No evidence that retinol is protective for skin cancer.

With over 1.5 million new cases annually, skin cancers are the most commonly diagnosed group of cancers worldwide. Among these, melanoma and keratinocyte cancers (KC), comprising squamous cell carcinoma (SCC) and basal cell carcinoma (BCC), are predominant. Retinol, a vitamin A derivative, is essential in the regulation of growth and differentiation of epidermal cells. Moreover, retinol exhibits antioxidant properties, protecting the skin against ultra-violet (UV) radiation induced oxidative damage. Existing research on the impact of retinol on melanoma, SCC and BCC development shows mixed results. Several dietary intake studies have suggested that higher retinol levels reduce skin cancer risk, however, others have failed to find this association. We used two-sample Mendelian randomization (MR) to explore if there is a causal relationship between retinol and the risk of developing melanoma, SCC or BCC. Genetically predicted circulating retinol levels were obtained from a genome wide association study (GWAS) meta-analysis of the INTERVAL (N=11,132) and METSIM (N=6,136) cohorts. Melanoma (30,134 cases and 375,188 controls), SCC (10,557 cases and 537,850 controls) and BCC (36,479 cases and 540,185 controls) risks were derived from published GWAS meta-analyses. We conducted two MR approaches. In the first MR we used a single SNP (rs10882283) that is associated with the levels of Retinol Binding Protein 4 (RBP4) as an instrument variable (IV) for circulating retinol levels. In the second MR we used all independent genetic variants that were strongly associated (P < 5 × 10-8) with retinol levels as IVs. Odds ratios (OR) for skin cancer were calculated for a one standard deviation (SD) increase in genetically predicted retinol levels. The single IV approach revealed that retinol levels were not significantly associated with risk of melanoma (OR = 1.04 [95% confidence interval 0.83, 1.31], P = 0.72), SCC (OR = 1.15 [0.87, 1.51], P = 0.32) or BCC (OR = 1.06 [0.90, 1.23], P = 0.50). Similar null results were observed with the multiple IV approach for melanoma (OR = 1.03 [0.95, 1.11], P = 0.54), SCC (OR = 1.01 [0.91, 1.13], P = 0.83), and BCC (OR = 1.04 [0.96, 1.12], P = 0.38). In conclusion, we found no evidence that circulating retinol levels were causally associated with the development of melanoma, SCC and BCC.

Exploring the Germline Genetics of In Situ and Invasive Cutaneous Melanoma: A Genome-Wide Association Study Meta-Analysis.

Importance: It is unknown whether germline genetic factors influence in situ melanoma risk differently than invasive melanoma risk. Objective: To determine whether differences in risk of in situ melanoma and invasive melanoma are heritable. Design, Setting, and Participants: Three genome-wide association study meta-analyses were conducted of in situ melanoma vs controls, invasive melanoma vs controls, and in situ vs invasive melanoma (case-case) using 4 population-based genetic cohorts: the UK Biobank, the FinnGen cohort, the QSkin Sun and Health Study, and the Queensland Study of Melanoma: Environmental and Genetic Associations (Q-MEGA). Melanoma status was determined using International Statistical Classification of Diseases and Related Health Problems codes from cancer registry data. Data were collected from 1987 to 2022, and data were analyzed from September 2022 to June 2023. Exposure: In situ and invasive cutaneous melanoma. Main Outcomes and Measures: To test whether in situ and invasive melanoma have independent heritable components, genetic effect estimates were calculated for single-nucleotide variants (SNV; formerly single-nucleotide polymorphisms) throughout the genome for each melanoma. Then, SNV-based heritability was estimated, the genetic correlation between melanoma subtypes was assessed, and polygenic risk scores (PRS) were generated for in situ vs invasive status in Q-MEGA participants. Results: A total of 6 genome-wide significant loci associated with in situ melanoma and 18 loci with invasive melanoma were identified. A strong genetic correlation (genetic r = 0.96; 95% CI, 0.76-1.15) was observed between the 2 classifications. Notably, loci near IRF4, KLF4, and HULC had significantly larger effects for in situ melanoma compared with invasive melanoma, while MC1R had a significantly larger effect on invasive melanoma compared with in situ melanoma. Heritability estimates were consistent for both, with in situ melanoma heritability of 6.7% (95% CI, 4.1-9.3) and invasive melanoma heritability of 4.9% (95% CI, 2.8-7.2). Finally, a PRS, derived from comparing invasive melanoma with in situ melanoma genetic risk, was on average significantly higher in participants with invasive melanoma (odds ratio per 1-SD increase in PRS, 1.43; 95% CI, 1.16-1.77). Conclusions and Relevance: There is much shared genetic architecture between in situ melanoma and invasive melanoma. Despite indistinguishable heritability estimates between the melanoma classifications, PRS suggest germline genetics may influence whether a person gets in situ melanoma or invasive melanoma. PRS could potentially help stratify populations based on invasive melanoma risk, informing future screening programs without exacerbating the current burden of melanoma overdiagnosis.

Phenotypic and genotypic risk factors for invasive melanoma by sex and body site.

BACKGROUND: Cutaneous melanoma incidence varies consistently across body sites between men and women, but the underlying causes of the differences remain unclear. To date, no prospective studies have examined risk factors for melanoma separately for men and women according to body site. METHODS: We compared the association between constitutional, genetic and environmental risk factors for invasive melanoma on different body sites separately for men and women in a population-based prospective cohort study of 17,774 men and 21,070 women aged between 40 and 69 years and residents of Queensland, Australia at baseline in 2011. Participants were followed until December 2021.We examined risk factors including hair colour, tanning ability, naevus density, and proxies for high cumulative sun exposure, all self-reported at baseline. We also examined polygenic risk score (PRS) derived from summary statistics from a melanoma genome-wide association study meta-analysis. RESULTS: During a median 10.4 years of follow-up, 455 men and 331 women developed an incident invasive melanoma; the mean age at diagnosis was lower in women than in men (62.6 vs. 65.0, respectively). The most common body site was the trunk in men (45.1%), and the upper (36.8%) and lower limbs (27.4%) in women. High naevus density and proxy measures of high cumulative sun exposure were similarly associated with melanoma at all sites in men and women. In both sexes, high genetic risk was associated with melanoma on all body sites except the head and neck. We observed differences between men and women in the association between PRS and melanoma of the trunk (highest vs. lowest tertile of PRS: HR 2.78, 95% CI 1.64-4.69 for men; 1.55, 95% CI 0.63-3.80 for women), and non-significant but large differences for the lower limbs (HR 5.25, 95% CI 1.80-15.27 for men; 1.75, 95% CI 0.88-3.47 for women). CONCLUSIONS: While there are a number of potential explanations for these findings, this raises the possibility that genetic factors other than those related to pigmentation and naevus phenotypes may play a role in the predilection for melanoma to arise on different sites between the sexes.

Genetic predisposition to childhood obesity does not influence the risk of developing skin cancer in adulthood.

The relationship between body mass index (BMI) and melanoma and other skin cancers remains unclear. The objective of this study was to employ the Mendelian randomization (MR) approach to evaluate the effects of genetically predicted childhood adiposity on the risk of developing skin cancer later in life. Two-sample MR analyses were conducted using summary data from genome-wide association study (GWAS) meta-analyses of childhood BMI, melanoma, cutaneous squamous cell carcinoma (cSCC), and basal cell carcinoma (BCC). We used the inverse-variance-weighted (IVW) methods to obtain a pooled estimate across all genetic variants for childhood BMI. We performed multiple sensitivity analyses to evaluate the potential influence of various assumptions on our findings. We found no evidence that genetically predicted childhood BMI was associated with risks of developing melanoma, cSCC, or BCC in adulthood (OR, 95% CI: melanoma: 1.02 (0.93-1.13), cSCC 0.94 (0.79-1.11), BCC 0.97 (0.84-1.12)). Our findings do not support the conclusions from observational studies that childhood BMI is associated with increased risks of melanoma, cSCC, or BCC in adulthood. Intervening on childhood adiposity will not reduce the risk of common skin cancers later in life.

Genetic Analysis of Perceived Youthfulness Reveals Differences in How Men's and Women's Age Is Assessed.

Skin aging is a natural process that occurs over time but can be accelerated by sun exposure. Measuring skin age in a large population can provide insight into the extent of skin damage from sun exposure and skin cancer risk. Understanding the genetics of skin aging, within and across sexes (males and females), could improve our understanding of the genetic drivers of both skin aging and skin cancer. We used UK Biobank data to examine the genetic overlap between perceived youthfulness and traits relevant to actinic photoaging. Our GWAS identified 22 genome-wide significant loci for women and 43 for men. The genetic correlation (rg) between perceived youthfulness in men and women was significantly less than unity (rg = 0.75, 95% confidence interval = 0.69-0.80), suggesting a gene-by-sex interaction. In women, perceived youthfulness was modestly correlated with keratinocyte cancer (rg = -0.19) and skin tanning (rg = 0.18). In men, perceived youthfulness was correlated with male-pattern baldness (rg = -0.23). This suggests that the genetic architecture of perceived youthfulness may differ between sexes, with genes influencing skin tanning and skin cancer susceptibility driving the difference in women, whereas genes influencing male-pattern baldness and other puberty-related traits drive the difference in men. We recommend that future genetic analysis of skin aging include a sex-stratified component.

Uncovering the complex relationship between balding, testosterone and skin cancers in men.

Male-pattern baldness (MPB) is related to dysregulation of androgens such as testosterone. A previously observed relationship between MPB and skin cancer may be due to greater exposure to ultraviolet radiation or indicate a role for androgenic pathways in the pathogenesis of skin cancers. We dissected this relationship via Mendelian randomization (MR) analyses, using genetic data from recent male-only meta-analyses of cutaneous melanoma (12,232 cases; 20,566 controls) and keratinocyte cancers (KCs) (up to 17,512 cases; >100,000 controls), followed by stratified MR analysis by body-sites. We found strong associations between MPB and the risk of KC, but not with androgens, and multivariable models revealed that this relationship was heavily confounded by MPB single nucleotide polymorphisms involved in pigmentation pathways. Site-stratified MR analyses revealed strong associations between MPB with head and neck squamous cell carcinoma and melanoma, suggesting that sun exposure on the scalp, rather than androgens, is the main driver. Men with less hair covering likely explains, at least in part, the higher incidence of melanoma in men residing in countries with high ambient UV.

Genetic variants for smoking behaviour and risk of skin cancer.

Observational studies have suggested that smoking may increase the risk of cutaneous squamous cell carcinoma (cSCC) while decreasing the risks of basal cell carcinoma (BCC), and melanoma. However, it remains possible that confounding by other factors may explain these associations. The aim of this investigation was to use Mendelian randomization (MR) to test whether smoking is associated with skin cancer, independently of other factors. Two-sample MR analyses were conducted to determine the causal effect of smoking measures on skin cancer risk using genome-wide association study (GWAS) summary statistics. We used the inverse-variance-weighted estimator to derive separate risk estimates across genetic instruments for all smoking measures. A genetic predisposition to smoking initiation was associated with lower risks of all skin cancer types, although none of the effect estimates reached statistical significance (OR 95% CI BCC 0.91, 0.82-1.01; cSCC 0.82, 0.66-1.01; melanoma 0.91, 0.82-1.01). Results for other measures were similar to smoking initiation with the exception of smoking intensity which was associated with a significantly reduced risk of melanoma (OR 0.67, 95% CI 0.51-0.89). Our findings support the findings of observational studies linking smoking to lower risks of melanoma and BCC. However, we found no evidence that smoking is associated with an elevated risk of cSCC; indeed, our results are most consistent with a decreased risk, similar to BCC and melanoma.

Does genetic risk modify the effect of skin screening on melanoma detection rates?

BACKGROUND: Skin screening is associated with higher melanoma detection rates, a potential indicator of overdiagnosis, but it remains possible that this effect is due to confounding by genetic risk. OBJECTIVES: To compare melanoma incidence among screened vs. unscreened participants within tertiles of genetic risk. METHODS: We investigated melanoma incidence in the QSkin study, a prospective cohort study which for this analysis comprised 15 283 participants aged 40-69 years with genotype data and no prior history of melanoma. We calculated a polygenic score (PGS) for melanoma. We first calculated the age-standardized rate (ASR) of melanoma within PGS tertiles, and then measured the association between skin examination and melanoma detection by calculating the hazard ratio (HR) and 95% confidence interval (95% CI), overall and within PGS tertiles. RESULTS: Melanoma incidence increased with PGS (ASR per 100 000 per year): tertile 1 = 442; tertile 2 = 519; tertile 3 = 871. We found that the HRs for all melanomas (i.e. in situ and invasive) associated with skin examination differed slightly across PGS tertiles [age- and sex-adjusted tertile 1 HR 1.88 (95% CI 1.26-2.81); tertile 2 HR 1.70 (95% CI 1.20-2.41); tertile 3 HR 1.96 (95% CI 1.43-2.70); fully adjusted tertile 1 HR 1.14 (95% CI 0.74-1.75); tertile 2 HR 1.21 (95% CI 0.82-1.78); tertile 3 HR 1.41 (95% CI 1.00-1.98)], but these differences were not statistically significant. HRs for in situ melanoma associated with skin examination were similar across PGS tertiles. For invasive melanomas, the point estimates appeared to be highest in PGS tertile 3 in both the minimally adjusted (age, sex) and fully adjusted models; however, these apparent differences were also not statistically significant. CONCLUSIONS: Genetic risk predicts subsequent melanoma incidence, and is weakly associated with screening behaviour, but it does not explain the higher rate of melanoma detection between screened and unscreened people.

Study profile: the Genetics of Glaucoma Study.

PURPOSE: Glaucoma, a major cause of irreversible blindness, is a highly heritable human disease. Currently, the majority of the risk genes for glaucoma are unknown. We established the Genetics of Glaucoma Study (GOGS) to identify disease genes and improve genetic prediction of glaucoma risk and response to treatment. PARTICIPANTS: More than 5700 participants with glaucoma or a family history of glaucoma were recruited through a media campaign and the Australian Government healthcare service provider, Services Australia, making GOGS one of the largest genetic studies of glaucoma globally. The mean age of the participants was 65.30±9.36 years, and 62% were female. Participants completed a questionnaire obtaining information about their glaucoma-related medical history such as family history, glaucoma status and subtypes, surgical procedures, and prescriptions. The questionnaire also obtained information about other eye and systemic diseases. Approximately 80% of the participants provided a DNA sample and ~70% consented to data linkage to their Australian Government Medicare and Pharmaceutical Benefits Scheme schedules. FINDINGS TO DATE: 4336 GOGS participants reported that an optometrist or ophthalmologist has diagnosed them with glaucoma and 3639 participants reported having a family history of glaucoma. The vast majority of the participants (N=4393) had used at least one glaucoma-related medication; latanoprost was the most commonly prescribed drug (54% of the participants who had a glaucoma prescription). A subset of the participants reported a surgical treatment for glaucoma including a laser surgery in 2008 participants and a non-laser operation in 803 participants. Several comorbid eye and systemic diseases were also observed; the most common reports were ocular hypertension (53% of the participants), cataract (48%), hypertension (40%), nearsightedness (31%), astigmatism (22%), farsightedness (16%), diabetes (12%), sleep apnoea (11%) and migraines (10%). FUTURE PLANS: GOGS will contribute to the global gene-mapping efforts as one of the largest genetic studies for glaucoma. We will also use GOGS to develop or validate genetic risk prediction models to stratify glaucoma risk, particularly in individuals with a family history of glaucoma, and to predict clinical outcomes (eg, which medication works better for an individual and whether glaucoma surgery is required). GOGS will also help us answer various research questions about genetic overlap and causal relationships between glaucoma and its comorbidities.

The association between genetically elevated polyunsaturated fatty acids and risk of cancer.

BACKGROUND: The causal relevance of polyunsaturated fatty acids (PUFAs) for risk of site-specific cancers remains uncertain. METHODS: Using a Mendelian randomization (MR) framework, we assessed the causal relevance of PUFAs for risk of cancer in European and East Asian ancestry individuals. We defined the primary exposure as PUFA desaturase activity, proxied by rs174546 at the FADS locus. Secondary exposures were defined as omega 3 and omega 6 PUFAs that could be proxied by genetic polymorphisms outside the FADS region. Our study used summary genetic data on 10 PUFAs and 67 cancers, corresponding to 562,871 cases and 1,619,465 controls, collected by the Fatty Acids in Cancer Mendelian Randomization Collaboration. We estimated odds ratios (ORs) for cancer per standard deviation increase in genetically proxied PUFA exposures. FINDINGS: Genetically elevated PUFA desaturase activity was associated (P < 0.0007) with higher risk (OR [95% confidence interval]) of colorectal cancer (1.09 [1.07-1.11]), esophageal squamous cell carcinoma (1.16 [1.06-1.26]), lung cancer (1.06 [1.03-1.08]) and basal cell carcinoma (1.05 [1.02-1.07]). There was little evidence for associations with reproductive cancers (OR = 1.00 [95% CI: 0.99-1.01]; Pheterogeneity = 0.25), urinary system cancers (1.03 [0.99-1.06], Pheterogeneity = 0.51), nervous system cancers (0.99 [0.95-1.03], Pheterogeneity = 0.92) or blood cancers (1.01 [0.98-1.04], Pheterogeneity = 0.09). Findings for colorectal cancer and esophageal squamous cell carcinoma remained compatible with causality in sensitivity analyses for violations of assumptions. Secondary MR analyses highlighted higher omega 6 PUFAs (arachidonic acid, gamma-linolenic acid and dihomo-gamma-linolenic acid) as potential mediators. PUFA biosynthesis is known to interact with aspirin, which increases risk of bleeding and inflammatory bowel disease. In a phenome-wide MR study of non-neoplastic diseases, we found that genetic lowering of PUFA desaturase activity, mimicking a hypothetical intervention to reduce cancer risk, was associated (P < 0.0006) with increased risk of inflammatory bowel disease but not bleeding. INTERPRETATION: The PUFA biosynthesis pathway may be an intervention target for prevention of colorectal cancer and esophageal squamous cell carcinoma but with potential for increased risk of inflammatory bowel disease. FUNDING: Cancer Resesrch UK (C52724/A20138, C18281/A19169). UK Medical Research Council (MR/P014054/1). National Institute for Health Research (NIHR202411). UK Medical Research Council (MC_UU_00011/1, MC_UU_00011/3, MC_UU_00011/6, and MC_UU_00011/4). National Cancer Institute (R00 CA215360). National Institutes of Health (U01 CA164973, R01 CA60987, R01 CA72520, U01 CA74806, R01 CA55874, U01 CA164973 and U01 CA164973).

Genome-wide analyses characterize shared heritability among cancers and identify novel cancer susceptibility regions.

BACKGROUND: The shared inherited genetic contribution to risk of different cancers is not fully known. In this study, we leverage results from 12 cancer genome-wide association studies (GWAS) to quantify pairwise genome-wide genetic correlations across cancers and identify novel cancer susceptibility loci. METHODS: We collected GWAS summary statistics for 12 solid cancers based on 376 759 participants with cancer and 532 864 participants without cancer of European ancestry. The included cancer types were breast, colorectal, endometrial, esophageal, glioma, head and neck, lung, melanoma, ovarian, pancreatic, prostate, and renal cancers. We conducted cross-cancer GWAS and transcriptome-wide association studies to discover novel cancer susceptibility loci. Finally, we assessed the extent of variant-specific pleiotropy among cancers at known and newly identified cancer susceptibility loci. RESULTS: We observed widespread but modest genome-wide genetic correlations across cancers. In cross-cancer GWAS and transcriptome-wide association studies, we identified 15 novel cancer susceptibility loci. Additionally, we identified multiple variants at 77 distinct loci with strong evidence of being associated with at least 2 cancer types by testing for pleiotropy at known cancer susceptibility loci. CONCLUSIONS: Overall, these results suggest that some genetic risk variants are shared among cancers, though much of cancer heritability is cancer-specific and thus tissue-specific. The increase in statistical power associated with larger sample sizes in cross-disease analysis allows for the identification of novel susceptibility regions. Future studies incorporating data on multiple cancer types are likely to identify additional regions associated with the risk of multiple cancer types.

The genetic basis of endometriosis and comorbidity with other pain and inflammatory conditions.

Endometriosis is a common condition associated with debilitating pelvic pain and infertility. A genome-wide association study meta-analysis, including 60,674 cases and 701,926 controls of European and East Asian descent, identified 42 genome-wide significant loci comprising 49 distinct association signals. Effect sizes were largest for stage 3/4 disease, driven by ovarian endometriosis. Identified signals explained up to 5.01% of disease variance and regulated expression or methylation of genes in endometrium and blood, many of which were associated with pain perception/maintenance (SRP14/BMF, GDAP1, MLLT10, BSN and NGF). We observed significant genetic correlations between endometriosis and 11 pain conditions, including migraine, back and multisite chronic pain (MCP), as well as inflammatory conditions, including asthma and osteoarthritis. Multitrait genetic analyses identified substantial sharing of variants associated with endometriosis and MCP/migraine. Targeted investigations of genetically regulated mechanisms shared between endometriosis and other pain conditions are needed to aid the development of new treatments and facilitate early symptomatic intervention.

The MC1R r allele does not increase melanoma risk in MITF E318K carriers.

BACKGROUND: Population-wide screening for melanoma is not cost-effective, but genetic characterization could facilitate risk stratification and targeted screening. Common Melanocortin-1 receptor (MC1R) red hair colour (RHC) variants and Microphthalmia-associated transcription factor (MITF) E318K separately confer moderate melanoma susceptibility, but their interactive effects are relatively unexplored. OBJECTIVES: To evaluate whether MC1R genotypes differentially affect melanoma risk in MITF E318K+ vs. E318K- individuals. MATERIALS AND METHODS: Melanoma status (affected or unaffected) and genotype data (MC1R and MITF E318K) were collated from research cohorts (five Australian and two European). In addition, RHC genotypes from E318K+ individuals with and without melanoma were extracted from databases (The Cancer Genome Atlas and Medical Genome Research Bank, respectively). χ2 and logistic regression were used to evaluate RHC allele and genotype frequencies within E318K+/- cohorts depending on melanoma status. Replication analysis was conducted on 200 000 general-population exomes (UK Biobank). RESULTS: The cohort comprised 1165 MITF E318K- and 322 E318K+ individuals. In E318K- cases MC1R R and r alleles increased melanoma risk relative to wild type (wt), P < 0.001 for both. Similarly, each MC1R RHC genotype (R/R, R/r, R/wt, r/r and r/wt) increased melanoma risk relative to wt/wt (P < 0.001 for all). In E318K+ cases, R alleles increased melanoma risk relative to the wt allele [odds ratio (OR) 2.04 (95% confidence interval 1.67-2.49); P = 0.01], while the r allele risk was comparable with the wt allele [OR 0.78 (0.54-1.14) vs. 1.00, respectively]. E318K+ cases with the r/r genotype had a lower but not significant melanoma risk relative to wt/wt [OR 0.52 (0.20-1.38)]. Within the E318K+ cohort, R genotypes (R/R, R/r and R/wt) conferred a significantly higher risk compared with non-R genotypes (r/r, r/wt and wt/wt) (P < 0.001). UK Biobank data supported our findings that r did not increase melanoma risk in E318K+ individuals. CONCLUSIONS: RHC alleles/genotypes modify melanoma risk differently in MITF E318K- and E318K+ individuals. Specifically, although all RHC alleles increase risk relative to wt in E318K- individuals, only MC1R R increases melanoma risk in E318K+ individuals. Importantly, in the E318K+ cohort the MC1R r allele risk is comparable with wt. These findings could inform counselling and management for MITF E318K+ individuals.

Investigation of Shared Genetic Risk Factors Between Parkinson's Disease and Cancers.

BACKGROUND: Epidemiological studies that examined the association between Parkinson's disease (PD) and cancers led to inconsistent results, but they face a number of methodological difficulties. OBJECTIVE: We used results from genome-wide association studies (GWASs) to study the genetic correlation between PD and different cancers to identify common genetic risk factors. METHODS: We used individual data for participants of European ancestry from the Courage-PD (Comprehensive Unbiased Risk Factor Assessment for Genetics and Environment in Parkinson's Disease; PD, N = 16,519) and EPITHYR (differentiated thyroid cancer, N = 3527) consortia and summary statistics of GWASs from iPDGC (International Parkinson Disease Genomics Consortium; PD, N = 482,730), Melanoma Meta-Analysis Consortium (MMAC), Breast Cancer Association Consortium (breast cancer), the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (prostate cancer), International Lung Cancer Consortium (lung cancer), and Ovarian Cancer Association Consortium (ovarian cancer) (N comprised between 36,017 and 228,951 for cancer GWASs). We estimated the genetic correlation between PD and cancers using linkage disequilibrium score regression. We studied the association between PD and polymorphisms associated with cancers, and vice versa, using cross-phenotypes polygenic risk score (PRS) analyses. RESULTS: We confirmed a previously reported positive genetic correlation of PD with melanoma (Gcorr = 0.16 [0.04; 0.28]) and reported an additional significant positive correlation of PD with prostate cancer (Gcorr = 0.11 [0.03; 0.19]). There was a significant inverse association between the PRS for ovarian cancer and PD (odds ratio [OR] = 0.89 [0.84; 0.94]). Conversely, the PRS of PD was positively associated with breast cancer (OR = 1.08 [1.06; 1.10]) and inversely associated with ovarian cancer (OR = 0.95 [0.91; 0.99]). The association between PD and ovarian cancer was mostly driven by rs183211 located in an intron of the NSF gene (17q21.31). CONCLUSIONS: We show evidence in favor of a contribution of pleiotropic genes to the association between PD and specific cancers. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society. This article has been contributed to by U.S. Government employees and their work is in the public domain in the USA.

Risk Factors Associated With First and Second Primary Melanomas in a High-Incidence Population.

Importance: An increasing number of people develop more than 1 primary melanoma, yet to date, no population-based prospective cohort studies have reported on risk factors for developing first vs second primary melanomas. Objective: To compare the clinical characteristics of first and second melanomas and then to estimate the relative risks of developing 1 vs multiple melanomas associated with demographic, phenotypic, sun exposure, and genetic factors. Design, Setting, and Participants: This population-based prospective cohort study included men and women aged 40 to 69 years recruited in 2011 and followed up until December 2018 in Queensland, Australia. Data analysis was performed from February to July 2022. Exposures: Self-reported information about demographic, phenotypic, and sun exposure measures captured using a survey completed at baseline, and polygenic risk score for melanoma. Main Outcomes and Measures: Incident first or second primary melanoma diagnosis, and histologic and clinical characteristics thereof. The Wei-Lin-Weissfeld model for recurrent events was used to estimate the association of each factor with the risks of first and second primary melanoma. Results: A total of 38 845 patients (mean [SD] age at baseline, 56.1 [8.2] years; 17 775 men and 21 070 women) were included in the study. During a median follow-up period of 7.4 years, 1212 (3.1%) participants had a single primary melanoma diagnosis, and 245 (0.6%) had a second primary melanoma diagnosis. Second melanomas were more likely than first melanomas to be in situ; for invasive tumors, second melanomas were more likely to be thin (ie, ≤1 mm) than first melanomas. Having many moles at age 21 years (self-reported using visual scoring tool) was more strongly associated with second (hazard ratio [HR], 6.36; 95% CI, 3.77-10.75) than first primary melanoma (HR, 3.46; 95% CI, 2.72-4.40) (P value for difference between the HRs = .01). A high genetic predisposition (ie, polygenic risk score in tertile 3) was also more strongly associated with second (HR, 3.28; 95% CI, 2.06-5.23) than first melanoma (HR, 2.06; 95% CI, 1.71-2.49; P = .03). Second melanomas were more strongly associated with a history of multiple skin cancer excisions (HR, 2.63; 95% CI, 1.80-3.83) than first melanomas (HR, 1.86; 95% CI, 1.61-2.16; P = .05). For all other phenotypic characteristics and sun exposure measures, similarly elevated associations with first vs second melanomas were observed. Conclusions and Relevance: Findings of this cohort study suggest that within the general population, the presence of many nevi and having a high genetic predisposition to melanoma were associated with the highest risks of developing second primary melanomas.

Discovery of genomic loci associated with sleep apnea risk through multi-trait GWAS analysis with snoring.

STUDY OBJECTIVES: Despite its association with severe health conditions, the etiology of sleep apnea (SA) remains understudied. This study sought to identify genetic variants robustly associated with SA risk. METHODS: We performed a genome-wide association study (GWAS) meta-analysis of SA across five cohorts (NTotal = 523 366), followed by a multi-trait analysis of GWAS (multi-trait analysis of genome-wide association summary statistics [MTAG]) to boost power, leveraging the high genetic correlation between SA and snoring. We then adjusted our results for the genetic effects of body mass index (BMI) using multi-trait-based conditional and joint analysis (mtCOJO) and sought replication of lead hits in a large cohort of participants from 23andMe, Inc (NTotal = 1 477 352; Ncases = 175 522). We also explored genetic correlations with other complex traits and performed a phenome-wide screen for causally associated phenotypes using the latent causal variable method. RESULTS: Our SA meta-analysis identified five independent variants with evidence of association beyond genome-wide significance. After adjustment for BMI, only one genome-wide significant variant was identified. MTAG analyses uncovered 49 significant independent loci associated with SA risk. Twenty-nine variants were replicated in the 23andMe GWAS adjusting for BMI. We observed genetic correlations with several complex traits, including multisite chronic pain, diabetes, eye disorders, high blood pressure, osteoarthritis, chronic obstructive pulmonary disease, and BMI-associated conditions. CONCLUSION: Our study uncovered multiple genetic loci associated with SA risk, thus increasing our understanding of the etiology of this condition and its relationship with other complex traits.

Design and quality control of large-scale two-sample Mendelian randomization studies.

Background: Mendelian randomization (MR) studies are susceptible to metadata errors (e.g. incorrect specification of the effect allele column) and other analytical issues that can introduce substantial bias into analyses. We developed a quality control (QC) pipeline for the Fatty Acids in Cancer Mendelian Randomization Collaboration (FAMRC) that can be used to identify and correct for such errors. Methods: We collated summary association statistics from fatty acid and cancer genome-wide association studies (GWAS) and subjected the collated data to a comprehensive QC pipeline. We identified metadata errors through comparison of study-specific statistics to external reference data sets (the National Human Genome Research Institute-European Bioinformatics Institute GWAS catalogue and 1000 genome super populations) and other analytical issues through comparison of reported to expected genetic effect sizes. Comparisons were based on three sets of genetic variants: (i) GWAS hits for fatty acids, (ii) GWAS hits for cancer and (iii) a 1000 genomes reference set. Results: We collated summary data from 6 fatty acid and 54 cancer GWAS. Metadata errors and analytical issues with the potential to introduce substantial bias were identified in seven studies (11.6%). After resolving metadata errors and analytical issues, we created a data set of 219 842 genetic associations with 90 cancer types, generated in analyses of 566 665 cancer cases and 1 622 374 controls. Conclusions: In this large MR collaboration, 11.6% of included studies were affected by a substantial metadata error or analytical issue. By increasing the integrity of collated summary data prior to their analysis, our protocol can be used to increase the reliability of downstream MR analyses. Our pipeline is available to other researchers via the CheckSumStats package (https://github.com/MRCIEU/CheckSumStats).

A multi-phenotype analysis reveals 19 susceptibility loci for basal cell carcinoma and 15 for squamous cell carcinoma.

Basal cell carcinoma and squamous cell carcinoma are the most common skin cancers, and have genetic overlap with melanoma, pigmentation traits, autoimmune diseases, and blood biochemistry biomarkers. In this multi-trait genetic analysis of over 300,000 participants from Europe, Australia and the United States, we reveal 78 risk loci for basal cell carcinoma (19 previously unknown and replicated) and 69 for squamous cell carcinoma (15 previously unknown and replicated). The previously unknown risk loci are implicated in cancer development and progression (e.g. CDKL1), pigmentation (e.g. TPCN2), cardiometabolic (e.g. FADS2), and immune-regulatory pathways for innate immunity (e.g. IFIH1), and HIV-1 viral load modulation (e.g. CCR5). We also report an optimised polygenic risk score for effective risk stratification for keratinocyte cancer in the Canadian Longitudinal Study of Aging (794 cases and 18139 controls), which could facilitate skin cancer surveillance e.g. in high risk subpopulations such as transplantees.