Quantifying the impact of genes on body mass index during the obesity epidemic : Longitudinal findings from the HUNT study

Objectives To study the trajectories of body mass index (BMI) in Norway over five decades and to assess the differential influence of the obesogenic environment on BMI according to genetic predisposition. Design Longitudinal study. Setting General population of Nord-Trøndelag County, Norway. Participants 118 959 people aged 13-80 years who participated in a longitudinal population based health study (Nord-Trøndelag Health Study, HUNT), of whom 67 305 were included in analyses of association between genetic predisposition and BMI. Main outcome measure BMI. Results Obesity increased in Norway starting between the mid-1980s and mid-1990s and, compared with older birth cohorts, those born after 1970 had a substantially higher BMI already in young adulthood. BMI differed substantially between the highest and lowest fifths of genetic susceptibility for all ages at each decade, and the difference increased gradually from the 1960s to the 2000s. For 35 year old men, the most genetically predisposed had 1.20 kg/m2 (95% confidence interval 1.03 to 1.37 kg/m2) higher BMI than those who were least genetically predisposed in the 1960s compared with 2.09 kg/m2 (1.90 to 2.27 kg/m2) in the 2000s. For women of the same age, the corresponding differences in BMI were 1.77 kg/m2 (1.56 to 1.97 kg/m2) and 2.58 kg/m2 (2.36 to 2.80 kg/m2). Conclusions This study provides evidence that genetically predisposed people are at greater risk for higher BMI and that genetic predisposition interacts with the obesogenic environment resulting in higher BMI, as observed between the mid-1980s and mid-2000s. Regardless, BMI has increased for both genetically predisposed and non-predisposed people, implying that the environment remains the main contributor.publishedVersionPaid Open Acces

Intergenerational polygenic obesity risk throughout adolescence in a cross-sectional study design: The HUNT study, Norway

Objective - This study examined the relationship between parental obesity polygenic risk and children’s BMI throughout adolescence. Additionally, from a smaller subsample, the objective was to assess whether parental polygenic risk score (PRS) may act as a proxy for offspring PRS in studies lacking offspring genetic data. Methods - A total of 8,561 parent-offspring (age 13-19 years) trios from the Trøndelag Health Study (the HUNT Study) were included, of which, 1,286 adolescents had available genetic data. Weighted parental PRSs from 900 single-nucleotide polymorphisms robustly associated with adult BMI were constructed and applied in linear mixed-effects models. Results - A positive association between parental PRS and offspring sex- and age-adjusted BMI (iso-BMI) throughout adolescence was identified. The estimated marginal effects per standard deviation increase in parental PRS were 0.26 (95% CI: 0.18-0.33), 0.36 (95% CI: 0.29-0.43), and 0.62 kg/m2 (95% CI: 0.51-0.72) for maternal, paternal, and combined parental PRS, respectively. In subsample analyses, the magnitude of association of the parental PRS versus offspring PRS with iso-BMI in adolescents was similar. Conclusions - Parental PRS was consistently associated with offspring iso-BMI throughout adolescence. Results from subsample analyses support the use of parental PRS of obesity as a proxy for adolescent PRS in the absence of offspring genetic data

Genetic associations with temporal shifts in obesity and severe obesity during the obesity epidemic in Norway:A longitudinal population-based cohort (the HUNT Study)

Background Obesity has tripled worldwide since 1975 as environments are becoming more obesogenic. Our study investigates how changes in population weight and obesity over time are associated with genetic predisposition in the context of an obesogenic environment over 6 decades and examines the robustness of the findings using sibling design. Methods and findings A total of 67,110 individuals aged 13–80 years in the Nord-Trøndelag region of Norway participated with repeated standardized body mass index (BMI) measurements from 1966 to 2019 and were genotyped in a longitudinal population-based health study, the Trøndelag Health Study (the HUNT Study). Genotyping required survival to and participation in the HUNT Study in the 1990s or 2000s. Linear mixed models with observations nested within individuals were used to model the association between a genome-wide polygenic score (GPS) for BMI and BMI, while generalized estimating equations were used for obesity (BMI ≥ 30 kg/m2) and severe obesity (BMI ≥ 35 kg/m2). The increase in the average BMI and prevalence of obesity was steeper among the genetically predisposed. Among 35-year-old men, the prevalence of obesity for the least predisposed tenth increased from 0.9% (95% confidence interval [CI] 0.6% to 1.2%) to 6.5% (95% CI 5.0% to 8.0%), while the most predisposed tenth increased from 14.2% (95% CI 12.6% to 15.7%) to 39.6% (95% CI 36.1% to 43.0%). Equivalently for women of the same age, the prevalence of obesity for the least predisposed tenth increased from 1.1% (95% CI 0.7% to1.5%) to 7.6% (95% CI 6.0% to 9.2%), while the most predisposed tenth increased from 15.4% (95% CI 13.7% to 17.2%) to 42.0% (95% CI 38.7% to 45.4%). Thus, for 35-year-old men and women, respectively, the absolute change in the prevalence of obesity from 1966 to 2019 was 19.8 percentage points (95% CI 16.2 to 23.5, p < 0.0001) and 20.0 percentage points (95% CI 16.4 to 23.7, p < 0.0001) greater for the most predisposed tenth compared with the least predisposed tenth, defined using the GPS for BMI. The corresponding absolute changes in the prevalence of severe obesity for men and women, respectively, were 8.5 percentage points (95% CI 6.3 to 10.7, p < 0.0001) and 12.6 percentage points (95% CI 9.6 to 15.6, p < 0.0001) greater for the most predisposed tenth. The greater increase in BMI in genetically predisposed individuals over time was apparent after adjustment for family-level confounding using a sibling design. Key limitations include a slightly lower survival to date of genetic testing for the older cohorts and that we apply a contemporary genetic score to past time periods. Future research should validate our findings using a polygenic risk score constructed from historical data. Conclusions In the context of increasingly obesogenic changes in our environment over 6 decades, our findings reveal a growing inequality in the risk for obesity and severe obesity across GPS tenths. Our results suggest that while obesity is a partially heritable trait, it is still modifiable by environmental factors. While it may be possible to identify those most susceptible to environmental change, who thus have the most to gain from preventive measures, efforts to reverse the obesogenic environment will benefit the whole population and help resolve the obesity epidemic

Evidence of a causal relationship between body mass index and psoriasis:A mendelian randomization study

Background: Psoriasis is a common inflammatory skin disease that has been reported to be associated with obesity. We aimed to investigate a possible causal relationship between body mass index (BMI) and psoriasis. Methods and Findings: Following a review of published epidemiological evidence of the association between obesity and psoriasis, mendelian randomization (MR) was used to test for a causal relationship with BMI. We used a genetic instrument comprising 97 single-nucleotide polymorphisms (SNPs) associated with BMI as a proxy for BMI (expected to be much less confounded than measured BMI). One-sample MR was conducted using individual-level data (396,495 individuals) from the UK Biobank and the Nord-Trøndelag Health Study (HUNT), Norway. Two-sample MR was performed with summary-level data (356,926 individuals) from published BMI and psoriasis genome-wide association studies (GWASs). The one-sample and two-sample MR estimates were meta-analysed using a fixed-effect model. To test for a potential reverse causal effect, MR analysis with genetic instruments comprising variants from recent genome-wide analyses for psoriasis were used to test whether genetic risk for this skin disease has a causal effect on BMI. Published observational data showed an association of higher BMI with psoriasis. A mean difference in BMI of 1.26 kg/m2 (95% CI 1.02-1.51) between psoriasis cases and controls was observed in adults, while a 1.55 kg/m2 mean difference (95% CI 1.13-1.98) was observed in children. The observational association was confirmed in UK Biobank and HUNT data sets. Overall, a 1 kg/m2 increase in BMI was associated with 4% higher odds of psoriasis (meta-analysis odds ratio [OR] = 1.04; 95% CI 1.03-1.04; P = 1.73 × 10-60). MR analyses provided evidence that higher BMI causally increases the odds of psoriasis (by 9% per 1 unit increase in BMI; OR = 1.09 (1.06-1.12) per 1 kg/m2; P = 4.67 × 10-9). In contrast, MR estimates gave little support to a possible causal effect of psoriasis genetic risk on BMI (0.004 kg/m2 change in BMI per doubling odds of psoriasis (-0.003 to 0.011). Limitations of our study include possible misreporting of psoriasis by patients, as well as potential misdiagnosis by clinicians. In addition, there is also limited ethnic variation in the cohorts studied. Conclusions: Our study, using genetic variants as instrumental variables for BMI, provides evidence that higher BMI leads to a higher risk of psoriasis. This supports the prioritization of therapies and lifestyle interventions aimed at controlling weight for the prevention or treatment of this common skin disease. Mechanistic studies are required to improve understanding of this relationship

Body mass index and all cause mortality in HUNT and UK Biobank studies:linear and non-linear mendelian randomisation analyses

Objective To investigate the shape of the causal relation between body mass index (BMI) and mortality. Design Linear and non-linear mendelian randomisation analyses. Setting Nord-Trøndelag Health (HUNT) Study (Norway) and UK Biobank (United Kingdom). Participants Middle to early late aged participants of European descent: 56 150 from the HUNT Study and 366 385 from UK Biobank. Main outcome measures All cause and cause specific (cardiovascular, cancer, and non-cardiovascular non-cancer) mortality. Results 12 015 and 10 344 participants died during a median of 18.5 and 7.0 years of follow-up in the HUNT Study and UK Biobank, respectively. Linear mendelian randomisation analyses indicated an overall positive association between genetically predicted BMI and the risk of all cause mortality. An increase of 1 unit in genetically predicted BMI led to a 5% (95% confidence interval 1% to 8%) higher risk of mortality in overweight participants (BMI 25.0-29.9) and a 9% (4% to 14%) higher risk of mortality in obese participants (BMI ≥30.0) but a 34% (16% to 48%) lower risk in underweight (BMI <18.5) and a 14% (−1% to 27%) lower risk in low normal weight participants (BMI 18.5-19.9). Non-linear mendelian randomisation indicated a J shaped relation between genetically predicted BMI and the risk of all cause mortality, with the lowest risk at a BMI of around 22-25 for the overall sample. Subgroup analyses by smoking status, however, suggested an always-increasing relation of BMI with mortality in never smokers and a J shaped relation in ever smokers. Conclusions The previously observed J shaped relation between BMI and risk of all cause mortality appears to have a causal basis, but subgroup analyses by smoking status revealed that the BMI-mortality relation is likely comprised of at least two distinct curves, rather than one J shaped relation. An increased risk of mortality for being underweight was only evident in ever smokers

Avoiding dynastic, assortative mating, and population stratification biases in Mendelian randomization through within-family analyses.

Estimates from Mendelian randomization studies of unrelated individuals can be biased due to uncontrolled confounding from familial effects. Here we describe methods for within-family Mendelian randomization analyses and use simulation studies to show that family-based analyses can reduce such biases. We illustrate empirically how familial effects can affect estimates using data from 61,008 siblings from the Nord-Trøndelag Health Study and UK Biobank and replicated our findings using 222,368 siblings from 23andMe. Both Mendelian randomization estimates using unrelated individuals and within family methods reproduced established effects of lower BMI reducing risk of diabetes and high blood pressure. However, while Mendelian randomization estimates from samples of unrelated individuals suggested that taller height and lower BMI increase educational attainment, these effects were strongly attenuated in within-family Mendelian randomization analyses. Our findings indicate the necessity of controlling for population structure and familial effects in Mendelian randomization studies

Darlings and Disability - Perceived Health in Couples and Disability Pension Receipt

Background In Norway, almost 10% of the working age population receive a disability pension. Spouses tend to have similar health and lifestyle, and they also tend to coordinate their retirements. Spousal similarities can be explained by similarities existing before marriage, spousal influence and shared resources. Sickness is the social role related to disease and illness, sickness is therefore also a social construct. There are thus both medical and non-medical determinants of work related disability, and there might be temporal changes in the illness experienced by people who receive a disability pension. Aims The aims of this thesis were to assess disability pension receipt in Norway in the context of the married or cohabitating couple, and to consider how the health around time of receiving a disability pension might have changed over time. Methods We conducted three studies based on the second and third wave of the Nord-Trøndelag Health Study (HUNT2 1995-97 and HUNT3 2006-08), linked to data on households and families, retirements and education from national registries. In the first study, we assessed the clustering of disability pensions received within couples, as well as the hazard of receiving a disability pension dependent on the spouse’s disability status. We adjusted for baseline health, diseases, illness, health-related behaviours and education. In the second study, we examined the associations of health, disease, illness, lifestyle and education in couples with disability pension receipt and mortality. We estimated association both within and between couples. In the third study, we examined the self-rated health, insomnia and mental symptoms of people who received a disability pension in the 1990s and 2000s and their spouses, depending on time before or after receiving a disability pension. Results In the first paper, we identified a substantial clustering of disability pensions in couples and an increased risk of receiving a disability pension for more than six years after the spouse’s disability pension for both men and women. The hazard of receiving disability pensions increased by about a third after the spouse had received a disability pension. In the second paper, we found indication of an association between the couple’s exposures and the individual’s risk of receiving a disability pension. This association appeared for poor self-rated health, illness and education, but not for somatic diseases. Such associations could indicate influence from the burden of a partner with poor health, but also shared confounding in the couple. We did not find corresponding association between poor health in the couple and the individual’s mortality. There were, however, associations between couple’s smoking and education and the individual’s mortality. In the third paper, we found a peak in prevalence of poor self-rated health around time of disability pension, and similar prevalence of poor self-rated health among those who received a disability pension in the 1990s and 2000s. Symptoms of depression peaked the year before a disability pension in the 1990s, while the prevalence was similar before and after receiving a disability pension in the 2000s. Estimated prevalence of insomnia increased between the 1990s and 2000s. On the other hand, the association between time before or after receiving a disability pension and insomnia was stronger in the 1990s compared to the 2000s. We did not find statistical evidence of associations between time before or after receiving a disability pension and the spouse’s health and illness. Conclusions We found a substantial clustering of disability pensions within couples. Some of this could be attributed to pre-existing similarities between partners. Living with an ill spouse could have a negative impact on work related disability, but we did not find that it affected all-cause mortality. A negative impact on the spouse’s health could still not explain the higher risk of receiving a disability pension when the spouse after the spouse had received a disability pension. Other contributing mechanisms could include social influence on illness behaviour and self-efficacy. Furthermore, our results indicate that the health and illness experienced by individuals who received a disability pension did not change much from the 1990s to the 2000s. This suggests that the National Labour and Welfare Administration treated requests for disability pensions in similar manners in the two time periods. However, the stress related to the disability process seemed to be lower in the 2000s compared to the 1990s. This could be due to faster case handling or fewer stigmas. Our findings of possible associations between couple’s health and individual work related disability should be examined further. In the clinical setting, spouses could be included in the discussions about opportunities and limitations regarding return-to-work