variants on sleep traits in large population-based cohorts. We performed genetic association analysis of variants previously reported to be causal for Mendelian sleep and circadian conditions. Analyses were performed using 191,929 individuals with data on sleep and whole-exome or genome-sequence data from 4 population-based studies: UK Biobank, FINRISK, Health-2000-2001, and the Multi-Ethnic Study of Atherosclerosis (MESA). We identified sleep disorders from self-report, hospital and primary care data. We estimated sleep duration and timing measures from self-report and accelerometery data. We identified carriers for 10 out of 12 previously reported pathogenic variants for 8 of the 10 genes. They ranged in frequency from 1 individual with the variant in CSNK1D to 1,574 individuals with a reported variant in the PER3 gene in the UK Biobank. No carriers for variants reported in NPSR1 or PER2 were identified. We found no association between variants analyzed and extreme sleep or circadian phenotypes. Using sleep timing as a proxy measure for sleep phase, only PER3 and CRY1 variants demonstrated association with earlier and later sleep timing, respectively; however, the magnitude of effect was smaller than previously reported (sleep midpoint ~7 mins earlier and ~5 mins later, respectively). We also performed burden tests of protein truncating (PTVs) or rare missense variants for the 10 genes. Only PTVs in PER2 and PER3 were associated with a relevant trait (for example, 64 individuals with a PTV in PER2 had an odds ratio of 4.4 for being "definitely a morning person", P = 4x10-8; and had a 57-minute earlier midpoint sleep, P = 5x10-7). Our results indicate that previously reported variants for Mendelian sleep and circadian conditions are often not highly penetrant when ascertained incidentally from the general population.

Integrated analyses of growth differentiation factor-15 concentration and cardiometabolic diseases in humans

Growth differentiation factor-15 (GDF15) is a stress response cytokine that is elevated in several cardiometabolic diseases and has attracted interest as a potential therapeutic target. To further explore the association of GDF15 with human disease, we conducted a broad study into the phenotypic and genetic correlates of GDF15 concentration in up to 14,099 individuals. Assessment of 772 traits across 6610 participants in FINRISK identified associations of GDF15 concentration with a range of phenotypes including all-cause mortality, cardiometabolic disease, respiratory diseases and psychiatric disorders, as well as inflammatory markers. A meta-analysis of genome-wide association studies (GWAS) of GDF15 concentration across three different assay platforms (n=14,099) confirmed significant heterogeneity due to a common missense variant (rs1058587; p.H202D) in GDF15, potentially due to epitope-binding artefacts. After conditioning on rs1058587, statistical fine mapping identified four independent putative causal signals at the locus. Mendelian randomisation (MR) analysis found evidence of a causal relationship between GDF15 concentration and high-density lipoprotein (HDL) but not body mass index (BMI). Using reverse MR, we identified a potential causal association of BMI on GDF15 (IVW pFDR = 0.0040). Taken together, our data derived from human population cohorts do not support a role for moderately elevated GDF15 concentrations as a causal factor in human cardiometabolic disease but support its role as a biomarker of metabolic stress.

Multi-Trait Genetic Analysis Reveals Clinically Interpretable Hypertension Subtypes

Background:

Hypertension comprises a heterogeneous range of phenotypes. We asked whether underlying genetic structure could explain a part of this heterogeneity.

Methods:

Our study sample comprised N=198 148 FinnGen participants (56% women, mean age 58 years) and N=21 168 well-phenotyped FINRISK participants (53% women, mean age 50 years). First, we identified genetic hypertension components with an unsupervised Bayesian non-negative matrix factorization algorithm using public genome-wide association data for 144 genetic hypertension variants and 16 clinical traits. For these components, we computed their (1) cross-sectional associations with clinical traits in FINRISK using linear regression and (2) longitudinal associations with incident adverse outcomes in FinnGen using Cox regression.

Results:

We observed 4 genetic hypertension components corresponding to recognizable clinical phenotypes: obesity (high body mass index), dyslipidemia (low high-density lipoprotein cholesterol and high triglycerides), hypolipidemia (low low-density lipoprotein cholesterol and low total cholesterol), and short stature. In FINRISK, all hypertension components had robust associations with their respective clinical characteristics. In FinnGen, the Obesity component was associated with increased diabetes risk (hazard ratio per 1 SD increase 1.08 [Bonferroni corrected CI, 1.05–1.10]) and the Hypolipidemia component with increased autoimmune disease risk (hazard ratio per 1 SD increase 1.05 [Bonferroni corrected CI, 1.03–1.07]). In addition, all hypertension components were related to both hypertension and cardiovascular disease.

Conclusions:

Our unsupervised analysis demonstrates that the genetic basis of hypertension can be understood as a mixture of 4 broad, clinically interpretable components capturing disease heterogeneity. These components could be used to stratify individuals into specific genetic subtypes and, therefore, to benefit personalized health care and pharmaceutical research.

Development and validation of a model to predict incident chronic liver disease in the general population: The CLivD score

BACKGROUND & AIMS

Current screening strategies for chronic liver disease focus on detection of subclinical advanced liver fibrosis but cannot identify those at high future risk of severe liver disease. Our aim was to develop and validate a risk prediction model for incident chronic liver disease in the general population based on widely available factors.

METHODS

Multivariable Cox regression analyses were used to develop prediction models for liver-related outcomes with and without laboratory measures (Model_lab and Model_non-lab) in 25,760 individuals aged 40-70 years. Their data were sourced from the Finnish population-based health examination surveys FINRISK 1992-2012 and Health 2000 (derivation cohort). The models were externally validated in the Whitehall II (n = 5,058) and Copenhagen City Heart Study (CCHS) (n = 3,049) cohorts.

RESULTS

The absolute rate of incident liver outcomes per 100,000 person-years ranged from 53 to 144. The final prediction model included age, sex, alcohol use (drinks/week), waist-hip ratio, diabetes, and smoking, and Model_lab also included gamma-glutamyltransferase values. Internally validated Wolbers' C-statistics were 0.77 for Model_lab and 0.75 for Model_non-lab, while apparent 15-year AUCs were 0.84 (95% CI 0.75-0.93) and 0.82 (95% CI 0.74-0.91). The models identified a small proportion (<2%) of the population with >10% absolute 15-year risk for liver events. Of all liver events, only 10% occurred in participants in the lowest risk category. In the validation cohorts, 15-year AUCs were 0.78 (Model_lab) and 0.65 (Model_non-lab) in the CCHS cohort, and 0.78 (Model_non-lab) in the Whitehall II cohort.

CONCLUSIONS

Based on widely available risk factors, the Chronic Liver Disease (CLivD) score can be used to predict risk of future advanced liver disease in the general population.

LAY SUMMARY

Liver disease often progresses silently without symptoms and thus the diagnosis is often delayed until severe complications occur and prognosis becomes poor. In order to identify individuals in the general population who have a high risk of developing severe liver disease in the future, we developed and validated a Chronic Liver Disease (CLivD) risk prediction score, based on age, sex, alcohol use, waist-hip ratio, diabetes, and smoking, with or without measurement of the liver enzyme gamma-glutamyltransferase. The CLivD score can be used as part of health counseling, and for planning further liver investigations and follow-up.

Identification of healthspan-promoting genes in Caenorhabditis elegans based on a human GWAS study

To find drivers of healthy ageing, a genome-wide association study (GWAS) was performed in healthy and unhealthy older individuals. Healthy individuals were defined as free from cardiovascular disease, stroke, heart failure, major adverse cardiovascular event, diabetes, dementia, cancer, chronic obstructive pulmonary disease (COPD), asthma, rheumatism, Crohn’s disease, malabsorption or kidney disease. Six single nucleotide polymorphisms (SNPs) with unknown function associated with ten human genes were identified as candidate healthspan markers. Thirteen homologous or closely related genes were selected in the model organism C. elegans for evaluating healthspan after targeted RNAi-mediated knockdown using pathogen resistance, muscle integrity, chemotaxis index and the activity of known longevity and stress response pathways as healthspan reporters. In addition, lifespan was monitored in the RNAi-treated nematodes. RNAi knockdown of yap-1, wwp-1, paxt-1 and several acdh genes resulted in heterogeneous phenotypes regarding muscle integrity, pathogen resistance, chemotactic behaviour, and lifespan. Based on these observations, we hypothesize that their human homologues WWC2, CDKN2AIP and ACADS may play a role in health maintenance in the elderly.

Circulating Metabolic Biomarkers Are Consistently Associated With Type 2 Diabetes Risk in Asian and European Populations

CONTEXT

While Asians have a higher risk of type 2 diabetes (T2D) than Europeans for a given body mass index (BMI), it remains unclear whether the same markers of metabolic pathways are associated with diabetes.

OBJECTIVE

We evaluated associations between metabolic biomarkers and incidence of T2D in 3 major Asian ethnic groups (Chinese, Malay, and Indian) and a European population.

METHODS

We analyzed data from adult males and females of 2 cohorts from Singapore (n = 6393) consisting of Chinese, Malays, and Indians and 3 cohorts of European-origin participants from Finland (n = 14 558). We used nuclear magnetic resonance to quantify 154 circulating metabolic biomarkers at baseline and performed logistic regression to assess associations with T2D risk adjusted for age, sex, BMI and glycemic markers.

RESULTS

Of the 154 metabolic biomarkers, 59 were associated with higher risk of T2D in both Asians and Europeans (P < 0.0003, Bonferroni-corrected). These included branched chain and aromatic amino acids, the inflammatory marker glycoprotein acetyls, total fatty acids, monounsaturated fatty acids, apolipoprotein B, larger very low-density lipoprotein particle sizes, and triglycerides. In addition, 13 metabolites were associated with a lower T2D risk in both populations, including omega-6 polyunsaturated fatty acids and larger high-density lipoprotein particle sizes. Associations were consistent within the Asian ethnic groups (all Phet ≥ 0.05) and largely consistent for the Asian and European populations (Phet ≥ 0.05 for 128 of 154 metabolic biomarkers).

CONCLUSION

Metabolic biomarkers across several biological pathways were consistently associated with T2D risk in Asians and Europeans.

Metabolomics profile of 5649 users and non-users of hormonal intrauterine devices in Finland

BACKGROUND

Use of hormonal intrauterine devices has grown during the last decades. Although the hormonal intrauterine devices act mostly via local effects on uterus, measurable concentrations of levonorgestrel are absorbed into the systemic circulation. The possible metabolic changes and large scale biomarker profiles associated with the hormonal intrauterine devices have not yet been studied in detail.

OBJECTIVES

To examine, through the metabolomics approach, the metabolic profile of the hormonal intrauterine device use, its associations as a function of the duration of use, as well as those with after discontinuation of the hormonal intrauterine device use.

STUDY DESIGN

The study consists of cross-sectional analyses of five population-based surveys (FINRISK and FinHealth studies), spanning 1997-2017. All fertile aged (18-49 years) participants in the surveys with available information on hormonal contraceptive use and metabolomics data (n=5649), were included in the study. Altogether 211 metabolic measures in users of hormonal intrauterine devices (n=1006) were compared to those in non-users of hormonal contraception (n=4643) via multivariable linear regression models. In order to allow the comparison across multiple measures, association magnitudes are reported in SD units of difference in biomarker concentration compared to the reference group.

RESULTS

After adjustment for covariates, levels of 141 metabolites differed in current users of hormonal intrauterine devices compared to non-users of hormonal contraception (median difference in biomarker concentration: 0.09 SD): lower levels of particle concentration of larger lipoprotein subclasses, triglycerides, cholesterol and derivatives, apolipoproteins A and B, fatty acids, glycoprotein acetyls and aromatic amino acids. The metabolic pattern of the hormonal intrauterine device use did not change according to the duration of use. When comparing previous users and never-users of hormonal intrauterine devices, no significant metabolic differences emerged.

CONCLUSIONS

The use of hormonal intrauterine devices was associated with several moderate metabolic changes, previously associated with reduced arterial cardiometabolic risk. The metabolic effects were independent of the duration of use of the hormonal intrauterine devices. Moreover, the metabolic profiles were similar after discontinuation of the hormonal intrauterine devices and in never-users.

Risk of Dementia After Hospitalization Due to Traumatic Brain Injury: A Longitudinal Population-Based Study

BACKGROUND AND OBJECTIVES

Traumatic brain injury (TBI) is considered a potential modifiable dementia risk factor. We aimed to determine whether TBI actually increases the risk of dementia when adjusting for other relevant dementia risk factors.

METHODS

This was a national prospective longitudinal cohort study that included random and representative population samples from different parts of Finland of patients 25 through 64 years of age from 1992 to 2012. Major TBI was defined as a diagnosis of traumatic intracranial hemorrhage and hospital length of stay (LOS) ≥3 days and minor TBI was defined as a diagnosis of concussion and hospital LOS ≤1 day. Dementia was defined as any first hospital contact with a diagnosis of dementia, first use of an antidementia drug, or dementia as an underlying or contributing cause of death. Follow-up was until death or end of 2017.

RESULTS

Of 31,909 participants, 288 were hospitalized due to a major TBI and 406 were hospitalized due to a minor TBI. There was a total of 976 incident dementia cases during a median follow-up of 15.8 years. After adjusting for age and sex, hospitalization due to major TBI (hazard ratio [HR] 1.51, 95% CI 1.03-2.22), but not minor TBI, increased the risk of dementia. After additional adjustment for educational status, smoking status, alcohol consumption, physical activity, and hypertension, the association between major TBI and dementia weakened (HR 1.30, 95% CI 0.86-1.97). The risk factors most strongly attenuating the association between major TBI and dementia were alcohol consumption and physical activity.

DISCUSSION

There was an association between hospitalized major TBI and incident dementia. The association was diluted after adjusting for confounders, especially alcohol consumption and physical activity. Hospitalization due to minor TBI was not associated with an increased risk of dementia.

CLASSIFICATION OF EVIDENCE

This study provides Class I evidence that major TBI is associated with incident dementia.

Study protocol for an epidemiological study 'Multimorbidity - identifying the most burdensome patterns, risk factors and potentials to reduce future burden (MOLTO)' based on the Finnish health examination surveys and the ongoing register-based follow-up

INTRODUCTION

Multimorbidity, defined as the co-occurrence of two or more long-term medical conditions, is an increasing public health concern worldwide causing enormous burden to individuals, healthcare systems and societies. The most effective way of decreasing the burden caused by multimorbidity is to find tools for its successful prevention but gaps in research evidence limit capacities to develop prevention strategies. The aim of the MOLTO study (Multimorbidity - identifying the most burdensome patterns, risk factors and potentials to reduce future burden) is to provide novel evidence required for cost-effective prevention of multimorbidity by defining the multimorbidity patterns causing the greatest burden at the population level, by examining their risk and protective factors and by estimating the potentials to reduce the future burden.

METHODS AND ANALYSIS

The MOLTO study is based on the data from the Finnish population-based cross-sectional (FINRISK 2002-2012, FinHealth 2017 the Migrant Health and Well-being Study 2010-2012) and longitudinal (Health 2000/2011) health examination surveys with individual-level link to administrative health registers, allowing register-based follow-up for the study participants. Both cross-sectional and longitudinal study designs will be used. Multimorbidity patterns will be defined using latent class analysis. The burden caused by multimorbidity as well as risk and protective factors for multimorbidity will be analysed by survival analysis methods such as Cox proportional hazards and Poisson regression models.

ETHICS AND DISSEMINATION

The survey data have been collected following the legislation at the time of the survey. The ethics committee of the Hospital District of Helsinki and Uusimaa has approved the data collection and register linkages for each survey. The results will be published as peer-reviewed scientific publications.

Risk factors for major gastrointestinal bleeding in the general population in Finland

BACKGROUND

Data on non-drug related risk-factors for gastrointestinal bleeding (GIB) in the general population are limited, especially for life-style factors, clinical measurements and laboratory parameters.

AIM

To identify and investigate non-drug risk factors for major GIB in the general population of Finland.

METHODS

We performed a retrospective cohort study using data from the FINRISK health examination surveys, which have been conducted every 5 years across Finland from 1987 to 2007. Participants were adults aged 25 years to 74 years, excluding those with a previous hospitalization for GIB. Follow-up from enrollment was performed through linkage to national electronic health registers and ended at an event of GIB that led to hospitalization/death, death due to any other cause, or after 10 years. Covariates included demographics, socioeconomic and lifestyle factors, clinical measurements, laboratory parameters and comorbidities. Variable selection was undertaken using Least Absolute Shrinkage and Selection Operator (LASSO) and factors associated with GIB were identified using Cox regression.

RESULTS

Among 33,508 participants, 403 (1.2%) experienced GIB [256 men (63.5%); mean age, 56.0 years (standard deviation (SD) ± 12.1)] and 33105 who did not experience GIB [15768 men (47.6%); mean age, 46.8 (SD ± 13) years], within 10 years of follow-up. Factors associated with a significantly increased risk of GIB were baseline age [per 10-year increase; hazard ratio (HR) 1.62, 95% confidence interval (CI): 1.42-1.86], unemployment (HR: 1.70, 95%CI: 1.11-2.59), body mass index (BMI) (HR: 1.15, 95%CI: 1.01-1.32), gamma-glutamyl transferase (GGT) (HR: 1.05, 95%CI: 1.02-1.09), precursors of GIB (HR: 1.90, 95%CI: 1.37-2.63), cancer (HR: 1.47, 95%CI: 1.10-1.97), psychiatric disorders (HR: 1.32, 95%CI: 1.01-1.71), heart failure (HR: 1.46, 95%CI: 1.04-2.05), and liver disorders (HR: 3.20, 95%CI: 2.06-4.97). Factors associated with a significantly decreased risk of GIB were systolic blood pressure (SBP) (HR: 0.78, 95%CI: 0.64-0.96), 6-10 cups of coffee a day (HR: 0.67, 95%CI: 0.46-0.99), or > 10 cups (HR: 0.43, 95%CI: 0.23-0.81).

CONCLUSION

Our study confirms established risk-factors for GIB and identifies potential risk-factors not previously reported such as unemployment, BMI, GGT, SBP and coffee consumption.

Early prediction of incident liver disease using conventional risk factors and gut-microbiome-augmented gradient boosting

The gut microbiome has shown promise as a predictive biomarker for various diseases. However, the potential of gut microbiota for prospective risk prediction of liver disease has not been assessed. Here, we utilized shallow shotgun metagenomic sequencing of a large population-based cohort (N > 7,000) with ∼15 years of follow-up in combination with machine learning to investigate the predictive capacity of gut microbial predictors individually and in conjunction with conventional risk factors for incident liver disease. Separately, conventional and microbial factors showed comparable predictive capacity. However, microbiome augmentation of conventional risk factors using machine learning significantly improved the performance. Similarly, disease-free survival analysis showed significantly improved stratification using microbiome-augmented models. Investigation of predictive microbial signatures revealed previously unknown taxa for liver disease, as well as those previously associated with hepatic function and disease. This study supports the potential clinical validity of gut metagenomic sequencing to complement conventional risk factors for prediction of liver diseases.

Phylogeny-Aware Analysis of Metagenome Community Ecology Based on Matched Reference Genomes while Bypassing Taxonomy

We introduce the operational genomic unit (OGU) method, a metagenome analysis strategy that directly exploits sequence alignment hits to individual reference genomes as the minimum unit for assessing the diversity of microbial communities and their relevance to environmental factors. This approach is independent of taxonomic classification, granting the possibility of maximal resolution of community composition, and organizes features into an accurate hierarchy using a phylogenomic tree. The outputs are suitable for contemporary analytical protocols for community ecology, differential abundance, and supervised learning while supporting phylogenetic methods, such as UniFrac and phylofactorization, that are seldom applied to shotgun metagenomics despite being prevalent in 16S rRNA gene amplicon studies. As demonstrated in two real-world case studies, the OGU method produces biologically meaningful patterns from microbiome data sets. Such patterns further remain detectable at very low metagenomic sequencing depths. Compared with taxonomic unit-based analyses implemented in currently adopted metagenomics tools, and the analysis of 16S rRNA gene amplicon sequence variants, this method shows superiority in informing biologically relevant insights, including stronger correlation with body environment and host sex on the Human Microbiome Project data set and more accurate prediction of human age by the gut microbiomes of Finnish individuals included in the FINRISK 2002 cohort. We provide Woltka, a bioinformatics tool to implement this method, with full integration with the QIIME 2 package and the Qiita web platform, to facilitate adoption of the OGU method in future metagenomics studies. IMPORTANCE Shotgun metagenomics is a powerful, yet computationally challenging, technique compared to 16S rRNA gene amplicon sequencing for decoding the composition and structure of microbial communities. Current analyses of metagenomic data are primarily based on taxonomic classification, which is limited in feature resolution. To solve these challenges, we introduce operational genomic units (OGUs), which are the individual reference genomes derived from sequence alignment results, without further assigning them taxonomy. The OGU method advances current read-based metagenomics in two dimensions: (i) providing maximal resolution of community composition and (ii) permitting use of phylogeny-aware tools. Our analysis of real-world data sets shows that it is advantageous over currently adopted metagenomic analysis methods and the finest-grained 16S rRNA analysis methods in predicting biological traits. We thus propose the adoption of OGUs as an effective practice in metagenomic studies.

Gut Microbiota–Brain Axis as a Potential Modulator of Psychological Stress after Spinal Cord Injury

A growing body of evidence from preclinical and clinical studies has associated alterations of the gut microbiota–brain axis with the progression and development of a number of pathological conditions that also affect cognitive functions. Spinal cord injuries (SCIs) can be produced from traumatic and non-traumatic causes. It has been reported that SCIs are commonly associated with anxiety and depression-like symptoms, showing an incidence range between 11 and 30% after the injury. These psychological stress-related symptoms are associated with worse prognoses in SCIs and have been attributed to psychosocial stressors and losses of independence. Nevertheless, emotional and mental modifications after SCI could be related to changes in the volume of specific brain areas associated with information processing and emotions. Additionally, physiological modifications have been recognized as a predisposing factor for mental health depletion, including the development of gut dysbiosis. This condition of imbalance in microbiota composition has been shown to be associated with depression in clinical and pre-clinical models. Therefore, the understanding of the mechanisms underlying the relationship between SCIs, gut dysbiosis and psychological stress could contribute to the development of novel therapeutic strategies to improve SCI patients’ quality of life.

How Communicating Polygenic and Clinical Risk for Atherosclerotic Cardiovascular Disease Impacts Health Behavior: an Observational Follow-up Study

BACKGROUND

Prediction tools that combine polygenic risk scores with clinical factors provide a new opportunity for improved prediction and prevention of atherosclerotic cardiovascular disease, but the clinical utility of polygenic risk score has remained unclear.

METHODS

We collected a prospective cohort of 7342 individuals (64% women, mean age 56 years) and estimated their 10-year risk for atherosclerotic cardiovascular disease both by a traditional risk score and a composite score combining the effect of a polygenic risk score and clinical risk factors. We then tested how returning the personal risk information with an interactive web-tool impacted on the participants' health behavior.

RESULTS

When reassessed after 1.5 years by a clinical visit and questionnaires, 20.8% of individuals at high (>10%) 10-year atherosclerotic cardiovascular disease risk had seen a doctor, 12.4% reported weight loss, 14.2% of smokers had quit smoking, and 15.4% had signed up for health coaching online. Altogether, 42.6% of persons at high risk had made one or more health behavioral changes versus 33.5% of persons at low/average risk such that higher baseline risk predicted a favorable change (OR [CI], 1.53 [1.37-1.72] for persons at high risk versus the rest, P<0.001), with both high clinical (P<0.001) and genomic risk (OR [CI], 1.10 [1.03-1.17], P=0.003) contributing independently.

CONCLUSIONS

Web-based communication of personal atherosclerotic cardiovascular disease risk-data including polygenic risk to middle-aged persons motivates positive changes in health behavior and the propensity to seek care. It supports integration of genomic information into clinical risk calculators as a feasible approach to enhance disease prevention.

Obesity Does Not Protect From Subarachnoid Hemorrhage: Pooled Analyses of 3 Large Prospective Nordic Cohorts

BACKGROUND

Several population-based cohort studies have related higher body mass index (BMI) to a decreased risk of subarachnoid hemorrhage (SAH). The main objective of our study was to investigate whether the previously reported inverse association can be explained by modifying effects of the most important risk factors of SAH-smoking and hypertension.

METHODS

We conducted a collaborative study of three prospective population-based Nordic cohorts by combining comprehensive baseline data from 211 972 adult participants collected between 1972 and 2012, with follow-up until the end of 2018. Primarily, we compared the risk of SAH between three BMI categories: (1) low (BMI<22.5), (2) moderate (BMI: 22.5-29.9), and (3) high (BMI≥30) BMI and evaluated the modifying effects of smoking and hypertension on the associations.

RESULTS

We identified 831 SAH events (mean age 62 years, 55% women) during the total follow-up of 4.7 million person-years. Compared with the moderate BMI category, persons with low BMI had an elevated risk for SAH (adjusted hazard ratio [HR], 1.30 [1.09-1.55]), whereas no significant risk difference was found in high BMI category (HR, 0.91 [0.73-1.13]). However, we only found the increased risk of low BMI in smokers (HR, 1.49 [1.19-1.88]) and in hypertensive men (HR, 1.72 [1.18-2.50]), but not in nonsmokers (HR, 1.02 [0.76-1.37]) or in men with normal blood pressure values (HR, 0.98 [0.63-1.54]; interaction HRs, 1.68 [1.18-2.41], P=0.004 between low BMI and smoking and 1.76 [0.98-3.13], P=0.06 between low BMI and hypertension in men).

CONCLUSIONS

Smoking and hypertension appear to explain, at least partly, the previously reported inverse association between BMI and the risk of SAH. Therefore, the independent role of BMI in the risk of SAH is likely modest.

Gut Microbiome Composition Is Predictive of Incident Type 2 Diabetes in a Population Cohort of 5,572 Finnish Adults

OBJECTIVE

To examine the previously unknown long-term association between gut microbiome composition and incident type 2 diabetes in a representative population cohort.

RESEARCH DESIGN AND METHODS

We collected fecal samples from 5,572 Finns (mean age 48.7 years; 54.1% women) in 2002 who were followed up for incident type 2 diabetes until 31 December 2017. The samples were sequenced using shotgun metagenomics. We examined associations between gut microbiome composition and incident diabetes using multivariable-adjusted Cox regression models. We first used the eastern Finland subpopulation to obtain initial findings and validated these in the western Finland subpopulation.

RESULTS

Altogether, 432 cases of incident diabetes occurred over the median follow-up of 15.8 years. We detected four species and two clusters consistently associated with incident diabetes in the validation models. These four species were Clostridium citroniae (hazard ratio [HR] 1.21; 95% CI 1.04-1.42), C. bolteae (HR 1.20; 95% CI 1.04-1.39), Tyzzerella nexilis (HR 1.17; 95% CI 1.01-1.36), and Ruminococcus gnavus (HR 1.17; 95% CI 1.01-1.36). The positively associated clusters, cluster 1 (HR 1.18; 95% CI 1.02-1.38) and cluster 5 (HR 1.18; 95% CI 1.02-1.36), mostly consisted of these same species.

CONCLUSIONS

We observed robust species-level taxonomic features predictive of incident type 2 diabetes over long-term follow-up. These findings build on and extend previous mainly cross-sectional evidence and further support links between dietary habits, metabolic diseases, and type 2 diabetes that are modulated by the gut microbiome. The gut microbiome can potentially be used to improve disease prediction and uncover novel therapeutic targets for diabetes.

National Genome Initiatives in Europe and the United Kingdom in the Era of Whole-Genome Sequencing: A Comprehensive Review

Identification of genomic variability in population plays an important role in the clinical diagnostics of human genetic diseases. Thanks to rapid technological development in the field of massive parallel sequencing technologies, also known as next-generation sequencing (NGS), complex genomic analyses are now easier and cheaper than ever before, which consequently leads to more effective utilization of these techniques in clinical practice. However, interpretation of data from NGS is still challenging due to several issues caused by natural variability of DNA sequences in human populations. Therefore, development and realization of projects focused on description of genetic variability of local population (often called "national or digital genome") with a NGS technique is one of the best approaches to address this problem. The next step of the process is to share such data via publicly available databases. Such databases are important for the interpretation of variants with unknown significance or (likely) pathogenic variants in rare diseases or cancer or generally for identification of pathological variants in a patient's genome. In this paper, we have compiled an overview of published results of local genome sequencing projects from United Kingdom and Europe together with future plans and perspectives for newly announced ones.

Pairwise association of key lifestyle factors and risk of colorectal cancer: a prospective pooled multicohort study

BACKGROUND

Several lifestyle factors are associated with an increased risk of colorectal cancer (CRC). Although lifestyle factors co-occur, in most previous studies these factors have been studied focusing upon a single risk factor or assuming independent effects between risk factors.

AIM

To examine the pairwise effects and interactions of smoking, alcohol consumption, physical inactivity, and body mass index (BMI) with risk of subsequent colorectal cancer (CRC).

METHODS AND RESULTS

We used METCA cohort data (pooled data from seven population-based Finnish health behavior survey studies during years 1972-2015) consisting of 171 063 women and men. Participants' smoking, alcohol consumption, physical inactivity and BMI measures were gathered, and participants were categorized into those exposed and those not exposed. The incidence of CRC was modeled by Poisson regression with main and interaction effects of key lifestyle factors. The cohort members were followed-up through register linkage to the Finnish Cancer Registry for first primary CRC case until the end of 2015. Follow-up time was 1715, 690 person years. The highest pairwise CRC risk was among male smokers who had overweight (BMI ≥ 25 kg/m² ) (HR 1.75, 95% CI 1.36-2.26) and women who had overweight and consumed alcohol (HR 1.45, 95% CI 1.14-1.85). Overall, among men the association of lifestyle factors and CRC risk was stronger than among women. In men, both having overweight and being a smoker combined with any other adverse lifestyle factor increased CRC risk. Among women, elevated CRC risks were observed for those who were physically inactive and who consumed alcohol or had overweight. No statistically significant interactions were detected between pairs of lifestyle factors.

CONCLUSIONS

This study strengthens the evidence of overweight, smoking, and alcohol consumption as CRC risk factors. Substantial protective benefits in CRC risk can be achieved by preventing smoking, maintaining BMI to <25 kg/m² and not consuming alcohol.

Joint associations of depression, genetic susceptibility and the area of residence for coronary heart disease incidence

BACKGROUND

Depression is a risk factor for coronary heart disease (CHD), but less is known whether genetic susceptibility to CHD or regional-level social indicators modify this association.

METHODS

Risk factors of CHD including a Polygenic Risk Score (PRS) were measured for 19 999 individuals residing in Finland in 1997, 2002, 2007 and 2012 (response rates 60%-75%). During the register-based follow-up until 2015, there were 1381 fatal and non-fatal incident CHD events. Unemployment rate, degree of urbanisation and crime rate of the municipality of residence were used as regional level social indicators. HRs were calculated using register-based antidepressant purchases as a non-reversible time-dependent covariate.

RESULTS

Those having depression and in the highest quartile of PRS had somewhat higher CHD risk than predicted only by the main effects of depression and PRS (HR for interaction 1.53, 95% CI 0.95 to 2.45). Depression was moderately associated with CHD in high crime (HR 1.51, 95% CI 1.20 to 1.90) and weakly in low crime regions (HR 1.07, 95% CI 0.86 to 1.33; p value of interaction=0.087). Otherwise, we did not found evidence for interactions.

CONCLUSIONS

Those having both depression and high genetic susceptibility need a special attention in healthcare for CHD.

A plasma metabolite score of three eicosanoids predicts incident type 2 diabetes: a prospective study in three independent cohorts

INTRODUCTION

Peptide markers of inflammation have been associated with the development of type 2 diabetes. The role of upstream, lipid-derived mediators of inflammation such as eicosanoids, remains less clear. The aim of this study was to examine whether eicosanoids are associated with incident type 2 diabetes.

RESEARCH DESIGN & METHODS

In the FINRISK (Finnish Cardiovascular Risk Study) 2002 study, a population-based sample of Finnish men and women aged 25-74 years, we used directed, non-targeted liquid chromatography-mass spectrometry to identify 545 eicosanoids and related oxylipins in the participants' plasma samples (n=8292). We used multivariable-adjusted Cox regression to examine associations between eicosanoids and incident type 2 diabetes. The significant independent findings were replicated in the Framingham Heart Study (FHS, n=2886) and DIetary, Lifestyle and Genetic determinants of Obesity and Metabolic syndrome (DILGOM) 2007 (n=3905). Together, these three cohorts had 1070 cases of incident type 2 diabetes.

RESULTS

In the FINRISK 2002 cohort, 76 eicosanoids were associated individually with incident type 2 diabetes. We identified three eicosanoids independently associated with incident type 2 diabetes using stepwise Cox regression with forward selection and a Bonferroni-corrected inclusion threshold. A three-eicosanoid risk score produced an HR of 1.56 (95% CI 1.41 to 1.72) per 1 SD increment for risk of incident diabetes. The HR for comparing the top quartile with the lowest was 2.80 (95% CI 2.53 to 3.07). In the replication analyses, the three-eicosanoid risk score was significant in FHS (HR 1.24 (95% CI 1.10 to 1.39, p<0.001)) and directionally consistent in DILGOM (HR 1.12 (95% CI 0.99 to 1.27, p=0.07)). Meta-analysis of the three cohorts yielded a pooled HR of 1.31 (95% CI 1.05 to 1.56).

CONCLUSIONS

Plasma eicosanoid profiles predict incident type 2 diabetes and the clearest signals replicate in three independent cohorts. Our findings give new information on the biology underlying type 2 diabetes and suggest opportunities for early identification of people at risk.

Multiparametric platform for profiling lipid trafficking in human leukocytes

Systematic insight into cellular dysfunction can improve understanding of disease etiology, risk assessment, and patient stratification. We present a multiparametric high-content imaging platform enabling quantification of low-density lipoprotein (LDL) uptake and lipid storage in cytoplasmic droplets of primary leukocyte subpopulations. We validate this platform with samples from 65 individuals with variable blood LDL-cholesterol (LDL-c) levels, including familial hypercholesterolemia (FH) and non-FH subjects. We integrate lipid storage data into another readout parameter, lipid mobilization, measuring the efficiency with which cells deplete lipid reservoirs. Lipid mobilization correlates positively with LDL uptake and negatively with hypercholesterolemia and age, improving differentiation of individuals with normal and elevated LDL-c. Moreover, combination of cell-based readouts with a polygenic risk score for LDL-c explains hypercholesterolemia better than the genetic risk score alone. This platform provides functional insights into cellular lipid trafficking and has broad possible applications in dissecting the cellular basis of metabolic disorders.

Integration of questionnaire-based risk factors improves polygenic risk scores for human coronary heart disease and type 2 diabetes

Large-scale biobank initiatives and commercial repositories store genomic data collected from millions of individuals, and tools to leverage the rapidly growing pool of health and genomic data in disease prevention are needed. Here, we describe the derivation and validation of genomics-enhanced risk tools for two common cardiometabolic diseases, coronary heart disease and type 2 diabetes. Data used for our analyses include the FinnGen study (N = 309,154) and the UK Biobank project (N = 343,672). The risk tools integrate contemporary genome-wide polygenic risk scores with simple questionnaire-based risk factors, including demographic, lifestyle, medication, and comorbidity data, enabling risk calculation across resources where genome data is available. Compared to routinely used clinical risk scores for coronary heart disease and type 2 diabetes prevention, the risk tools show at least equivalent risk discrimination, improved risk reclassification (overall net reclassification improvements ranging from 3.7 [95% CI 2.8–4.6] up to 6.2 [4.6–7.8]), and capacity to be improved even further with standard lipid and blood pressure measurements. Without the need for blood tests or evaluation by a health professional, the risk tools provide a powerful yet simple method for preliminary cardiometabolic risk assessment for individuals with genome data available.

Max Tamlander et al. combine polygenic risk scores and clinical assessments to improve prediction of coronary artery disease and type 2 diabetes in European cohorts. Taken together, their results provide a useful method for preliminary cardiometabolic risk assessment in patients.

Polygenic Score for Physical Activity Is Associated with Multiple Common Diseases

INTRODUCTION

Genetic pleiotropy, in which the same genes affect two or more traits, may partially explain the frequently observed associations between high physical activity (PA) and later reduced morbidity or mortality. This study investigated associations between PA polygenic risk scores (PRS) and cardiometabolic diseases among the Finnish population.

METHODS

PRS for device-measured overall PA were adapted to a FinnGen study cohort of 218,792 individuals with genomewide genotyping and extensive digital longitudinal health register data. Associations between PA PRS and body mass index, diseases, and mortality were analyzed with linear and logistic regression models.

RESULTS

A high PA PRS predicted a lower body mass index (β = -0.025 kg·m-2 per one SD change in PA PRS, SE = 0.013, P = 1.87 × 10-80). The PA PRS also predicted a lower risk for diseases that typically develop later in life or not at all among highly active individuals. A lower disease risk was systematically observed for cardiovascular diseases (odds ratio [OR] per 1 SD change in PA PRS = 0.95, P = 9.5 × 10-19) and, for example, hypertension [OR = 0.93, P = 2.7 × 10-44), type 2 diabetes (OR = 0.91, P = 4.1 × 10-42), and coronary heart disease (OR = 0.95, P = 1.2 × 10-9). Participants with high PA PRS had also lower mortality risk (OR = 0.97, P = 0.0003).

CONCLUSIONS

Genetically less active persons are at a higher risk of developing cardiometabolic diseases, which may partly explain the previously observed associations between low PA and higher disease and mortality risk. The same inherited physical fitness and metabolism-related mechanisms may be associated both with PA levels and with cardiometabolic disease risk.

Working Conditions and Long-Term Sickness Absence Due to Mental Disorders: A Prospective Record Linkage Cohort Study Among 19- to 39-Year-Old Female Municipal Employees

OBJECTIVE

We examined associations between working conditions and long-term sickness absence due to mental disorders (LTSA-MD) among younger female public sector employees from different employment sectors.

METHODS

Survey data collected in 2017 (n = 3048) among 19- to 39-year-old female employees of the City of Helsinki, Finland, were used to examine job demands, job control, physical workload, computer work, and covariates. Register data on LTSA-MD were used over 1-year follow-up. Negative binomial regression models were applied.

RESULTS

Adverse psychosocial and physical working conditions were associated with higher LTSA-MD during the follow-up. Health and social care workers had the highest number of days of LTSA-MD.

CONCLUSION

Working conditions are important factors when aiming to prevent LTSA-MD among younger employees, in the health and social care sector in particular.

Combined effects of host genetics and diet on human gut microbiota and incident disease in a single population cohort

Human genetic variation affects the gut microbiota through a complex combination of environmental and host factors. Here we characterize genetic variations associated with microbial abundances in a single large-scale population-based cohort of 5,959 genotyped individuals with matched gut microbial metagenomes, and dietary and health records (prevalent and follow-up). We identified 567 independent SNP-taxon associations. Variants at the LCT locus associated with Bifidobacterium and other taxa, but they differed according to dairy intake. Furthermore, levels of Faecalicatena lactaris associated with ABO, and suggested preferential utilization of secreted blood antigens as energy source in the gut. Enterococcus faecalis levels associated with variants in the MED13L locus, which has been linked to colorectal cancer. Mendelian randomization analysis indicated a potential causal effect of Morganella on major depressive disorder, consistent with observational incident disease analysis. Overall, we identify and characterize the intricate nature of host-microbiota interactions and their association with disease.

APOE ε4 associates with increased risk of severe COVID-19, cerebral microhaemorrhages and post-COVID mental fatigue: a Finnish biobank, autopsy and clinical study

Apolipoprotein E ε4 allele (APOE4) has been shown to associate with increased susceptibility to SARS-CoV-2 infection and COVID-19 mortality in some previous genetic studies, but information on the role of APOE4 on the underlying pathology and parallel clinical manifestations is scarce. Here we studied the genetic association between APOE and COVID-19 in Finnish biobank, autopsy and prospective clinical cohort datasets. In line with previous work, our data on 2611 cases showed that APOE4 carriership associates with severe COVID-19 in intensive care patients compared with non-infected population controls after matching for age, sex and cardiovascular disease status. Histopathological examination of brain autopsy material of 21 COVID-19 cases provided evidence that perivascular microhaemorrhages are more prevalent in APOE4 carriers. Finally, our analysis of post-COVID fatigue in a prospective clinical cohort of 156 subjects revealed that APOE4 carriership independently associates with higher mental fatigue compared to non-carriers at six months after initial illness. In conclusion, the present data on Finns suggests that APOE4 is a risk factor for severe COVID-19 and post-COVID mental fatigue and provides the first indication that some of this effect could be mediated via increased cerebrovascular damage. Further studies in larger cohorts and animal models are warranted.

Projections for obesity, smoking and hypertension based on multiple imputation

AIMS

Information on the future development of prevalences of risk factors and health indicators is needed to prepare for the forthcoming burden of disease in the population and to allocate resources properly for prevention. We aim to present how multiple imputation can be used flexibly to project future prevalences.

METHODS

The proposed approach uses data on repeated cross-sectional surveys from different years. We create future samples with age and sex distributions corresponding to the official national population forecasts. Then, the risk factors are simulated using multiple imputation by chained equations. Finally, the imputations are pooled to obtain the prevalences of interest. Covariates, such as sociodemographic variables as well as their possible interactions and non-linear terms, can be included in the modelling. The future development of these covariates is also projected simultaneously. We apply the procedure to data from five Finnish health examination surveys conducted between 1997 and 2017, and project the prevalences of obesity, smoking and hypertension to 2020 and 2025.

RESULTS

The prevalence of obesity is projected to increase to 24% for both men and women in 2025. The prevalences of hypertension and smoking are expected to continue decreasing, and the differences between men and women are projected to remain so that men will have higher prevalences.

CONCLUSIONS

Simulation of future observations by multiple imputation can be used as a flexible yet relatively easy-to-use projection method.

Metabolic Biomarker Discovery for Risk of Peripheral Artery Disease Compared With Coronary Artery Disease: Lipoprotein and Metabolite Profiling of 31 657 Individuals From 5 Prospective Cohorts

Background Peripheral artery disease (PAD) and coronary artery disease (CAD) represent atherosclerosis in different vascular beds. We used detailed metabolic biomarker profiling to identify common and discordant biomarkers and clarify pathophysiological differences for these vascular diseases. Methods and Results We used 5 prospective cohorts from Finnish population (FINRISK 1997, 2002, 2007, and 2012, and Health 2000; n=31 657; median follow-up time of 14 years) to estimate associations between >200 metabolic biomarkers and incident PAD and CAD. Metabolic biomarkers were measured with nuclear magnetic resonance, and disease events were obtained from nationwide hospital records. During the follow-up, 498 incident PAD and 2073 incident CAD events occurred. In age- and sex-adjusted Cox models, apolipoproteins and cholesterol measures were robustly associated with incident CAD (eg, hazard ratio [HR] per SD for higher apolipoprotein B/A-1 ratio, 1.30; 95% CI, 1.25-1.36), but not with incident PAD (HR per SD for higher apolipoprotein B/A-1 ratio, 1.04; 95% CI, 0.95-1.14; P_{heterogeneity}<0.001). In contrast, triglyceride levels in low-density lipoprotein and high-density lipoprotein were associated with both end points (P_{heterogeneity}>0.05). Lower proportion of polyunsaturated fatty acids relative to total fatty acids, and higher concentrations of monounsaturated fatty acids, glycolysis-related metabolites, and inflammatory protein markers were strongly associated with incident PAD, and many of these associations were stronger for PAD than for CAD (P_{heterogeneity}<0.001). Most differences in metabolic profiles for PAD and CAD remained when adjusting for traditional risk factors. Conclusions The metabolic biomarker profile for future PAD risk is distinct from that of CAD. This may represent pathophysiological differences.

Waist and hip circumference are independently associated with the risk of liver disease in population-based studies

BACKGROUND & AIMS

While several anthropometric measures predict liver disease, the waist-hip ratio (WHR) has shown superiority in previous studies. We analysed independent and joint associations of waist circumference (WC) and hip circumference (HC) with liver disease and liver-related risk factors.

METHODS

Cross-sectional study (n = 6619) and longitudinal cohort (n = 40 923) comprised individuals from Health 2000 and FINRISK 1992-2012 studies. Prevalent and viral liver diseases were excluded. Longitudinal cohort was linked with national healthcare registers for severe incident liver disease. Linear regression and Cox proportional hazards models were used to analyse anthropometric, lifestyle, metabolic and bioimpedance-related parameters; liver enzymes; and 59 liver-related genetic risk variants.

RESULTS

WC and HC showed independent and opposite associations with both liver enzymes and incident liver disease among men (HR for liver disease: WC, 1.07, 95% CI 1.03-1.11; HC, 0.96, 95% CI 0.92-0.99; P-range .04 to <.001) and women (HR for liver diseases: WC, 1.06, 95% CI 1.02-1.10; HC, 0.93, 95% CI 0.89-0.98; P-range .005 to .004). HC modified associations between WC and liver enzymes, and between WC and incident liver disease, particularly among men. Liver enzymes and risk of liver disease increased with increasing WC, more so among individuals with high WHR compared to with low WHR. WC and HC jointly reflected both body fat distribution and muscle mass, which was largely mirrored by WHR.

CONCLUSIONS

WC and HC exhibit independent and joint associations with liver disease, which are largely reflected by WHR. Both body fat distribution and muscle mass contribute to these anthropometric measures.

Adverse Effects of Refeeding on the Plasma Lipidome in Young Individuals With Anorexia Nervosa?

OBJECTIVE

Refeeding is the cornerstone of anorexia nervosa (AN) treatment, but little is known regarding the optimal pace and dietary composition or possible adverse effects of current clinical practices. Plasma lipids may be a moderating factor underlying unfavorable refeeding effects in AN, such as an abnormal central body fat distribution. The objective of this study was to analyze the plasma lipidome in the acutely underweight state of AN before and after refeeding.

METHOD

Using high-throughput quantitative mass spectrometry-based shotgun lipidomics, we measured 13 lipid classes and 204 lipid species or subspecies in the plasma of young female patients with acute AN, before (n = 39) and after (n = 23) short-term weight restoration during an intensive inpatient refeeding program (median body mass index [BMI] increase = 26.4%), in comparison to those in healthy control participants (n = 37).

RESULTS

Before inpatient treatment, patients with AN exhibited increased concentrations of cholesterol and several other lipid classes. After refeeding, multiple lipid classes including cholesterol and ceramides, as well as certain ceramide species previously associated with obesity or overfeeding, showed increased concentrations, and a pattern of shorter and more saturated triacylgycerides emerged. A machine learning model trained to predict BMI based on the lipidomic profiles revealed a sizable overprediction in patients with AN after weight restoration.

CONCLUSION

The results point toward a profound lipid dysregulation with similarities to obesity and other features of the metabolic syndrome after short-term weight restoration. Thus, this study provides evidence for possible short-term adverse effects of current refeeding practices on the metabolic state and should inspire more research on nutritional interventions in AN.

Risk factors for major adverse cardiovascular events after the first acute coronary syndrome

AIMS

To evaluate risk factors for major adverse cardiac event (MACE) after the first acute coronary syndrome (ACS) and to examine the prevalence of risk factors in post-ACS patients.

METHODS

We used Finnish population-based myocardial infarction register, FINAMI, data from years 1993-2011 to identify survivors of first ACS (n = 12686), who were then followed up for recurrent events and all-cause mortality for three years. Finnish FINRISK risk factor surveys were used to determine the prevalence of risk factors (smoking, hyperlipidaemia, diabetes and blood pressure) in post-ACS patients (n = 199).

RESULTS

Of the first ACS survivors, 48.4% had MACE within three years of their primary event, 17.0% were fatal. Diabetes (p = 4.4 × 10-7), heart failure (HF) during the first ACS attack hospitalization (p = 6.8 × 10-15), higher Charlson index (p = 1.56 × 10-19) and older age (p = .026) were associated with elevated risk for MACE in the three-year follow-up, and revascularization (p = .0036) was associated with reduced risk. Risk factor analyses showed that 23% of ACS survivors continued smoking and cholesterol levels were still high (>5mmol/l) in 24% although 86% of the patients were taking lipid lowering medication.

CONCLUSION

Diabetes, higher Charlson index and HF are the most important risk factors of MACE after the first ACS. Cardiovascular risk factor levels were still high among survivors of first ACS.

Absolute and relative risk prediction in cardiovascular primary prevention with a modified SCORE chart incorporating ceramide-phospholipid risk score and diabetes mellitus

Aims

A risk score, CERT2, based on distinct ceramide and phosphatidylcholine lipid species, has shown robust performance in predicting cardiovascular risk in secondary prevention. Here, our aim was to investigate the predictive value of CERT2 in primary prevention compared to classical lipid biomarkers and its compatibility with clinical characteristics used in the SCORE risk chart.

Methods and results

Four ceramides [Cer(d18:1/16:0), Cer(d18:1/18:0), Cer(d18:1/24:0), Cer(d18:1/24:1)] and three phosphatidylcholines [PC(14:0/22:6), PC(16:0/22:5), PC(16:0/16:0)] were analysed by targeted tandem liquid chromatography–mass spectrometry method in FINRISK 2002, which is a population-based risk factor survey investigating men and women aged 25–74 years. Primary prevention subjects (N = 7324) were followed up for 10 years for the following outcomes: incident coronary heart disease (CHD), cardiovascular disease (CVD), major adverse cardiovascular event (MACE), stroke, and heart failure. Hazard ratios per standard deviation obtained from adjusted Cox proportional hazard models were significant for all these endpoints, and the highest for fatal ones, i.e. fatal CHD [1.45 (95% confidence interval 1.07–1.97)], CVD [1.39 (1.06–1.83)], and MACE [1.39 (1.07–1.80)]. The categorical net reclassification improvement was 0.051 for the 10-year risk of incident CVD. Incidence of fatal events was over 10-fold more frequent in the highest CERT2 category compared to the lowest risk category and modified SCORE risk charts, utilizing CERT2 and diabetes mellitus, increased granularity of risk assessment compared to a chart utilizing total cholesterol.

Conclusion

CERT2 is a significant predictor of incident cardiovascular outcomes and risk charts utilizing this score provide an easy tool to estimate relative and absolute risk for incident CVD.

Genetic Profile of Endotoxemia Reveals an Association With Thromboembolism and Stroke

Background Translocation of lipopolysaccharide from gram-negative bacteria into the systemic circulation results in endotoxemia. In addition to acute infections, endotoxemia is detected in cardiometabolic disorders, such as cardiovascular diseases and obesity. Methods and Results We performed a genome-wide association study of serum lipopolysaccharide activity in 11 296 individuals from 6 different Finnish study cohorts. Endotoxemia was measured by limulus amebocyte lysate assay in the whole population and by 2 other techniques (Endolisa and high-performance liquid chromatography/tandem mass spectrometry) in subpopulations. The associations of the composed genetic risk score of endotoxemia and thrombosis-related clinical end points for 195 170 participants were analyzed in FinnGen. Lipopolysaccharide activity had a genome-wide significant association with 741 single-nucleotide polymorphisms in 5 independent loci, which were mainly located at genes affecting the contact activation of the coagulation cascade and lipoprotein metabolism and explained 1.5% to 9.2% of the variability in lipopolysaccharide activity levels. The closest genes included KNG1, KLKB1, F12, SLC34A1, YPEL4, CLP1, ZDHHC5, SERPING1, CBX5, and LIPC. The genetic risk score of endotoxemia was associated with deep vein thrombosis, pulmonary embolism, pulmonary heart disease, and venous thromboembolism. Conclusions The biological activity of lipopolysaccharide in the circulation (ie, endotoxemia) has a small but highly significant genetic component. Endotoxemia is associated with genetic variation in the contact activation pathway, vasoactivity, and lipoprotein metabolism, which play important roles in host defense, lipopolysaccharide neutralization, and thrombosis, and thereby thromboembolism and stroke.

Efficient computation of Faith's phylogenetic diversity with applications in characterizing microbiomes

The number of publicly available microbiome samples is continually growing. As data set size increases, bottlenecks arise in standard analytical pipelines. Faith's phylogenetic diversity (Faith's PD) is a highly utilized phylogenetic alpha diversity metric that has thus far failed to effectively scale to trees with millions of vertices. Stacked Faith's phylogenetic diversity (SFPhD) enables calculation of this widely adopted diversity metric at a much larger scale by implementing a computationally efficient algorithm. The algorithm reduces the amount of computational resources required, resulting in more accessible software with a reduced carbon footprint, as compared to previous approaches. The new algorithm produces identical results to the previous method. We further demonstrate that the phylogenetic aspect of Faith's PD provides increased power in detecting diversity differences between younger and older populations in the FINRISK study's metagenomic data.

Incidence of liver-related morbidity and mortality in a population cohort of non-alcoholic fatty liver disease

BACKGROUND & AIMS

Non-alcoholic fatty liver disease (NAFLD) increases morbidity and mortality. However, patients in biopsy-based cohorts are highly selected and the absolute risks of liver- and non-liver outcomes in NAFLD in population remains undefined. We analysed both liver-related and non-liver-related outcomes in Finnish population cohorts of NAFLD.

METHODS

We included 10 993 individuals (6707 men, mean age 53.3 ± 12.6 years) with NAFLD (fatty liver index ≥60) from the Finnish population-based FINRISK and Health 2000 studies. Liver fibrosis was assessed by the dAAR score, and genetic risk by a recent polygenic risk score (PRS-5). Incident liver-related outcomes, cardiovascular disease (CVD), cancer and chronic kidney disease (CKD) were identified through linkage with national registries.

RESULTS

Mean follow-up was 12.1 years (1128 069 person-years). The crude incidence rate of liver-related outcomes in NAFLD was 0.97/1000 person-years. The cumulative incidence increased with age, being respectively 2.4% and 1.5% at 20 years in men and women aged 60 years at baseline, while the relative risks for CVD and cancer were 9-16 times higher. The risk of CKD exceeded that of liver outcomes at a baseline age around 50 years. 20-year cumulative incidence of liver-related outcomes was 4.3% in the high, and 1.5% in the low PRS-5 group. The dAAR score associated with liver outcomes, but not with extra-hepatic outcomes.

CONCLUSION

The absolute risk of liver-related outcomes in NAFLD is low, with much higher risk of CVD and cancer, emphasizing the need for more individualized and holistic risk-stratification in NAFLD.

Experiences from the harmonization of Finnish national population-based health survey data

Aims: There are several advantages to pooling survey data from individual studies over time or across different countries. Our aim is to share our experiences on harmonizing data from 13 Finnish health examination surveys covering the years 1972–2017 and to describe the challenges related to harmonizing different variable types using two questionnaire variables – blood pressure measurement and total cholesterol assessment – as examples. Methods: Data from Finnish national population-based health surveys were harmonized as part of the research project ‘Projections of the Burden of Disease and Disability in Finland – Health Policy Prospects’, including variables from questionnaires, objective health measurements and results from the laboratory analysis of biological samples. The process presented in the Maelstrom Research guidelines for data harmonization was followed with minor adjustments. Results: The harmonization of data from objective measurements and biomarkers was reasonably straightforward, but questionnaire items proved more challenging. Some questions and response options had changed during the covered time period. This concerned, for example, questionnaire items on the availability and use of medication and diet. Conclusions: The long time period – 45 years – made harmonization more complicated. The survey questions or response options had changed for some topics due to changes in society. However, common core variables for topics that were especially relevant for the project, such as lifestyle factors and certain diseases or conditions, could be harmonized with sufficient comparability. For future surveys, the use of standardized survey methods and the proper documentation of data collection are recommended to facilitate harmonization.

Dissecting the contribution of single nucleotide polymorphisms in CCR9 and CCL25 genomic regions to the celiac disease phenotype

PURPOSE AND OBJECTIVES

Given their role in homing immune cells to the intestine, CC motif chemokine receptor 9 (CCR9) and its specific ligand CC motif chemokine ligand 25 (CCL25) are interesting candidate genes for celiac disease. These genes are located in regions previously shown to be associated with or linked to celiac disease, but no investigations on their association with various celiac disease phenotypes have so far been conducted. Here we studied such associations of both genotyped and imputed single nucleotide polymorphisms (SNPs) with either regulatory function or exonic location of the CCR9 and CCL25 loci.

RESULTS

Exploiting a carefully phenotyped cohort of 625 celiac disease patients and 1817 non-celiac controls, we identified that multiple SNPs with predicted regulatory function (RegulomeDB score ≤3a and/or eQTL effect) located between 100 kB upstream and downstream of CCR9 and CCL25 are associated with celiac disease and/or selected phenotypes. Of the genotyped SNPs in the CCR9 loci, rs213360 with an eQTL effect on CCR9 expression in blood was associated with celiac disease and all investigated phenotypes except high HLA risk. Rs1545985 with an eQTL on CCR9 expression and rs7652331 and rs12493471, both with RegulomeDB score ≤3a, were all associated with gastrointestinal symptoms and malabsorption and the latter additionally with anemia. The genotyped CCL25 SNPs rs952444 and rs882951, with RegulomeDB scores 1d and 1f respectively and eQTL effect on CCL25 expression in small intestine, were associated with gastrointestinal symptoms and malabsorption. The CCL25 SNP rs2303165 identified in sequencing followed by imputation was associated with partial villous atrophy. However, the association did not pass the permutation based multiple testing correction (PEMP2 > 0.05).

CONCLUSIONS

We conclude that SNPs in the region of CCR9 and CCL25 with predicted functional effect or exonic localization likely contribute only modestly to various celiac disease phenotypes.

Polygenic risk provides biological validity for the ICHD-3 criteria among Finnish migraine families

Background

Migraine is diagnosed using the extensively field-tested International Classification of Headache Disorders (ICHD-3) consensus criteria derived by the International Headache Society. To evaluate the criteria in respect to a measurable biomarker, we studied the relationship between the main ICHD-3 criteria and the polygenic risk score, a measure of common variant burden in migraine.

Methods

We used linear mixed models to study the correlation of ICHD-3 diagnostic criteria, underlying symptoms, and main diagnoses with the polygenic risk score of migraine in a cohort of 8602 individuals from the Finnish Migraine Genome Project.

Results

Main diagnostic categories and all underlying diagnostic criteria formed a consistent continuum along the increasing polygenic burden. Polygenic risk was associated with the heterogeneous clinical picture starting from the non-migraine headache (mean 0.07; 95% CI 0.02–0.12; p = 0.008 compared to the non-headache group), to probable migraine (mean 0.13; 95% CI 0.08–0.18; p < 0.001), migraine headache (mean 0.17; 95% CI 0.14–0.21; p < 0.001) and migraine with typical visual aura (mean 0.29; 95% CI 0.26–0.33; p < 0.001), all the way to the hemiplegic aura (mean 0.37; 95% CI 0.31–0.43; p < 0.001). All individual ICHD-3 symptoms and the total number of reported symptoms, a surrogate of migraine complexity, demonstrated a clear inclination with an increasing polygenic risk.

Conclusions

The complex migraine phenotype progressively follows the polygenic burden from individuals with no headache to non-migrainous headache and up to patients with attacks manifesting all the features of the ICHD-3 headache and aura. Results provide further biological support for the ICHD-3 diagnostic criteria.

Type 2 Diabetes-Related Health Economic Impact Associated with Increased Whole Grains Consumption among Adults in Finland

The prevalence of type 2 diabetes (T2D) is increasing rapidly worldwide. A healthy diet supporting the control of energy intake and body weight has major importance in the prevention of T2D. For example, a high intake of whole grain foods (WGF) has been shown to be inversely associated with risk for T2D. The objective of the study was to estimate the expected health economic impacts of increased WGF consumption to decrease the incidence of T2D in the Finnish adult population. A health economic model utilizing data from multiple national databases and published scientific literature was constructed to estimate these population-level health economic consequences. Among the adult Finnish population, increased WGF consumption could reduce T2D-related costs between 286€ and 989€ million during the next 10-year time horizon depending on the applied scenario (i.e., a 10%-unit increase in a proportion of daily WGF users, an increased number (i.e., two or more) of WGF servings a day, or alternatively a combination of these scenarios). Over the next 20–30 years, a population-wide increase in WGF consumption could lead to much higher benefits. Furthermore, depending on the applied scenario, between 1323 and 154,094 quality-adjusted life years (QALYs) could be gained at the population level due to decreased T2D-related morbidity and mortality during the next 10 to 30 years. The results indicate that even when the current level of daily WGF consumption is already at a relatively high-level in a global context, increased WGF consumption could lead to important health gains and savings in the Finnish adult population.

Taking it to the bank: the ethical management of individual findings arising in secondary research

A rapidly growing proportion of health research uses 'secondary data': data used for purposes other than those for which it was originally collected. Do researchers using secondary data have an obligation to disclose individual research findings to participants? While the importance of this question has been duly recognised in the context of primary research (ie, where data are collected from participants directly), it remains largely unexamined in the context of research using secondary data. In this paper, we critically examine the arguments for a moral obligation to disclose individual research findings in the context of primary research, to determine if they can be applied to secondary research. We conclude that they cannot. We then propose that the nature of the relationship between researchers and participants is what gives rise to particular moral obligations, including the obligation to disclose individual results. We argue that the relationship between researchers and participants in secondary research does not generate an obligation to disclose. However, we also argue that the biobanks or data archives which collect and provide access to secondary data may have such an obligation, depending on the nature of the relationship they establish with participants.

Predictive Accuracy of a Clinical and Genetic Risk Model for Atrial Fibrillation

BACKGROUND

Atrial fibrillation (AF) risk estimation using clinical factors with or without genetic information may identify AF screening candidates more accurately than the guideline-based age threshold of ≥65 years.

METHODS

We analyzed 4 samples across the United States and Europe (derivation: UK Biobank; validation: FINRISK, Geisinger MyCode Initiative, and Framingham Heart Study). We estimated AF risk using the CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology AF) score and a combination of CHARGE-AF and a 1168-variant polygenic score (Predict-AF). We compared the utility of age, CHARGE-AF, and Predict-AF for predicting 5-year AF by quantifying discrimination and calibration.

RESULTS

Among 543 093 individuals, 8940 developed AF within 5 years. In the validation sets, CHARGE-AF (C index range, 0.720-0.824) and Predict-AF (0.749-0.831) had largely comparable discrimination, both favorable to continuous age (0.675-0.801). Calibration was similar using CHARGE-AF (slope range, 0.67-0.87) and Predict-AF (0.65-0.83). Net reclassification improvement using Predict-AF versus CHARGE-AF was modest (net reclassification improvement range, 0.024-0.057) but more favorable among individuals aged <65 years (0.062-0.11). Using Predict-AF among 99 530 individuals aged ≥65 years across each sample, 70 849 had AF risk <5%, of whom 69 067 (97.5%) did not develop AF, whereas 28 681 had AF risk ≥5%, of whom 2264 (7.9%) developed AF. Of 11 379 individuals aged <65 years with AF risk ≥5%, 435 (3.8%) developed AF before age 65 years, with roughly half (46.9%) meeting anticoagulation criteria.

CONCLUSIONS

AF risk estimation using clinical factors may prioritize individuals for AF screening more precisely than the age threshold endorsed in current guidelines. The additional value of genetic predisposition is modest but greatest among younger individuals.

High-Density Lipoprotein 3 Cholesterol and Primary Open-Angle Glaucoma: Metabolomics and Mendelian Randomization Analyses

PURPOSE

We hypothesized that the effect of blood lipid-related metabolites on primary open-angle glaucoma (POAG) would differ according to specific lipoprotein particles and lipid sub-fractions. We investigated the associations of blood levels of lipoprotein particles and lipid sub-fractions with POAG.

DESIGN

Cross-sectional study.

PARTICIPANTS

Individuals recruited for the baseline visit of the population-based Singapore Epidemiology of Eye Disease study (n = 8503).

METHODS

All participants underwent detailed standardized ocular and systemic examinations. A total of 130 blood lipid-related metabolites were quantified using a nuclear magnetic resonance metabolomics platform. The analyses were conducted in 2 stages. First, we investigated whether and which lipid-related metabolites were directly associated with POAG using regression analyses followed by Bayesian network modeling. Second, we investigated if any causal relationship exists between the identified lipid-related metabolites, if any, and POAG using 2-sample Mendelian randomization (MR) analysis. We performed genome-wide association studies (GWAS) on high-density lipoprotein (HDL) 3 cholesterol (after inverse normal transformation) and used the top variants associated with HLD3 cholesterol as instrumental variables (IVs) in the MR analysis.

MAIN OUTCOME MEASURE

Primary open-angle glaucoma.

RESULTS

Of the participants, 175 (2.1%) had POAG. First, a logistic regression model showed that total HDL3 cholesterol (negatively) and phospholipids in very large HDL (positively) were associated with POAG. Further analyses using a Bayesian network analysis showed that only total HDL3 cholesterol was directly associated with POAG (odds ratio [OR], 0.72 per 1 standard deviation increase in HDL3 cholesterol; 95% confidence interval [CI], 0.61-0.84), independently of age, gender, intraocular pressure (IOP), body mass index (BMI), education level, systolic blood pressure, axial length, and statin medication. Using 5 IVs identified from the GWAS and with the inverse variance weighted MR method, we found that higher levels of HDL3 cholesterol were associated with a decreased odds of POAG (OR, 0.91; 95% CI, 0.84-0.99, P = 0.021). Other MR methods, including weighted median, mode-based estimator, and contamination mixture methods, derived consistent OR estimates. None of the routine lipids (blood total, HDL, or low-density lipoprotein [LDL] cholesterol) were associated with POAG.

CONCLUSIONS

Overall, these results suggest that the relationship between HDL3 cholesterol and POAG might be causal and specific, and that dysregulation of cholesterol transport may play a role in the pathogenesis of POAG.

Plasma N-glycome shows continuous deterioration as the diagnosis of insulin resistance approaches

INTRODUCTION

Prediction of type 2 diabetes mellitus (T2DM) and its preceding factors, such as insulin resistance (IR), is of great importance as it may allow delay or prevention of onset of the disease. Plasma protein N-glycome has emerged as a promising predictive biomarker. In a prospective longitudinal study, we included patients with a first diagnosis of impaired glucose metabolism (IR or T2DM) to investigate the N-glycosylation's predictive value years before diabetes development.

RESEARCH DESIGN AND METHODS

Plasma protein N-glycome was profiled by hydrophilic interaction ultra-performance liquid chromatography in 534 TwinsUK participants free from disease at baseline. This included 89 participants with incident diagnosis of IR or T2DM during the follow-up period (7.14±3.04 years) whose last sample prior to diagnosis was compared using general linear regression with 445 age-matched unrelated controls. Findings were replicated in an independent cohort. Changes in N-glycome have also been presented in connection with time to diagnosis.

RESULTS

Eight groups of plasma N-glycans were different between incident IR or T2DM cases and controls (p<0.05) after adjusting for multiple testing using Benjamini-Hochberg correction. These differences were noticeable up to 10 years prior to diagnosis and are changing continuously as becoming more expressed toward the diagnosis. The prediction model was built using significant glycan traits, displaying a discriminative performance with an area under the receiver operating characteristic curve of 0.77.

CONCLUSIONS

In addition to previous studies, we showed the diagnostic potential of plasma N-glycome in the prediction of both IR and T2DM development years before the clinical manifestation and indicated the continuous deterioration of N-glycome toward the diagnosis.