Multiplex melanoma families are enriched for polygenic risk

Polygenic Risk in Families With Spontaneous Coronary Artery Dissection

Importance

Spontaneous coronary artery dissection (SCAD) is a poorly understood cause of acute coronary syndrome that predominantly affects women. Evidence to date suggests a complex genetic architecture, while a family history is reported for a minority of cases.

Objective

To determine the contribution of rare and common genetic variants to SCAD risk in familial cases, the latter via the comparison of a polygenic risk score (PRS) with those with sporadic SCAD and healthy controls.

Design, Setting, and Participants

This genetic association study analyzed families with SCAD, individuals with sporadic SCAD, and healthy controls. Genotyping was undertaken for all participants. Participants were recruited between 2017 and 2021. A PRS for SCAD was calculated for all participants. The presence of rare variants in genes associated with connective tissue disorders (CTD) was also assessed. Individuals with SCAD were recruited via social media or from a single medical center. A previously published control database of older healthy individuals was used. Data were analyzed from January 2022 to October 2023.

Exposures

PRS for SCAD comprised of 7 single-nucleotide variants.

Main Outcomes and Measures

Disease status (familial SCAD, sporadic SCAD, or healthy control) associated with PRS.

Results

A total of 13 families with SCAD (27 affected and 12 unaffected individuals), 173 individuals with sporadic SCAD, and 1127 healthy controls were included. A total of 188 individuals with SCAD (94.0%) were female, including 25 of 27 with familial SCAD and 163 of 173 with sporadic SCAD; of 12 unaffected individuals from families with SCAD, 6 (50%) were female; and of 1127 healthy controls, 672 (59.6%) were female. Compared with healthy controls, the odds of being an affected family member or having sporadic SCAD was significantly associated with a SCAD PRS (where the odds ratio [OR] represents an increase in odds per 1-SD increase in PRS) (affected family member: OR, 2.14; 95% CI, 1.78-2.50; adjusted P = 1.96 × 10-4; sporadic SCAD: OR, 1.63; 95% CI, 1.37-1.89; adjusted P = 5.69 × 10-4). This association was not seen for unaffected family members (OR, 1.03; 95% CI, 0.46-1.61; adjusted P = .91) compared with controls. Further, those with familial SCAD were overrepresented in the top quintile of the control PRS distribution (OR, 3.70; 95% CI, 2.93-4.47; adjusted P = .001); those with sporadic SCAD showed a similar pattern (OR, 2.51; 95% CI, 1.98-3.04; adjusted P = .001). Affected individuals within a family did not share any rare deleterious variants in CTD-associated genes.

Conclusions and Relevance

Extreme aggregation of common genetic risk appears to play a significant role in familial clustering of SCAD as well as in sporadic case predisposition, although further study is required.

Independent evaluation of melanoma polygenic risk scores in UK and Australian prospective cohorts

BACKGROUND

Previous studies suggest that polygenic risk scores (PRSs) may improve melanoma risk stratification. However, there has been limited independent validation of PRS-based risk prediction, particularly assessment of calibration (comparing predicted to observed risks).

OBJECTIVES

To evaluate PRS-based melanoma risk prediction in prospective UK and Australian cohorts with European ancestry.

METHODS

We analysed invasive melanoma incidence in the UK Biobank (UKB; n = 395 647, 1651 cases) and a case-cohort nested within the Melbourne Collaborative Cohort Study (MCCS, Australia; n = 4765, 303 cases). Three PRSs were evaluated: 68 single-nucleotide polymorphisms (SNPs) at 54 loci from a 2020 meta-analysis (PRS68), 50 SNPs significant in the 2020 meta-analysis excluding UKB (PRS50) and 45 SNPs at 21 loci known in 2018 (PRS45). Ten-year melanoma risks were calculated from population-level cancer registry data by age group and sex, with and without PRS adjustment.

RESULTS

Predicted absolute melanoma risks based on age and sex alone underestimated melanoma incidence in the UKB [ratio of expected/observed cases: E/O = 0·65, 95% confidence interval (CI) 0·62-0·68] and MCCS (E/O = 0·63, 95% CI 0·56-0·72). For UKB, calibration was improved by PRS adjustment, with PRS50-adjusted risks E/O = 0·91, 95% CI 0·87-0·95. The discriminative ability for PRS68- and PRS50-adjusted absolute risks was higher than for risks based on age and sex alone (Δ area under the curve 0·07-0·10, P < 0·0001), and higher than for PRS45-adjusted risks (Δ area under the curve 0·02-0·04, P < 0·001).

CONCLUSIONS

A PRS derived from a larger, more diverse meta-analysis improves risk prediction compared with an earlier PRS, and might help tailor melanoma prevention and early detection strategies to different risk levels. Recalibration of absolute risks may be necessary for application to specific populations.

Melanoma susceptibility: an update on genetic and epigenetic findings

Malignant melanoma is one of the most highly ranked cancers in terms of years of life lost. Hereditary melanoma with its increased familial susceptibility is thought to affect up to 12% of all melanoma patients. In the past, only a few high-penetrance genes associated with familial melanoma, such as CDKN2A and CDK4, have been clinically tested. However, findings now indicate that melanoma is a cancer most likely to develop not only due to high-penetrance variants but also due to polygenic inheritance patterns, leaving no clear division between the hereditary and sporadic development of malignant melanoma. Various pathogenic low-penetrance variants were recently discovered through genome-wide association studies, and are now translated into polygenic risk scores. These can show superior sensitivity rates for the prediction of melanoma susceptibility and related mixed cancer syndromes than risk scores based on phenotypic traits of the patients, with odds ratios of up to 5.7 for patients in risk groups. In addition to describing genetic findings, we also review the first results of epigenetic research showing constitutional methylation changes that alter the susceptibility to cutaneous melanoma and its risk factors.

The Interplay between Nevi and Melanoma Predisposition Unravels Nevi-Related and Nevi-Resistant Familial Melanoma

Genetic susceptibility to nevi may affect the risk of developing melanoma, since common and atypical nevi are the main host risk factors implicated in the development of cutaneous melanoma. Recent genome-wide studies defined a melanoma polygenic risk score based on variants in genes involved in different pathways, including nevogenesis. Moreover, a predisposition to nevi is a hereditary trait that may account for melanoma clustering in some families characterized by cases with a high nevi density. On the other hand, familial melanoma aggregation may be due to a Mendelian inheritance of high/moderate-penetrance pathogenic variants affecting melanoma risk, regardless of the nevus count. Based on current knowledge, this review analyzes the complex interplay between nevi and melanoma predisposition in a familial context. We review familial melanoma, starting from Whiteman's divergent pathway model to overall melanoma development, distinguishing between nevi-related (cases with a high nevus count and a high polygenic risk score) and nevi-resistant (high/moderate-penetrance variant-carrier cases) familial melanoma. This distinction could better direct future research on genetic factors useful to identify high-risk subjects.

On Naevi and Melanomas: Two Sides of the Same Coin?

Benign naevi are closely linked to melanoma, as risk factors, simulators, or sites of melanoma formation. There is a heavy genetic overlap between the two lesions, a shared environmental influence of ultraviolet radiation, and many similar cellular features, yet naevi remain locally situated while melanomas spread from their primary site and may progress systemically to distal organs. Untangling the overlapping contributors and predictors of naevi and melanoma is an ongoing area of research and should eventually lead to more personalized prevention and treatment strategies, through the development of melanoma risk stratification tools and early detection of evolving melanomas. This will be achieved through a range of complementary strategies: risk-adjusted primary prevention counseling; the use of lesion imaging technologies such as sequential 3D total body photography and consumer-performed lesion imaging; artificial intelligence deep phenotyping and clinical assistance; a better understanding of genetic drivers of malignancy, risk variants, clinical genetics, and polygenic effects; and the interplay between genetics, phenotype and the environment.