The power of genetic diversity in genome-wide association studies of lipids.

Increased blood lipid levels are heritable risk factors of cardiovascular disease with varied prevalence worldwide owing to different dietary patterns and medication use1. Despite advances in prevention and treatment, in particular through reducing low-density lipoprotein cholesterol levels2, heart disease remains the leading cause of death worldwide3. Genome-wideassociation studies (GWAS) of blood lipid levels have led to important biological and clinical insights, as well as new drug targets, for cardiovascular disease. However, most previous GWAS4-23 have been conducted in European ancestry populations and may have missed genetic variants that contribute to lipid-level variation in other ancestry groups. These include differences in allele frequencies, effect sizes and linkage-disequilibrium patterns24. Here we conduct a multi-ancestry, genome-wide genetic discovery meta-analysis of lipid levels in approximately 1.65 million individuals, including 350,000 of non-European ancestries. We quantify the gain in studying non-European ancestries and provide evidence to support the expansion of recruitment of additional ancestries, even with relatively small sample sizes. We find that increasing diversity rather than studying additional individuals of European ancestry results in substantial improvements in fine-mapping functional variants and portability of polygenic prediction (evaluated in approximately 295,000 individuals from 7 ancestry groupings). Modest gains in the number of discovered loci and ancestry-specific variants were also achieved. As GWAS expand emphasis beyond the identification of genes and fundamental biology towards the use of genetic variants for preventive and precision medicine25, we anticipate that increased diversity of participants will lead to more accurate and equitable26 application of polygenic scores in clinical practice.

A multi-layer functional genomic analysis to understand noncoding genetic variation in lipids.

A major challenge of genome-wide association studies (GWASs) is to translate phenotypic associations into biological insights. Here, we integrate a large GWAS on blood lipids involving 1.6 million individuals from five ancestries with a wide array of functional genomic datasets to discover regulatory mechanisms underlying lipid associations. We first prioritize lipid-associated genes with expression quantitative trait locus (eQTL) colocalizations and then add chromatin interaction data to narrow the search for functional genes. Polygenic enrichment analysis across 697 annotations from a host of tissues and cell types confirms the central role of the liver in lipid levels and highlights the selective enrichment of adipose-specific chromatin marks in high-density lipoprotein cholesterol and triglycerides. Overlapping transcription factor (TF) binding sites with lipid-associated loci identifies TFs relevant in lipid biology. In addition, we present an integrative framework to prioritize causal variants at GWAS loci, producing a comprehensive list of candidate causal genes and variants with multiple layers of functional evidence. We highlight two of the prioritized genes, CREBRF and RRBP1, which show convergent evidence across functional datasets supporting their roles in lipid biology.

A genome-wide association study of susceptibility to upper urinary tract infections.

BACKGROUND: Our goal was to identify genetic and modifiable risk factors for upper urinary tract infections (UTIs). METHODS: We used data from UK Biobank, The Trøndelag Health Study (HUNT), and Michigan Genomics Initiative (MGI) to conduct genome-wide association studies (GWASs) and sex-stratified analyses on upper UTI. Mendelian randomization (MR) analyses were conducted to examine potential causal relationships between cardiometabolic risk factors and upper UTIs. RESULTS: One genome-wide significant (P ≤ 5E-08) locus was associated with the susceptibility to upper UTI, located near TSN in the female-only analysis. Additionally, we identified suggestive (P ≤ 5E-06) loci near DNAI3 for the females, SCAMP1-AS1 for the males, and near TSN, LINC00603, and HLA-DQA2 for both sexes. In MR analyses, higher genetically predicted lifetime smoking scores were associated with an increased risk of developing upper UTI for females and both sexes (OR of 4.84, P = 4.50E-06 and OR of 2.79, P = 3.02E-05, respectively). CONCLUSIONS: We found that genetic variants near TSN was associated with the risk of upper UTIs among females. In addition, we found several genetic loci with suggestive associations with the risk of upper UTIs. Finally, MR analyses found smoking to be a potential causal risk factor for upper UTIs.

A fast linkage method for population GWAS cohorts with related individuals.

Linkage analysis, a class of methods for detecting co-segregation of genomic segments and traits in families, was used to map disease-causing genes for decades before genotyping arrays and dense SNP genotyping enabled genome-wide association studies in population samples. Population samples often contain related individuals, but the segregation of alleles within families is rarely used because traditional linkage methods are computationally inefficient for larger datasets. Here, we describe Population Linkage, a novel application of Haseman-Elston regression as a method of moments estimator of variance components and their standard errors. We achieve additional computational efficiency by using modern methods for detection of IBD segments and variance component estimation, efficient preprocessing of input data, and minimizing redundant numerical calculations. We also refined variance component models to account for the biases in population-scale methods for IBD segment detection. We ran Population Linkage on four blood lipid traits in over 70,000 individuals from the HUNT and SardiNIA studies, successfully detecting 25 known genetic signals. One notable linkage signal that appeared in both was for low-density lipoprotein (LDL) cholesterol levels in the region near the gene APOE (LOD = 29.3, variance explained = 4.1%). This is the region where the missense variants rs7412 and rs429358, which together make up the ε2, ε3, and ε4 alleles each account for 2.4% and 0.8% of variation in circulating LDL cholesterol. Our results show the potential for linkage analysis and other large-scale applications of method of moments variance components estimation.

Regulatory variants in TCF7L2 are associated with thoracic aortic aneurysm.

Thoracic aortic aneurysm (TAA) is characterized by dilation of the aortic root or ascending/descending aorta. TAA is a heritable disease that can be potentially life threatening. While 10%-20% of TAA cases are caused by rare, pathogenic variants in single genes, the origin of the majority of TAA cases remains unknown. A previous study implicated common variants in FBN1 with TAA disease risk. Here, we report a genome-wide scan of 1,351 TAA-affected individuals and 18,295 control individuals from the Cardiovascular Health Improvement Project and Michigan Genomics Initiative at the University of Michigan. We identified a genome-wide significant association with TAA for variants within the third intron of TCF7L2 following replication with meta-analysis of four additional independent cohorts. Common variants in this locus are the strongest known genetic risk factor for type 2 diabetes. Although evidence indicates the presence of different causal variants for TAA and type 2 diabetes at this locus, we observed an opposite direction of effect. The genetic association for TAA colocalizes with an aortic eQTL of TCF7L2, suggesting a functional relationship. These analyses predict an association of higher expression of TCF7L2 with TAA disease risk. In vitro, we show that upregulation of TCF7L2 is associated with BCL2 repression promoting vascular smooth muscle cell apoptosis, a key driver of TAA disease.

Parental genetically predicted liability for coronary heart disease and risk of adverse pregnancy outcomes: a cohort study.

BACKGROUND: Adverse pregnancy outcomes (APO) may unmask or exacerbate a woman's underlying risk for coronary heart disease (CHD). We estimated associations of maternal and paternal genetically predicted liability for CHD with lifelong risk of APOs. We hypothesized that associations would be found for women, but not their male partners (negative controls). METHODS: We studied up to 83,969‬ women (and up to 55,568‬ male partners) from the Norwegian Mother, Father and Child Cohort Study or the Trøndelag Health Study with genotyping data and lifetime history of any APO in their pregnancies (1967-2019) in the Medical Birth Registry of Norway (miscarriage, stillbirth, hypertensive disorders of pregnancy, gestational diabetes, small for gestational age, large for gestational age, and spontaneous preterm birth). Maternal and paternal genetic risk scores (GRS) for CHD were generated using 148 gene variants (p-value < 5 × 10-8, not in linkage disequilibrium). Associations between GRS for CHD and each APO were determined using logistic regression, adjusting for genomic principal components, in each cohort separately, and combined using fixed effects meta-analysis. RESULTS: One standard deviation higher GRS for CHD in women was related to increased risk of any hypertensive disorders of pregnancy (odds ratio [OR] 1.08, 95% confidence interval [CI] 1.05-1.10), pre-eclampsia (OR 1.08, 95% CI 1.05-1.11), and small for gestational age (OR 1.04, 95% CI 1.01-1.06). Imprecise associations with lower odds of large for gestational age (OR 0.98, 95% CI 0.96-1.00) and higher odds of stillbirth (OR 1.04, 95% CI 0.98-1.11) were suggested. These findings remained consistent after adjusting for number of total pregnancies and the male partners' GRS and restricting analyses to stable couples. Associations for other APOs were close to the null. There was weak evidence of an association of paternal genetically predicted liability for CHD with spontaneous preterm birth in female partners (OR 1.02, 95% CI 0.99-1.05), but not with other APOs. CONCLUSIONS: Hypertensive disorders of pregnancy, small for gestational age, and stillbirth may unmask women with a genetically predicted propensity for CHD. The association of paternal genetically predicted CHD risk with spontaneous preterm birth in female partners needs further exploration.

Separating the genetics of childhood and adult obesity: a validation study of genetic scores for body mass index in adolescence and adulthood in the HUNT Study.

From a life-course perspective, genetic and environmental factors driving childhood obesity may have a lasting influence on health later in life. However, how obesity trajectories vary throughout the life-course remains unknown. Recently, Richardson et al. created powerful early life and adult gene scores for body mass index (BMI) in a comprehensive attempt to separate childhood and adult obesity. The childhood score was derived using questionnaire-based data administered to adults aged 40-69 regarding their relative body size at age 10, making it prone to recall and misclassification bias. We therefore attempted to validate the childhood and adult scores using measured BMI data in adolescence and adulthood among 66 963 individuals from the HUNT Study in Norway from 1963 to 2019. The predictive performance of the childhood score was better in adolescence and early adulthood, whereas the predictive performance of the adult score was better in adulthood. In the age group 12-15.9 years, the variance explained by the childhood polygenic risk score (PRS) was 6.7% versus 2.4% for the adult PRS. In the age group 24-29.9 years, the variance explained by the adult PRS was 3.9% versus 3.6% for the childhood PRS. Our findings support that genetic factors driving BMI differ at young age and in adulthood. Within the framework of multivariable Mendelian randomization, the validated childhood gene score can now be used to determine the consequence of childhood obesity on later disease.

Genome-wide association study of cardiac troponin I in the general population.

Circulating cardiac troponin proteins are associated with structural heart disease and predict incident cardiovascular disease in the general population. However, the genetic contribution to cardiac troponin I (cTnI) concentrations and its causal effect on cardiovascular phenotypes are unclear. We combine data from two large population-based studies, the Trøndelag Health Study and the Generation Scotland Scottish Family Health Study, and perform a genome-wide association study of high-sensitivity cTnI concentrations with 48 115 individuals. We further use two-sample Mendelian randomization to investigate the causal effects of circulating cTnI on acute myocardial infarction (AMI) and heart failure (HF). We identified 12 genetic loci (8 novel) associated with cTnI concentrations. Associated protein-altering variants highlighted putative functional genes: CAND2, HABP2, ANO5, APOH, FHOD3, TNFAIP2, KLKB1 and LMAN1. Phenome-wide association tests in 1688 phecodes and 83 continuous traits in UK Biobank showed associations between a genetic risk score for cTnI and cardiac arrhythmias, metabolic and anthropometric measures. Using two-sample Mendelian randomization, we confirmed the non-causal role of cTnI in AMI (5948 cases, 355 246 controls). We found indications for a causal role of cTnI in HF (47 309 cases and 930 014 controls), but this was not supported by secondary analyses using left ventricular mass as outcome (18 257 individuals). Our findings clarify the biology underlying the heritable contribution to circulating cTnI and support cTnI as a non-causal biomarker for AMI in the general population. Using genetically informed methods for causal inference helps inform the role and value of measuring cTnI in the general population.

Investigating the causal interplay between sleep traits and risk of acute myocardial infarction: a Mendelian randomization study.

BACKGROUND: Few studies have investigated the joint effects of sleep traits on the risk of acute myocardial infarction (AMI). No previous study has used factorial Mendelian randomization (MR) which may reduce confounding, reverse causation, and measurement error. Thus, it is prudent to study joint effects using robust methods to propose sleep-targeted interventions which lower the risk of AMI. METHODS: The causal interplay between combinations of two sleep traits (including insomnia symptoms, sleep duration, or chronotype) on the risk of AMI was investigated using factorial MR. Genetic risk scores for each sleep trait were dichotomized at their median in UK Biobank (UKBB) and the second survey of the Trøndelag Health Study (HUNT2). A combination of two sleep traits constituting 4 groups were analyzed to estimate the risk of AMI in each group using a 2×2 factorial MR design. RESULTS: In UKBB, participants with high genetic risk for both insomnia symptoms and short sleep had the highest risk of AMI (hazard ratio (HR) 1.10; 95% confidence interval (CI) 1.03, 1.18), although there was no evidence of interaction (relative excess risk due to interaction (RERI) 0.03; 95% CI -0.07, 0.12). These estimates were less precise in HUNT2 (HR 1.02; 95% CI 0.93, 1.13), possibly due to weak instruments and/or small sample size. Participants with high genetic risk for both a morning chronotype and insomnia symptoms (HR 1.09; 95% CI 1.03, 1.17) and a morning chronotype and short sleep (HR 1.11; 95% CI 1.04, 1.19) had the highest risk of AMI in UKBB, although there was no evidence of interaction (RERI 0.03; 95% CI -0.06, 0.12; and RERI 0.05; 95% CI -0.05, 0.14, respectively). Chronotype was not available in HUNT2. CONCLUSIONS: This study reveals no interaction effects between sleep traits on the risk of AMI, but all combinations of sleep traits increased the risk of AMI except those with long sleep. This indicates that the main effects of sleep traits on AMI are likely to be independent of each other.

The causal role of C-reactive protein and interleukin-6 on anxiety and depression symptoms and life satisfaction: Mendelian randomisation analyses in the HUNT study.

BACKGROUND: Serum levels of C-reactive protein (CRP) and interleukin-6 (IL-6) have been associated with anxiety and depression in cross-sectional and Mendelian randomisation studies, but results regarding the effect size and direction have been mixed. A recent Mendelian Randomisation (MR) study suggested that CRP may decrease and IL-6 may increase anxiety and depression symptoms. METHODS: Among 68 769 participants of the population-based Trøndelag Health Study (HUNT), we performed cross-sectional observational and one-sample MR analyses of serum CRP and two-sample MR analysis of serum IL-6. The main outcomes were symptoms of anxiety and depression assessed using the Hospital Anxiety and Depression Scale (HADS) and life satisfaction assessed using a seven-level ordinal questionnaire where higher scores indicate lower life satisfaction. RESULTS: In cross-sectional observational analyses, a doubling in serum CRP level was associated with 0.27% (95% CI -0.20 to 0.75) difference in HADS depression score (HADS-D), -0.77% (95% CI -1.24 to -0.29) difference in HADS anxiety score (HADS-A) and -0.10% (95% CI -0.41 to 0.21) difference in life satisfaction score. In one-sample MR analyses, a doubling in serum CRP was associated with 2.43% (95% CI -0.11 to 5.03) higher HADS-D, 1.94% (95% CI -0.58 to 4.52) higher HADS-A, and 2.00% (95% CI 0.45 to 3.59) higher life satisfaction score. For IL-6, causal point estimates were in the opposite direction, but imprecise and far from conventional criteria for statistical significance. CONCLUSIONS: Our results do not support a major causal role of serum CRP on anxiety and depression symptoms and life satisfaction, but provides weak evidence that serum CRP may modestly increase anxiety and depression symptoms and reduce life satisfaction. Our findings do not support the recent suggestion that serum CRP may lower anxiety and depression symptoms.

Using Genomic Structural Equation Modeling to Partition the Genetic Covariance Between Birthweight and Cardiometabolic Risk Factors into Maternal and Offspring Components in the Norwegian HUNT Study.

The Barker Hypothesis posits that adverse intrauterine environments result in fetal growth restriction and increased risk of cardiometabolic disease through developmental compensations. Here we introduce a new statistical model using the genomic SEM software that is capable of simultaneously partitioning the genetic covariation between birthweight and cardiometabolic traits into maternally mediated and offspring mediated contributions. We model the covariance between birthweight and later life outcomes, such as blood pressure, non-fasting glucose, blood lipids and body mass index in the Norwegian HUNT study, consisting of 15,261 mother-eldest offspring pairs with genetic and phenotypic data. Application of this model showed some evidence for maternally mediated effects of systolic blood pressure on offspring birthweight, and pleiotropy between birthweight and non-fasting glucose mediated through the offspring genome. This underscores the importance of genetic links between birthweight and cardiometabolic phenotypes and offer alternative explanations to environmentally based hypotheses for the phenotypic correlation between these variables.

Insight into the relationship between resting heart rate and atrial fibrillation: a Mendelian randomization study.

AIMS: A low resting heart rate (RHR) implies a more efficient heart function and a lower risk of cardiovascular disease. However, observational studies have reported a U-shaped association between RHR and atrial fibrillation (AF). In contrast, Mendelian randomization (MR) studies have found an inverse causal association between RHR and AF. Hence, the causal nature of the relationship is not clear. The aim is to investigate the causal association and its shape between RHR on AF using linear and non-linear MR (NLMR). METHODS AND RESULTS: Linear and non-linear MR were performed on individual-level data in the Trøndelag Health Study (HUNT) and UK Biobank (UKB). HUNT consists of 69 155 individuals with 7,062 AF cases, while UKB provides data on 431 852 individuals with 20 452 AF cases. The linear MR found an inverse relationship between RHR and AF with an OR = 0.95 [95% confidence interval (CI): 0.93-0.98] and OR = 0.96 (95% CI: 0.95-0.97) per unit decrease in RHR in HUNT and UKB, respectively. The NLMR was supportive of an inverse linear relationship in both HUNT and UKB for RHR values <90 beats per minute (bpm). Several sensitivity analyses were also consistent. CONCLUSION: In contrast with the current observational knowledge of RHR and AF, an inverse causal association between RHR and AF was demonstrated in both linear and non-linear MR for RHR values up to 90 bpm. Further exploring the underlying mechanisms of the genetic instrument for RHR may shed light on whether pleiotropy is biasing this association.

Self-reported insomnia symptoms, sleep duration, chronotype and the risk of acute myocardial infarction (AMI): a prospective study in the UK Biobank and the HUNT Study.

Insomnia and short/long sleep duration increase the risk of AMI, but their interaction with each other or with chronotype is not well known. We investigated the prospective joint associations of any two of these sleep traits on risk of AMI. We included 302 456 and 31 091 participants without past AMI episodes from UK Biobank (UKBB; 2006-10) and the Trøndelag Health Study (HUNT2; 1995-97), respectively. A total of 6 833 and 2 540 incident AMIs were identified during an average 11.7 and 21.0 years follow-up, in UKBB and HUNT2, respectively. Compared to those who reported normal sleep duration (7-8 h) without insomnia symptoms, the Cox proportional hazard ratios (HRs) for incident AMI in UKBB among participants who reported normal, short and long sleep duration with insomnia symptoms were 1.07 (95% CI 0.99, 1.15), 1.16 (95% CI 1.07, 1.25) and 1.40 (95% CI 1.21, 1.63), respectively. The corresponding HRs in HUNT2 were 1.09 (95% CI 0.95, 1.25), 1.17 (95% CI 0.87, 1.58) and 1.02 (95% CI 0.85, 1.23). The HRs for incident AMI in UKBB among evening chronotypes were 1.19 (95% CI 1.10, 1.29) for those who had insomnia symptoms, 1.18 (95% CI 1.08, 1.29) for those with short sleep duration, and 1.21 (95% CI 1.07, 1.37) for those with long sleep duration, compared to morning chronotypes without another sleep symptom. The relative excess risk for incident AMI in UKBB due to interaction between insomnia symptoms and long sleep duration was 0.25 (95% CI 0.01, 0.48). Insomnia symptoms with long sleep duration may contribute more than just an additive effect of these sleep traits on the risk of AMI.

Age-of-onset information helps identify 76 genetic variants associated with allergic disease.

Risk factors that contribute to inter-individual differences in the age-of-onset of allergic diseases are poorly understood. The aim of this study was to identify genetic risk variants associated with the age at which symptoms of allergic disease first develop, considering information from asthma, hay fever and eczema. Self-reported age-of-onset information was available for 117,130 genotyped individuals of European ancestry from the UK Biobank study. For each individual, we identified the earliest age at which asthma, hay fever and/or eczema was first diagnosed and performed a genome-wide association study (GWAS) of this combined age-of-onset phenotype. We identified 50 variants with a significant independent association (P<3x10-8) with age-of-onset. Forty-five variants had comparable effects on the onset of the three individual diseases and 38 were also associated with allergic disease case-control status in an independent study (n = 222,484). We observed a strong negative genetic correlation between age-of-onset and case-control status of allergic disease (rg = -0.63, P = 4.5x10-61), indicating that cases with early disease onset have a greater burden of allergy risk alleles than those with late disease onset. Subsequently, a multivariate GWAS of age-of-onset and case-control status identified a further 26 associations that were missed by the univariate analyses of age-of-onset or case-control status only. Collectively, of the 76 variants identified, 18 represent novel associations for allergic disease. We identified 81 likely target genes of the 76 associated variants based on information from expression quantitative trait loci (eQTL) and non-synonymous variants, of which we highlight ADAM15, FOSL2, TRIM8, BMPR2, CD200R1, PRKCQ, NOD2, SMAD4, ABCA7 and UBE2L3. Our results support the notion that early and late onset allergic disease have partly distinct genetic architectures, potentially explaining known differences in pathophysiology between individuals.

Genetic loci and prioritization of genes for kidney function decline derived from a meta-analysis of 62 longitudinal genome-wide association studies.

Estimated glomerular filtration rate (eGFR) reflects kidney function. Progressive eGFR-decline can lead to kidney failure, necessitating dialysis or transplantation. Hundreds of loci from genome-wide association studies (GWAS) for eGFR help explain population cross section variability. Since the contribution of these or other loci to eGFR-decline remains largely unknown, we derived GWAS for annual eGFR-decline and meta-analyzed 62 longitudinal studies with eGFR assessed twice over time in all 343,339 individuals and in high-risk groups. We also explored different covariate adjustment. Twelve genome-wide significant independent variants for eGFR-decline unadjusted or adjusted for eGFR-baseline (11 novel, one known for this phenotype), including nine variants robustly associated across models were identified. All loci for eGFR-decline were known for cross-sectional eGFR and thus distinguished a subgroup of eGFR loci. Seven of the nine variants showed variant-by-age interaction on eGFR cross section (further about 350,000 individuals), which linked genetic associations for eGFR-decline with age-dependency of genetic cross-section associations. Clinically important were two to four-fold greater genetic effects on eGFR-decline in high-risk subgroups. Five variants associated also with chronic kidney disease progression mapped to genes with functional in-silico evidence (UMOD, SPATA7, GALNTL5, TPPP). An unfavorable versus favorable nine-variant genetic profile showed increased risk odds ratios of 1.35 for kidney failure (95% confidence intervals 1.03-1.77) and 1.27 for acute kidney injury (95% confidence intervals 1.08-1.50) in over 2000 cases each, with matched controls). Thus, we provide a large data resource, genetic loci, and prioritized genes for kidney function decline, which help inform drug development pipelines revealing important insights into the age-dependency of kidney function genetics.

Genetic Architectures of Childhood- and Adult-Onset Asthma Are Partly Distinct.

The extent to which genetic risk factors are shared between childhood-onset (COA) and adult-onset (AOA) asthma has not been estimated. On the basis of data from the UK Biobank study (n = 447,628), we found that the variance in disease liability explained by common variants is higher for COA (onset at ages between 0 and 19 years; h2g = 25.6%) than for AOA (onset at ages between 20 and 60 years; h2g = 10.6%). The genetic correlation (rg) between COA and AOA was 0.67. Variation in age of onset among COA-affected individuals had a low heritability (h2g = 5%), which we confirmed in independent studies and also among AOA-affected individuals. To identify subtype-specific genetic associations, we performed a genome-wide association study (GWAS) in the UK Biobank for COA (13,962 affected individuals) and a separate GWAS for AOA (26,582 affected individuals) by using a common set of 300,671 controls for both studies. We identified 123 independent associations for COA and 56 for AOA (37 overlapped); of these, 98 and 34, respectively, were reproducible in an independent study (n = 262,767). Collectively, 28 associations were not previously reported. For 96 COA-associated variants, including five variants that represent COA-specific risk factors, the risk allele was more common in COA- than in AOA-affected individuals. Conversely, we identified three variants that are stronger risk factors for AOA. Variants associated with obesity and smoking had a stronger contribution to the risk of AOA than to the risk of COA. Lastly, we identified 109 likely target genes of the associated variants, primarily on the basis of correlated expression quantitative trait loci (up to n = 31,684). GWAS informed by age of onset can identify subtype-specific risk variants, which can help us understand differences in pathophysiology between COA and AOA and so can be informative for drug development.

Body mass index and incidence of lung cancer in the HUNT study: using observational and Mendelian randomization approaches.

BACKGROUND: Traditional observational studies have shown an inverse association between body mass index (BMI) and lung cancer risk. Mendelian randomization (MR) analysis using genetic variants as instruments for BMI may clarify the nature of the association. AIMS: We studied the causal association between BMI and lung cancer incidence using observational and MR approaches. METHODS: We followed up 62,453 cancer-free Norwegian adults from 1995-97 (HUNT2) until 2017. BMI at baseline in HUNT2 was classified as < 25.0, 25.0-29.9 and ≥ 30.0 kg/m2. BMI change over ten years between HUNT1 (1984-86) and HUNT2 was calculated and classified into quartiles. Seventy-five genetic variants were included as instruments for BMI (among which 14 also associated with smoking behavior). Incident lung cancer cases were ascertained from the Cancer Registry of Norway. Cox regression models were used to estimate hazard ratios (HRs) with 95% confidence intervals (CIs). Multivariable MR was used to examine the effect of BMI after genetically controlling for smoking. RESULTS: During a median follow-up of 21.1 years, 1009 participants developed lung cancer including 327 with lung adenocarcinoma. The HRs and 95% CIs for incidence of adenocarcinoma were 0.73 (0.58-0.92) for BMI 25.0-29.9 kg/m2 and 0.53 (0.37-0.76) for BMI ≥ 30 kg/m2 compared with BMI < 25.0 kg/m2 in HUNT2 (P for trend < 0.001). However, there was little evidence of a dose-response relationship between the BMI change from HUNT1 to HUNT2 in quartiles and the incidence of adenocarcinoma (P for trend = 0.08). Furthermore, multivariable MR approach suggested a positive association between genetically determined 1 kg/m2 increase in BMI and the incidence of adenocarcinoma (HR 1.25, 95% CI 1.02-1.53). No associations were found with other lung cancer histologic types. CONCLUSIONS: Our study suggests that the inverse association between baseline BMI and lung adenocarcinoma in observational analysis may not be causal. More MR studies are needed to confirm our finding of a positive association between BMI and lung adenocarcinoma.

Investigating obesity-related risk factors for childhood asthma.

BACKGROUND: We tested the hypothesis that multiple obesity-related risk factors (obesity, physical activity, cardiopulmonary physical fitness, sleep-disorder breathing (SDB), and sleep quality) are associated with childhood asthma using a Mendelian randomization (MR) design. Furthermore, we aim to investigate whether these risk factors were associated with incident asthma prospectively. METHODS: In total, 7069 children aged 12 from the Taiwan Children Health Study were enrolled in the current study. Cross-sectional logistic regression, one-sample MR, summary-level MR sensitivity analyses, and prospective survival analyses were used to investigate each causal pathway. RESULTS: In MR analysis, three of the five risk factors (obesity, SDB, and sleep quality) were associated with asthma, with the highest effect sizes per inter-quartile range (IQR) increase observed for sleep quality (odds ratio [OR] = 1.42; 95% confidence interval [CI]: 1.06 to 1.92) and the lowest for obesity (OR = 1.08; 95% CI: 1.00-1.16). In the prospective survival analysis, obesity showed the highest risk of incident asthma per IQR increase (hazard ratio [HR] = 1.28; 95% CI: 1.05 to 1.56), followed by SDB (HR = 1.18; 95% CI: 1.08 to 1.29) and sleep quality (HR = 1.10; 95% CI: 1.03 to 1.17). CONCLUSION: Among the examined factors, the most plausible risk factors for asthma were obesity, SDB, and poor sleep quality. For the prevention of childhood asthma, relevant stakeholders should prioritize improving children's sleep quality and preventing obesity comorbidities such as SDB.

The HUNT study: Association of comorbidity clusters with long-term survival and incidence of exacerbation in a population-based Norwegian COPD cohort.

BACKGROUND AND OBJECTIVE: Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease often viewed as part of a multimorbidity complex. There is a need for better phenotyping of the disease, characterization of its interplay with other comorbidities and its association with long-term outcomes. This study aims to examine how clusters of comorbidities are associated with severe exacerbations and mortality in COPD. METHODS: Participants with potential COPD were recruited from the second (1995-1997) and third (2006-2008) survey of the HUNT Study and followed up until April 2020. Ten objectively identified comorbidities were clustered using self-organizing maps. Severe COPD exacerbations requiring hospitalization were assessed using hospital data. All-cause mortality was collected from national registries. Multivariable Cox regression was used to calculate hazard ratios (HRs) with 95% CIs for the association between comorbidity clusters and all-cause mortality. Poisson regression was used to calculate incidence rate ratios (IRRs) with 95% CI for the cumulative number of severe exacerbations for each cluster. RESULTS: Five distinct clusters were identified, including 'less comorbidity', 'psychological', 'cardiovascular', 'metabolic' and 'cachectic' clusters. Using the less comorbidity cluster as reference, the psychological and cachectic clusters were associated with all-cause mortality (HR 1.23 [1.04-1.45] and HR 1.83 [1.52-2.20], adjusted for age and sex). The same clusters also had increased risk of exacerbations (unadjusted IRR of 1.24 [95% CI 1.04-1.48] and 1.50 [95% CI 1.23-1.83], respectively). CONCLUSION: During 25 years of follow-up, individuals in the psychological and cachectic clusters had increased mortality. Furthermore, these clusters were associated with increased risk of severe COPD exacerbations.