Methodological approaches, challenges, and opportunities in the application of Mendelian randomisation to lifecourse epidemiology: A systematic literature review.

Diseases diagnosed in adulthood may have antecedents throughout (including prenatal) life. Gaining a better understanding of how exposures at different stages in the lifecourse influence health outcomes is key to elucidating the potential benefits of disease prevention strategies. Mendelian randomisation (MR) is increasingly used to estimate causal effects of exposures across the lifecourse on later life outcomes. This systematic literature review explores MR methods used to perform lifecourse investigations and reviews previous work that has utilised MR to elucidate the effects of factors acting at different stages of the lifecourse. We conducted searches in PubMed, Embase, Medline and MedRXiv databases. Thirteen methodological studies were identified. Four studies focused on the impact of time-varying exposures in the interpretation of "standard" MR techniques, five presented methods for repeat measures of the same exposure, and four described methodological approaches to handling multigenerational exposures. A further 127 studies presented the results of an applied research question. Over half of these estimated effects in a single generation and were largely confined to the exploration of questions regarding body composition. The remaining mostly estimated maternal effects. There is a growing body of research focused on the development and application of MR methods to address lifecourse research questions. The underlying assumptions require careful consideration and the interpretation of results rely on select conditions. Whilst we do not advocate for a particular strategy, we encourage practitioners to make informed decisions on how to approach a research question in this field with a solid understanding of the limitations present and how these may be affected by the research question, modelling approach, instrument selection, and data availability.

Establishing the relationships between adiposity and reproductive factors: a multivariable Mendelian randomization analysis.

BACKGROUND: Few studies have investigated associations between adiposity and reproductive factors using causal methods, both of which have a number of consequences on women's health. Here we assess whether adiposity at different points in the lifecourse affects reproductive factors differently and independently, and the plausibility of the impact of reproductive factors on adiposity. METHODS: We used genetic data from UK Biobank (273,238 women) and other consortia (EGG, GIANT, ReproGen and SSGAC) for eight reproductive factors: age at menarche, age at menopause, age at first birth, age at last birth, number of births, being parous, age first had sexual intercourse and lifetime number of sexual partners, and two adiposity traits: childhood and adulthood body size. We applied multivariable Mendelian randomization to account for genetic correlation and to estimate the causal effects of childhood and adulthood adiposity, independently of each other, on reproductive factors. Additionally, we estimated the effects of reproductive factors, independently of other relevant reproductive factors, on adulthood adiposity. RESULTS: We found a higher childhood body size leads to an earlier age at menarche, and an earlier age at menarche leads to a higher adulthood body size. Furthermore, we find contrasting and independent effects of childhood and adulthood body size on age at first birth (beta 0.22 SD (95% confidence interval: 0.14, 0.31) vs - 2.49 (- 2.93, - 2.06) per 1 SD increase), age at last birth (0.13 (0.06,0.21) vs - 1.86 (- 2.23, - 1.48) per 1 SD increase), age at menopause (0.17 (0.09, 0.25) vs - 0.99 (- 1.39, - 0.59) per 1 SD increase), and likelihood of having children (Odds ratio 0.97 (0.95, 1.00) vs 1.20 (1.06, 1.37) per 1 SD increase). CONCLUSIONS: Our findings demonstrate the importance of considering a lifecourse approach when investigating the inter-relationships between adiposity measures and reproductive events, as well as the use of 'age specific' genetic instruments when evaluating lifecourse hypotheses in a Mendelian randomization framework.

The EWAS Catalog: a database of epigenome-wide association studies.

Epigenome-wide association studies (EWAS) seek to quantify associations between traits/exposures and DNA methylation measured at thousands or millions of CpG sites across the genome. In recent years, the increase in availability of DNA methylation measures in population-based cohorts and case-control studies has resulted in a dramatic expansion of the number of EWAS being performed and published. To make this rich source of results more accessible, we have manually curated a database of CpG-trait associations (with p<1x10 -4) from published EWAS, each assaying over 100,000 CpGs in at least 100 individuals. From January 7, 2022, The EWAS Catalog contained 1,737,746 associations from 2,686 EWAS. This includes 1,345,398 associations from 342 peer-reviewed publications. In addition, it also contains summary statistics for 392,348 associations from 427 EWAS, performed on data from the Avon Longitudinal Study of Parents and Children (ALSPAC) and the Gene Expression Omnibus (GEO). The database is accompanied by a web-based tool and R package, giving researchers the opportunity to query EWAS associations quickly and easily, and gain insight into the molecular underpinnings of disease as well as the impact of traits and exposures on the DNA methylome. The EWAS Catalog data extraction team continue to update the database monthly and we encourage any EWAS authors to upload their summary statistics to our website. Details of how to upload data can be found here: http://www.ewascatalog.org/upload. The EWAS Catalog is available at http://www.ewascatalog.org.

The relationships between women's reproductive factors: a Mendelian randomisation analysis.

BACKGROUND: Women's reproductive factors include their age at menarche and menopause, the age at which they start and stop having children and the number of children they have. Studies that have linked these factors with disease risk have largely investigated individual reproductive factors and have not considered the genetic correlation and total interplay that may occur between them. This study aimed to investigate the nature of the relationships between eight female reproductive factors. METHODS: We used data from the UK Biobank and genetic consortia with data available for the following reproductive factors: age at menarche, age at menopause, age at first birth, age at last birth, number of births, being parous, age first had sexual intercourse and lifetime number of sexual partners. Linkage disequilibrium score regression (LDSC) was performed to investigate the genetic correlation between reproductive factors. We then applied Mendelian randomisation (MR) methods to estimate the causal relationships between these factors. Sensitivity analyses were used to investigate directionality of the effects, test for evidence of pleiotropy and account for sample overlap. RESULTS: LDSC indicated that most reproductive factors are genetically correlated (rg range: |0.06-0.94|), though there was little evidence for genetic correlations between lifetime number of sexual partners and age at last birth, number of births and ever being parous (rg < 0.01). MR revealed potential causal relationships between many reproductive factors, including later age at menarche (1 SD increase) leading to a later age at first sexual intercourse (beta (B) = 0.09 SD, 95% confidence intervals (CI) = 0.06,0.11), age at first birth (B = 0.07 SD, CI = 0.04,0.10), age at last birth (B = 0.06 SD, CI = 0.04,0.09) and age at menopause (B = 0.06 SD, CI = 0.03,0.10). Later age at first birth was found to lead to a later age at menopause (B = 0.21 SD, CI = 0.13,0.29), age at last birth (B = 0.72 SD, CI = 0.67, 0.77) and a lower number of births (B = -0.38 SD, CI = -0.44, -0.32). CONCLUSION: This study presents evidence that women's reproductive factors are genetically correlated and causally related. Future studies examining the health sequelae of reproductive factors should consider a woman's entire reproductive history, including the causal interplay between reproductive factors.

Integrative multiomics analysis highlights immune-cell regulatory mechanisms and shared genetic architecture for 14 immune-associated diseases and cancer outcomes.

Developing functional insight into the causal molecular drivers of immunological disease is a critical challenge in genomic medicine. Here, we systematically apply Mendelian randomization (MR), genetic colocalization, immune-cell-type enrichment, and phenome-wide association methods to investigate the effects of genetically predicted gene expression on ten immune-associated diseases and four cancer outcomes. Using whole blood-derived estimates for regulatory variants from the eQTLGen consortium (n = 31,684), we constructed genetic risk scores for 10,104 genes. Applying the inverse-variance-weighted MR method transcriptome wide while accounting for linkage disequilibrium structure identified 664 unique genes with evidence of a genetically predicted effect on at least one disease outcome (p < 4.81 × 10-5). We next undertook genetic colocalization to investigate cell-type-specific effects at these loci by using gene expression data derived from 18 types of immune cells. This highlighted many cell-type-dependent effects, such as PRKCQ expression and asthma risk (posterior probability = 0.998), which was T cell specific. Phenome-wide analyses on 311 complex traits and endpoints allowed us to explore shared genetic architecture and prioritize key drivers of disease risk, such as CASP10, which provided evidence of an effect on seven cancer-related outcomes. Our atlas of results can be used to characterize known and novel loci in immune-associated disease and cancer susceptibility, both in terms of elucidating cell-type-dependent effects as well as dissecting shared disease pathways and pervasive pleiotropy. As an exemplar, we have highlighted several key findings in this study, although similar evaluations can be conducted via our interactive web platform.

Investigating the DNA methylation profile of e-cigarette use.

BACKGROUND: Little evidence exists on the health effects of e-cigarette use. DNA methylation may serve as a biomarker for exposure and could be predictive of future health risk. We aimed to investigate the DNA methylation profile of e-cigarette use. RESULTS: Among 117 smokers, 117 non-smokers and 116 non-smoking vapers, we evaluated associations between e-cigarette use and epigenome-wide methylation from saliva. DNA methylation at 7 cytosine-phosphate-guanine sites (CpGs) was associated with e-cigarette use at p < 1 × 10-5 and none at p < 5.91 × 10-8. 13 CpGs were associated with smoking at p < 1 × 10-5 and one at p < 5.91 × 10-8. CpGs associated with e-cigarette use were largely distinct from those associated with smoking. There was strong enrichment of known smoking-related CpGs in the smokers but not the vapers. We also tested associations between e-cigarette use and methylation scores known to predict smoking and biological ageing. Methylation scores for smoking and biological ageing were similar between vapers and non-smokers. Higher levels of all smoking scores and a biological ageing score (GrimAge) were observed in smokers. A methylation score for e-cigarette use showed poor prediction internally (AUC 0.55, 0.41-0.69) and externally (AUC 0.57, 0.36-0.74) compared with a smoking score (AUCs 0.80) and was less able to discriminate lung squamous cell carcinoma from adjacent normal tissue (AUC 0.64, 0.52-0.76 versus AUC 0.73, 0.61-0.85). CONCLUSIONS: The DNA methylation profile for e-cigarette use is largely distinct from that of cigarette smoking, did not replicate in independent samples, and was unable to discriminate lung cancer from normal tissue. The extent to which methylation related to long-term e-cigarette use translates into chronic effects requires further investigation.

Novel nonsense variants in SLURP1 and DSG1 cause palmoplantar keratoderma in Pakistani families.

BACKGROUND: Inherited palmoplantar keratodermas (PPKs) are clinically and genetically heterogeneous and phenotypically diverse group of genodermatoses characterized by hyperkeratosis of the palms and soles. More than 20 genes have been reported to be associated with PPKs including desmoglein 1 (DSG1) a key molecular component for epidermal adhesion and differentiation. Mal de Meleda (MDM) is a rare inherited autosomal recessive genodermatosis characterized by transgrediens PPK, associated with mutations in the secreted LY6/PLAUR domain containing 1 (SLURP1) gene. METHODS: This study describes clinical as well as genetic whole exome sequencing (WES) and di-deoxy sequencing investigations in two Pakistani families with a total of 12 individuals affected by PPK. RESULTS: WES identified a novel homozygous nonsense variant in SLURP1, and a novel heterozygous nonsense variant in DSG1, as likely causes of the conditions in each family. CONCLUSIONS: This study expands knowledge regarding the molecular basis of PPK, providing important information to aid clinical management in families with PPK from Pakistan.

Investigating the impact of cigarette smoking behaviours on DNA methylation patterns in adolescence.

Smoking usually begins in adolescence, and early onset of smoking has been linked to increased risk of later life disease. There is a need to better understand the biological impact of cigarette smoking behaviours in adolescence. DNA methylation profiles related to smoking behaviours and cessation in adulthood have been previously identified, but alterations arising from smoking initiation have not been thoroughly investigated. We aimed to investigate DNA methylation in the Avon Longitudinal Study of Parents and Children in relation to (1) different smoking measures, (2) time since smoking initiation and frequency of smoke exposure and (3) latent classes of smoking behaviour. Using 2620 CpG sites previously associated with cigarette smoking, we investigated DNA methylation change in relation to own smoking measures, smoke exposure duration and frequency, and using longitudinal latent class analysis of different smoking behaviour patterns in 968 adolescents. Eleven CpG sites located in seven gene regions were differentially methylated in relation to smoking in adolescence. While only AHRR (cg05575921) showed a robust pattern of methylation in relation to weekly smoking, several CpGs showed differences in methylation among individuals who had tried smoking compared with non-smokers. In relation to smoke exposure duration and frequency, cg05575921 showed a strong dose-response relationship, while there was evidence for more immediate methylation change at other sites. Our findings illustrate the impact of cigarette smoking behaviours on DNA methylation at some smoking-responsive CpG sites, even among individuals with a short smoking history.