Identifying atopic dermatitis risk loci in 1,094,060 individuals with sub analysis of disease severity and onset.

Atopic dermatitis (AD) is a common inflammatory skin disease highly attributable to genetic factors. Here, we report results from a genome-wide meta-analysis of AD in 37,541 cases and 1,056,519 controls with data from the FinnGen project, the Estonian Biobank, the UK Biobank, the EAGLE Consortium, and the BioBank Japan. We detected 77 independent AD-associated loci of which 10 were to our knowledge previously unreported. The associated loci showed enrichment in various immune regulatory processes. We further performed subgroup analyses of mild and severe AD, and of early and late-onset AD, with data from the FinnGen project. 55 of the 79 tested variants in the associated loci showed larger effect estimates for severe than mild AD as determined through administered treatment. The age of onset, as determined by the first hospital visit with AD diagnosis, was lower in patients with particular AD-risk alleles. Our findings add to the knowledge of the genetic background of AD and may underlay the development of new therapeutic strategies.

Clinical and biochemical associations of urinary metabolites: quantitative epidemiological approach on renal-cardiometabolic biomarkers.

BACKGROUND: Urinary metabolomics has demonstrated considerable potential to assess kidney function and its metabolic corollaries in health and disease. However, applications in epidemiology remain sparse due to technical challenges. METHODS: We added 17 metabolites to an open-access urinary nuclear magnetic resonance metabolomics platform, extending the panel to 61 metabolites (n = 994). We also introduced automated quantification for 11 metabolites, extending the panel to 12 metabolites (+creatinine). Epidemiological associations between these 12 metabolites and 49 clinical measures were studied in three independent cohorts (up to 5989 participants). Detailed regression analyses with various confounding factors are presented for body mass index (BMI) and smoking. RESULTS: Sex-specific population reference concentrations and distributions are provided for 61 urinary metabolites (419 men and 575 women), together with methodological intra-assay metabolite variations as well as the biological intra-individual and epidemiological population variations. For the 12 metabolites, 362 associations were found. These are mostly novel and reflect potential molecular proxies to estimate kidney function, as the associations cannot be simply explained by estimated glomerular filtration rate. Unspecific renal excretion results in leakage of amino acids (and glucose) to urine in all individuals. Seven urinary metabolites associated with smoking, providing questionnaire-independent proxy measures of smoking status in epidemiological studies. Common confounders did not affect metabolite associations with smoking, but insulin had a clear effect on most associations with BMI, including strong effects on 2-hydroxyisobutyrate, valine, alanine, trigonelline and hippurate. CONCLUSIONS: Urinary metabolomics provides new insight on kidney function and related biomarkers on the renal-cardiometabolic system, supporting large-scale applications in epidemiology.

Low and high serum IgG associates with respiratory infections in a young and working age population.

BACKGROUND: We investigated health consequences and genetic properties associated with serum IgG concentration in a young and working age general population. METHODS: Northern Finland Birth Cohort 1966 (NFBC1966, n = 12,231) health data have been collected from birth to 52 years of age. Relationships between life-long health events, medications, chronic conditions, lifestyle, and serum IgG concentration measured at age 46 years (n = 5430) were analysed. Regulatory mechanisms of serum IgG concentration were considered. FINDINGS: Smoking and genetic variation (FCGR2B and TNFRSF13B) were the most important determinants of serum IgG concentration. Laboratory findings suggestive of common variable immunodeficiency (CVID) were 10-fold higher compared to previous reports (73.7 per 100,000 vs 0.6-6.9 per 100,000). Low IgG was associated with antibiotic use (relative risk 1.285, 95% CI 1.001-1.648; p = 0.049) and sinus surgery (relative risk 2.257, 95% CI 1.163-4.379; p = 0.016). High serum IgG was associated with at least one pneumonia episode (relative risk 1.737, 95% CI 1.032-2.922; p = 0.038) and with total number of pneumonia episodes (relative risk 2.167, 95% CI 1.443-3.254; p < 0.001). INTERPRETATION: CVID-like laboratory findings are surprisingly common in our unselected study population. Any deviation of serum IgG from normal values can be harmful; both low and high serum IgG may indicate immunological insufficiency. Critical evaluation of clinical presentation must accompany immunological laboratory parameters. FUNDING: Oulu University Hospital VTR, CSL Behring, Foundation for Pediatric Research.

Genetic Risk Factors Associated With Preeclampsia and Hypertensive Disorders of Pregnancy.

Importance: A genetic contribution to preeclampsia susceptibility has been established but is still incompletely understood. Objective: To disentangle the underlying genetic architecture of preeclampsia and preeclampsia or other maternal hypertension during pregnancy with a genome-wide association study (GWAS) of hypertensive disorders of pregnancy. Design, Setting, and Participants: This GWAS included meta-analyses in maternal preeclampsia and a combination phenotype encompassing maternal preeclampsia and preeclampsia or other maternal hypertensive disorders. Two overlapping phenotype groups were selected for examination, namely, preeclampsia and preeclampsia or other maternal hypertension during pregnancy. Data from the Finnish Genetics of Pre-eclampsia Consortium (FINNPEC, 1990-2011), Finnish FinnGen project (1964-2019), Estonian Biobank (1997-2019), and the previously published InterPregGen consortium GWAS were combined. Individuals with preeclampsia or other maternal hypertension during pregnancy and control individuals were selected from the cohorts based on relevant International Classification of Diseases codes. Data were analyzed from July 2020 to February 2023. Exposures: The association of a genome-wide set of genetic variants and clinical risk factors was analyzed for the 2 phenotypes. Results: A total of 16 743 women with prior preeclampsia and 15 200 with preeclampsia or other maternal hypertension during pregnancy were obtained from FINNPEC, FinnGen, Estonian Biobank, and the InterPregGen consortium study (respective mean [SD] ages at diagnosis: 30.3 [5.5], 28.7 [5.6], 29.7 [7.0], and 28 [not available] years). The analysis found 19 genome-wide significant associations, 13 of which were novel. Seven of the novel loci harbor genes previously associated with blood pressure traits (NPPA, NPR3, PLCE1, TNS2, FURIN, RGL3, and PREX1). In line with this, the 2 study phenotypes showed genetic correlation with blood pressure traits. In addition, novel risk loci were identified in the proximity of genes involved in the development of placenta (PGR, TRPC6, ACTN4, and PZP), remodeling of uterine spiral arteries (NPPA, NPPB, NPR3, and ACTN4), kidney function (PLCE1, TNS2, ACTN4, and TRPC6), and maintenance of proteostasis in pregnancy serum (PZP). Conclusions and Relevance: The findings indicate that genes related to blood pressure traits are associated with preeclampsia, but many of these genes have additional pleiotropic effects on cardiometabolic, endothelial, and placental function. Furthermore, several of the associated loci have no known connection with cardiovascular disease but instead harbor genes contributing to maintenance of successful pregnancy, with dysfunctions leading to preeclampsialike symptoms.

Evidence of a causal effect of genetic tendency to gain muscle mass on uterine leiomyomata.

Uterine leiomyomata (UL) are the most common tumours of the female genital tract and the primary cause of surgical removal of the uterus. Genetic factors contribute to UL susceptibility. To add understanding to the heritable genetic risk factors, we conduct a genome-wide association study (GWAS) of UL in up to 426,558 European women from FinnGen and a previous UL meta-GWAS. In addition to the 50 known UL loci, we identify 22 loci that have not been associated with UL in prior studies. UL-associated loci harbour genes enriched for development, growth, and cellular senescence. Of particular interest are the smooth muscle cell differentiation and proliferation-regulating genes functioning on the myocardin-cyclin dependent kinase inhibitor 1 A pathway. Our results further suggest that genetic predisposition to increased fat-free mass may be causally related to higher UL risk, underscoring the involvement of altered muscle tissue biology in UL pathophysiology. Overall, our findings add to the understanding of the genetic pathways underlying UL, which may aid in developing novel therapeutics.

Longitudinal metabolomics of increasing body-mass index and waist-hip ratio reveals two dynamic patterns of obesity pandemic.

BACKGROUND/OBJECTIVE: This observational study dissects the complex temporal associations between body-mass index (BMI), waist-hip ratio (WHR) and circulating metabolomics using a combination of longitudinal and cross-sectional population-based datasets and new systems epidemiology tools. SUBJECTS/METHODS: Firstly, a data-driven subgrouping algorithm was employed to simplify high-dimensional metabolic profiling data into a single categorical variable: a self-organizing map (SOM) was created from 174 metabolic measures from cross-sectional surveys (FINRISK, n = 9708, ages 25-74) and a birth cohort (NFBC1966, n = 3117, age 31 at baseline, age 46 at follow-up) and an expert committee defined four subgroups of individuals based on visual inspection of the SOM. Secondly, the subgroups were compared regarding BMI and WHR trajectories in an independent longitudinal dataset: participants of the Young Finns Study (YFS, n = 1286, ages 24-39 at baseline, 10 years follow-up, three visits) were categorized into the four subgroups and subgroup-specific age-dependent trajectories of BMI, WHR and metabolic measures were modelled by linear regression. RESULTS: The four subgroups were characterised at age 39 by high BMI, WHR and dyslipidemia (designated TG-rich); low BMI, WHR and favourable lipids (TG-poor); low lipids in general (Low lipid) and high low-density-lipoprotein cholesterol (High LDL-C). Trajectory modelling of the YFS dataset revealed a dynamic BMI divergence pattern: despite overlapping starting points at age 24, the subgroups diverged in BMI, fasting insulin (three-fold difference at age 49 between TG-rich and TG-poor) and insulin-associated measures such as triglyceride-cholesterol ratio. Trajectories also revealed a WHR progression pattern: despite different starting points at the age of 24 in WHR, LDL-C and cholesterol-associated measures, all subgroups exhibited similar rates of change in these measures, i.e. WHR progression was uniform regardless of the cross-sectional metabolic profile. CONCLUSIONS: Age-associated weight variation in adults between 24 and 49 manifests as temporal divergence in BMI and uniform progression of WHR across metabolic health strata.

Cross-sectionally Calculated Metabolic Aging Does Not Relate to Longitudinal Metabolic Changes-Support for Stratified Aging Models.

CONTEXT: Aging varies between individuals, with profound consequences for chronic diseases and longevity. One hypothesis to explain the diversity is a genetically regulated molecular clock that runs differently between individuals. Large human studies with long enough follow-up to test the hypothesis are rare due to practical challenges, but statistical models of aging are built as proxies for the molecular clock by comparing young and old individuals cross-sectionally. These models remain untested against longitudinal data. OBJECTIVE: We applied novel methodology to test if cross-sectional modeling can distinguish slow vs accelerated aging in a human population. METHODS: We trained a machine learning model to predict age from 153 clinical and cardiometabolic traits. The model was tested against longitudinal data from another cohort. The training data came from cross-sectional surveys of the Finnish population (n = 9708; ages 25-74 years). The validation data included 3 time points across 10 years in the Young Finns Study (YFS; n = 1009; ages 24-49 years). Predicted metabolic age in 2007 was compared against observed aging rate from the 2001 visit to the 2011 visit in the YFS dataset and correlation between predicted vs observed metabolic aging was determined. RESULTS: The cross-sectional proxy failed to predict longitudinal observations (R2 = 0.018%, P = 0.67). CONCLUSION: The finding is unexpected under the clock hypothesis that would produce a positive correlation between predicted and observed aging. Our results are better explained by a stratified model where aging rates per se are similar in adulthood but differences in starting points explain diverging metabolic fates.

The Finnish genetic heritage in 2022 - from diagnosis to translational research.

Isolated populations have been valuable for the discovery of rare monogenic diseases and their causative genetic variants. Finnish disease heritage (FDH) is an example of a group of hereditary monogenic disorders caused by single major, usually autosomal-recessive, variants enriched in the population due to several past genetic drift events. Interestingly, distinct subpopulations have remained in Finland and have maintained their unique genetic repertoire. Thus, FDH diseases have persisted, facilitating vigorous research on the underlying molecular mechanisms and development of treatment options. This Review summarizes the current status of FDH, including the most recently discovered FDH disorders, and introduces a set of other recently identified diseases that share common features with the traditional FDH diseases. The Review also discusses a new era for population-based studies, which combine various forms of big data to identify novel genotype-phenotype associations behind more complex conditions, as exemplified here by the FinnGen project. In addition to the pathogenic variants with an unequivocal causative role in the disease phenotype, several risk alleles that correlate with certain phenotypic features have been identified among the Finns, further emphasizing the broad value of studying genetically isolated populations.

Genome-wide association meta-analysis identifies 48 risk variants and highlights the role of the stria vascularis in hearing loss.

Hearing loss is one of the top contributors to years lived with disability and is a risk factor for dementia. Molecular evidence on the cellular origins of hearing loss in humans is growing. Here, we performed a genome-wide association meta-analysis of clinically diagnosed and self-reported hearing impairment on 723,266 individuals and identified 48 significant loci, 10 of which are novel. A large proportion of associations comprised missense variants, half of which lie within known familial hearing loss loci. We used single-cell RNA-sequencing data from mouse cochlea and brain and mapped common-variant genomic results to spindle, root, and basal cells from the stria vascularis, a structure in the cochlea necessary for normal hearing. Our findings indicate the importance of the stria vascularis in the mechanism of hearing impairment, providing future paths for developing targets for therapeutic intervention in hearing loss.

Association between mitochondrial DNA haplogroups J and K, serum branched-chain amino acids and lowered capability for endurance exercise.

BACKGROUND: Endurance exercise training promotes the catabolism of branched-chain amino acids (BCAAs) in skeletal muscles. We have previously shown that mitochondrial DNA (mtDNA) haplogroups J and K are markers of low responders in endurance training. In this paper, we hypothesize that BCAA catabolism is a surrogate marker of lower respiratory chain activity attributed to these haplogroups. We evaluated whether exercise-induced changes in amino acid concentrations differ between subjects harbouring mtDNA haplogroups J or K and those with non-JK haplogroups. METHODS: Finnish male conscripts (N = 633) undertook the 12-min Cooper running test at the beginning and end of their military service. The intervention during the service mainly included endurance aerobic exercise and sports-related muscle training. Concentrations of seven amino acids were analysed in the serum using a high-throughput 1H NMR metabolomics platform. Total DNA was extracted from whole blood, and restriction fragment analysis was used to determine mtDNA haplogroups J and K. RESULTS: The concentrations of the seven amino acids were higher following the intervention, with the exception of phenylalanine; interestingly, the increase in the concentrations of three BCAAs was larger in subjects with haplogroup J or K than in subjects with non-JK haplogroups (p = 0.029). MtDNA haplogroups J and K share two common nonsynonymous variants. Structural analysis based on crystallographic data on bovine complexes I and III revealed that the Leu18 variant in cytochrome b encoded by m.14798T > C may interfere with ubiquinone binding at the Qi site in complex III. CONCLUSIONS: The increase in the concentrations of serum BCAAs following exercise intervention differs between subjects harbouring mtDNA haplogroup J or K and those harbouring non-JK haplogroups. Lower response in endurance training and difference in exercise-induced increase in the concentrations of serum BCAAs suggest decreased respiratory chain activity. Haplogroups J and K share m.14798T > C in MT-CYB, which may hamper the function of complex III.

Longitudinal profiling of metabolic ageing trends in two population cohorts of young adults.

BACKGROUND: Quantification of metabolic changes over the human life course is essential to understanding ageing processes. Yet longitudinal metabolomics data are rare and long gaps between visits can introduce biases that mask true trends. We introduce new ways to process quantitative time-series population data and elucidate metabolic ageing trends in two large cohorts. METHODS: Eligible participants included 1672 individuals from the Cardiovascular Risk in Young Finns Study and 3117 from the Northern Finland Birth Cohort 1966. Up to three time points (ages 24-49 years) were analysed by nuclear magnetic resonance metabolomics and clinical biochemistry (236 measures). Temporal trends were quantified as median change per decade. Sample quality was verified by consistency of shared biomarkers between metabolomics and clinical assays. Batch effects between visits were mitigated by a new algorithm introduced in this report. The results below satisfy multiple testing threshold of P < 0.0006. RESULTS: Women gained more weight than men (+6.5% vs +5.0%) but showed milder metabolic changes overall. Temporal sex differences were observed for C-reactive protein (women +5.1%, men +21.1%), glycine (women +5.2%, men +1.9%) and phenylalanine (women +0.6%, men +3.5%). In 566 individuals with ≥+3% weight gain vs 561 with weight change ≤-3%, divergent patterns were observed for insulin (+24% vs -10%), very-low-density-lipoprotein triglycerides (+32% vs -6%), high-density-lipoprotein2 cholesterol (-6.5% vs +4.7%), isoleucine (+5.7% vs -6.0%) and C-reactive protein (+25% vs -22%). CONCLUSION: We report absolute and proportional trends for 236 metabolic measures as new reference material for overall age-associated and specific weight-driven changes in real-world populations.

Genetic and observational evidence: No independent role for cholesterol efflux over static high-density lipoprotein concentration measures in coronary heart disease risk assessment.

BACKGROUND: Observational findings for high-density lipoprotein (HDL)-mediated cholesterol efflux capacity (HDL-CEC) and coronary heart disease (CHD) appear inconsistent, and knowledge of the genetic architecture of HDL-CEC is limited. OBJECTIVES: A large-scale observational study on the associations of HDL-CEC and other HDL-related measures with CHD and the largest genome-wide association study (GWAS) of HDL-CEC. PARTICIPANTS/METHODS: Six independent cohorts were included with follow-up data for 14,438 participants to investigate the associations of HDL-related measures with incident CHD (1,570 events). The GWAS of HDL-CEC was carried out in 20,372 participants. RESULTS: HDL-CEC did not associate with CHD when adjusted for traditional risk factors and HDL cholesterol (HDL-C). In contradiction, almost all HDL-related concentration measures associated consistently with CHD after corresponding adjustments. There were no genetic loci associated with HDL-CEC independent of HDL-C and triglycerides. CONCLUSION: HDL-CEC is not unequivocally associated with CHD in contrast to HDL-C, apolipoprotein A-I, and most of the HDL subclass particle concentrations.

Uniting biobank resources reveals novel genetic pathways modulating susceptibility for atopic dermatitis.

BACKGROUND: Atopic dermatitis (AD) is a common chronic inflammatory skin disease with high heritability. Previous genome-wide association studies have identified several loci predisposing to AD. These findings explain approximately 30% of the variance in AD susceptibility, suggesting that further work is required to fully understand the genetic underpinnings. OBJECTIVE: We sought to gain additional understanding of the genetic contribution to AD risk by using biobank resources. METHODS: We completed a genome-wide meta-analysis of AD in 796,661 individuals (Ncases = 22,474) from the FinnGen study, the Estonian Biobank, and the UK Biobank. We further performed downstream in silico analyses to characterize the risk variants at the novel loci. RESULTS: We report 30 loci associating with AD (P < 5 × 10-8), 5 of which are novel. In 2 of the novel loci, we identified missense mutations with deleterious predictions in desmocollin 1 and serpin family B member 7, genes encoding proteins crucial to epidermal strength and integrity. CONCLUSIONS: These findings elucidate novel genetic pathways involved in AD pathophysiology. The likely involvement of desmocollin 1 and serpin family B member 7 in AD pathogenesis may offer opportunities for the development of novel treatment strategies for AD in the future.

Leveraging Northern European population history: novel low-frequency variants for polycystic ovary syndrome.

STUDY QUESTION: Can we identify novel variants associated with polycystic ovary syndrome (PCOS) by leveraging the unique population history of Northern Europe? SUMMARY ANSWER: We identified three novel genome-wide significant associations with PCOS, with two putative independent causal variants in the checkpoint kinase 2 (CHEK2) gene and a third in myosin X (MYO10). WHAT IS KNOWN ALREADY: PCOS is a common, complex disorder with unknown aetiology. While previous genome-wide association studies (GWAS) have mapped several loci associated with PCOS, the analysis of populations with unique population history and genetic makeup has the potential to uncover new low-frequency variants with larger effects. STUDY DESIGN, SIZE, DURATION: A population-based case-control GWAS was carried out. PARTICIPANTS/MATERIALS, SETTING, METHODS: We identified PCOS cases from national registers by ICD codes (ICD-10 E28.2, ICD-9 256.4, or ICD-8 256.90), and all remaining women were considered controls. We then conducted a three-stage case-control GWAS: in the discovery phase, we had a total of 797 cases and 140 558 controls from the FinnGen study. For validation, we used an independent dataset from the Estonian Biobank, including 2812 cases and 89 230 controls. Finally, we performed a joint meta-analysis of 3609 cases and 229 788 controls from both cohorts. Additionally, we reran the association analyses including BMI as a covariate, with 2169 cases and 160 321 controls from both cohorts. MAIN RESULTS AND THE ROLE OF CHANCE: Two out of the three novel genome-wide significant variants associating with PCOS, rs145598156 (P = 3.6×10-8, odds ratio (OR) = 3.01 [2.02-4.50] minor allele frequency (MAF) = 0.005) and rs182075939 (P = 1.9×10-16, OR = 1.69 [1.49-1.91], MAF = 0.04), were found to be enriched in the Finnish and Estonian populations and are tightly linked to a deletion c.1100delC (r2 = 0.95) and a missense I157T (r2 = 0.83) in CHEK2. The third novel association is a common variant near MYO10 (rs9312937, P = 1.7 × 10-8, OR = 1.16 [1.10-1.23], MAF = 0.44). We also replicated four previous reported associations near the genes Erb-B2 Receptor Tyrosine Kinase 4 (ERBB4), DENN Domain Containing 1A (DENND1A), FSH Subunit Beta (FSHB) and Zinc Finger And BTB Domain Containing 16 (ZBTB16). When adding BMI as a covariate only one of the novel variants remained genome-wide significant in the meta-analysis (the EstBB lead signal in CHEK2 rs182075939, P = 1.9×10-16, OR = 1.74 [1.5-2.01]) possibly owing to reduced sample size. LARGE SCALE DATA: The age- and BMI-adjusted GWAS meta-analysis summary statistics are available for download from the GWAS Catalog with accession numbers GCST90044902 and GCST90044903. LIMITATIONS, REASONS FOR CAUTION: The main limitation was the low prevalence of PCOS in registers; however, the ones with the diagnosis most likely represent the most severe cases. Also, BMI data were not available for all (63% for FinnGen, 76% for EstBB), and the biobank setting limited the accessibility of PCOS phenotypes and laboratory values. WIDER IMPLICATIONS OF THE FINDINGS: This study encourages the use of isolated populations to perform genetic association studies for the identification of rare variants contributing to the genetic landscape of complex diseases such as PCOS. STUDY FUNDING/COMPETING INTEREST(S): This work has received funding from the European Union's Horizon 2020 research and innovation programme under the MATER Marie Sklodowska-Curie grant agreement No. 813707 (N.P.-G., T.L., T.P.), the Estonian Research Council grant (PRG687, T.L.), the Academy of Finland grants 315921 (T.P.), 321763 (T.P.), 297338 (J.K.), 307247 (J.K.), 344695 (H.L.), Novo Nordisk Foundation grant NNF17OC0026062 (J.K.), the Sigrid Juselius Foundation project grants (T.L., J.K., T.P.), Finska Läkaresällskapet (H.L.) and Jane and Aatos Erkko Foundation (H.L.). The funders had no role in study design, data collection and analysis, publishing or preparation of the manuscript. The authors declare no conflicts of interest.

Genome-wide association study of periodontal pocketing in Finnish adults.

BACKGROUND: A genome-wide association study is an analytical approach that investigates whether genetic variants across the whole genome contribute to disease progression. The aim of this study was to investigate genome-wide associations of periodontal condition measured as deepened periodontal pockets (≥ 4 mm) in Finnish adults. METHODS: This study was based on the data of the national Health 2000 Survey (BRIF8901) in Finland and the Northern Finland Birth Cohort 1966 Study totalling 3,245 individuals. The genotype data were analyzed using the SNPTEST v.2.4.1. The number of teeth with deepened periodontal pockets (≥ 4 mm deep) was employed as a continuous response variable in additive regression analyses performed separately for the two studies and the results were combined in a meta-analysis applying a fixed effects model. RESULTS: Genome-wide significant associations with the number of teeth with ≥ 4 mm deep pockets were not found at the p-level of < 5 × 10-8, while in total 17 loci reached the p-level of 5 × 10-6. Of the top hits, SNP rs4444613 in chromosome 20 showed the strongest association (p = 1.35 × 10-7). CONCLUSION: No statistically significant genome-wide associations with deepened periodontal pockets were found in this study.

Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression.

Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.

Systematic evaluation of the association between hemoglobin levels and metabolic profile implicates beneficial effects of hypoxia.

Activation of the hypoxia-inducible factor (HIF) pathway reprograms energy metabolism. Hemoglobin (Hb) is the main carrier of oxygen. Using its normal variation as a surrogate measure for hypoxia, we explored whether lower Hb levels could lead to healthier metabolic profiles in mice and humans (n = 7175) and used Mendelian randomization (MR) to evaluate potential causality (n = 173,480). The results showed evidence for lower Hb levels being associated with lower body mass index, better glucose tolerance and other metabolic profiles, lower inflammatory load, and blood pressure. Expression of the key HIF target genes SLC2A4 and Slc2a1 in skeletal muscle and adipose tissue, respectively, associated with systolic blood pressure in MR analyses and body weight, liver weight, and adiposity in mice. Last, manipulation of murine Hb levels mediated changes to key metabolic parameters. In conclusion, low-end normal Hb levels may be favorable for metabolic health involving mild chronic activation of the HIF response.

The Role of Inflammatory Cytokines as Intermediates in the Pathway from Increased Adiposity to Disease.

OBJECTIVE: This study aimed to investigate the role of cytokines as intermediates in the pathway from increased adiposity to disease. METHODS: BMI and circulating levels of up to 41 cytokines were measured in individuals from three Finnish cohort studies (n = 8,293). Mendelian randomization (MR) was used to assess the impact of BMI on circulating cytokines and the impact of BMI-driven cytokines on risk of obesity-related diseases. RESULTS: Observationally, BMI was associated with 19 cytokines. For every SD increase in BMI, causal effect estimates were strongest for hepatocyte growth factor, monocyte chemotactic protein-1 (MCP-1), and tumor necrosis factor-related apoptosis-inducing ligand (TRAIL) and were as ratios of geometric means 1.13 (95% CI: 1.08-1.19), 1.08 (95% CI: 1.04-1.14), and 1.13 (95% CI: 1.04-1.21), respectively. TRAIL was associated with a small increase in the odds of coronary artery disease (odds ratio: 1.03; 95% CI: 1.00-1.06). There was inconsistent evidence for a protective role of MCP-1 against inflammatory bowel diseases. CONCLUSIONS: Observational and MR estimates of the effect of BMI on cytokine levels were generally concordant. There was little evidence for an effect of raised levels of BMI-driven cytokines on disease. These findings illustrate the challenges of MR when applied in the context of molecular mediation.