Dataset Information

Causal relationship between the timing of menarche and young adult body mass index with consideration to a trend of consistently decreasing age at menarche.

ABSTRACT: Younger age at menarche (AAM) is associated with higher body mass index (BMI) for young women. Considering that continuous trends in decreasing AAM and increasing BMI are found in many countries, we attempted to assess whether the observed negative association between AAM and young adult BMI is causal. We included 4,093 women from the Korean Genome and Epidemiology Study (KoGES) and Healthy twin Study (HTS) with relevant epidemiologic data and genome-wide marker information. To mitigate the remarkable differences in AAM across generations, we converted the AAM to a generation-standardized AAM (gsAAM). To test causality, we applied the Mendelian randomization (MR) approach, using a genetic risk score (GRS) based on 14 AAM-associated single nucleotide polymorphisms (SNPs). We constructed MR models adjusting for education level and validated the results using the inverse-variance weighted (IVW), weighted median (WM), MR-pleiotropy residual sum and outliers test (MR-PRESSO), and MR-Egger regression methods. We found a null association using observed AAM and BMI level (conventional regression; -0.05 [95% CIs -0.10-0.00] per 1-year higher AAM). This null association was replicated when gsAAM was applied instead of AAM. Using the two-stage least squares (2SLS) approach employing a univariate GRS, the association was also negated for both AAM and gsAAM, regardless of model specifications. All the MR diagnostics suggested statistically insignificant associations, but weakly negative trends, without evidence of confounding from pleiotropy. We did not observe a causal association between AAM and young adult BMI whether we considered the birth cohort effect or not. Our study alone does not exclude the possibility of existing a weak negative association, considering the modest power of our study design.

SUBMITTER: Kim H

PROVIDER: S-EPMC7909625 | biostudies-literature | 2021

REPOSITORIES: biostudies-literature

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Causal relationship between the timing of menarche and young adult body mass index with consideration to a trend of consistently decreasing age at menarche.

Kim Hakyung H Choe Seung-Ah SA Lee Soo Ji SJ Sung Joohon J

PloS one 20210226 2

Younger age at menarche (AAM) is associated with higher body mass index (BMI) for young women. Considering that continuous trends in decreasing AAM and increasing BMI are found in many countries, we attempted to assess whether the observed negative association between AAM and young adult BMI is causal. We included 4,093 women from the Korean Genome and Epidemiology Study (KoGES) and Healthy twin Study (HTS) with relevant epidemiologic data and genome-wide marker information. To mitigate the rema ...[more]

PMID: 33635908

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Project description:ObjectiveThe occurrence and development of oesophageal neoplasia (ON) is closely related to hormone changes. The aim of this study was to investigate the causal relationships between age at menarche (AAMA) or age at menopause (AAMO) and benign oesophageal neoplasia (BON) or malignant oesophageal neoplasia (MON) from a genetic perspective.MethodsGenome-wide association study (GWAS) summary data of exposures (AAMA and AAMO) and outcomes (BON and MON) were obtained from the IEU OpenGWAS database. We performed a two-sample Mendelian randomization (MR) study between them. The inverse variance weighted (IVW) was used as the main analysis method, while the MR Egger, weighted median, simple mode, and weighted mode were supplementary methods. The maximum likelihood, penalized weighted median, and IVW (fixed effects) were validation methods. We used Cochran's Q statistic and Rucker's Q statistic to detect heterogeneity. The intercept test of the MR Egger and global test of MR pleiotropy residual sum and outlier (MR-PRESSO) were used to detect horizontal pleiotropy, and the distortion test of the MR-PRESSO analysis was used to detect outliers. The leave-one-out analysis was used to detect whether the MR analysis was affected by single nucleotide polymorphisms (SNPs). In addition, the MR robust adjusted profile score (MR-RAPS) method was used to assess the robustness of MR analysis.ResultsThe random-effects IVW results showed that AAMA had a negative genetic causal relationship with BON (odds ratio [OR] = 0.285 [95% confidence interval [CI]: 0.130-0.623], P = 0.002). The weighted median, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with random-effects IVW (P < 0.05). The MR Egger, simple mode and weighted mode results showed that AAMA had no genetic causal relationship with BON (P > 0.05). However, there were no causal genetic relationships between AAMA and MON (OR = 1.132 [95%CI: 0.621-2.063], P = 0.685), AAMO and BON (OR = 0.989 [95%CI: 0.755-1.296], P = 0.935), or AAMO and MON (OR = 1.129 [95%CI: 0.938-1.359], P = 0.200). The MR Egger, weighted median, simple mode, weighted mode, maximum likelihood, penalized weighted median, and IVW (fixed effects) were consistent with a random-effects IVW (P > 0.05). MR analysis results showed no heterogeneity, the horizontal pleiotropy and outliers (P > 0.05). They were not driven by a single SNP, and were normally distributed (P > 0.05).ConclusionOnly AAMA has a negative genetic causal relationship with BON, and no genetic causal relationships exist between AAMA and MON, AAMO and BON, or AAMO and MON. However, it cannot be ruled out that they are related at other levels besides genetics.

Project description:BackgroundPsoriasis 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 findingsFollowing 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.ConclusionsOur 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.

Dataset Information

Causal relationship between the timing of menarche and young adult body mass index with consideration to a trend of consistently decreasing age at menarche.

Publications

Causal relationship between the timing of menarche and young adult body mass index with consideration to a trend of consistently decreasing age at menarche.

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