A Flexible Bayesian Model for Studying Gene–Environment Interaction

An important follow-up step after genetic markers are found to be associated with a disease outcome is a more detailed analysis investigating how the implicated gene or chromosomal region and an established environment risk factor interact to influence the disease risk. The standard approach to this study of gene–environment interaction considers one genetic marker at a time and therefore could misrepresent and underestimate the genetic contribution to the joint effect when one or more functional loci, some of which might not be genotyped, exist in the region and interact with the environment risk factor in a complex way. We develop a more global approach based on a Bayesian model that uses a latent genetic profile variable to capture all of the genetic variation in the entire targeted region and allows the environment effect to vary across different genetic profile categories. We also propose a resampling-based test derived from the developed Bayesian model for the detection of gene–environment interaction. Using data collected in the Environment and Genetics in Lung Cancer Etiology (EAGLE) study, we apply the Bayesian model to evaluate the joint effect of smoking intensity and genetic variants in the 15q25.1 region, which contains a cluster of nicotinic acetylcholine receptor genes and has been shown to be associated with both lung cancer and smoking behavior. We find evidence for gene–environment interaction (P-value = 0.016), with the smoking effect appearing to be stronger in subjects with a genetic profile associated with a higher lung cancer risk; the conventional test of gene–environment interaction based on the single-marker approach is far from significant

mSigSDK -- private, at scale, computation of mutation signatures

In our previous work, we demonstrated that it is feasible to perform analysis on mutation signature data without the need for downloads or installations and analyze individual patient data at scale without compromising privacy. Building on this foundation, we developed a Software Development Kit (SDK) called mSigSDK to facilitate the orchestration of distributed data processing workflows and graphic visualization of mutational signature analysis results. We strictly adhered to modern web computing standards, particularly the modularization standards set by the ECMAScript ES6 framework (JavaScript modules). Our approach allows for computation to be entirely performed by secure delegation to the computational resources of the user's own machine (in-browser), without any downloads or installations. The mSigSDK was developed primarily as a companion library to the mSig Portal resource of the National Cancer Institute Division of Cancer Epidemiology and Genetics (NIH/NCI/DCEG), with a focus on its FAIR extensibility as components of other researchers' computational constructs. Anticipated extensions include the programmatic operation of other mutation signature API ecosystems such as SIGNAL and COSMIC, advancing towards a data commons for mutational signature research (Grossman et al., 2016)

A regression model for risk difference estimation in population-based case-control studies clarifies gender differences in lung cancer risk of smokers and never smokers

BACKGROUND: Additive risk models are necessary for understanding the joint effects of exposures on individual and population disease risk. Yet technical challenges have limited the consideration of additive risk models in case-control studies. METHODS: Using a flexible risk regression model that allows additive and multiplicative components to estimate absolute risks and risk differences, we report a new analysis of data from the population-based case-control Environment And Genetics in Lung cancer Etiology study, conducted in Northern Italy between 2002-2005. The analysis provides estimates of the gender-specific absolute risk (cumulative risk) for non-smoking- and smoking-associated lung cancer, adjusted for demographic, occupational, and smoking history variables. RESULTS: In the multiple-variable lexpit regression, the adjusted 3-year absolute risk of lung cancer in never smokers was 4.6 per 100,000 persons higher in women than men. However, the absolute increase in 3-year risk of lung cancer for every 10 additional pack-years smoked was less for women than men, 13.6 versus 52.9 per 100,000 persons. CONCLUSIONS: In a Northern Italian population, the absolute risk of lung cancer among never smokers is higher in women than men but among smokers is lower in women than men. Lexpit regression is a novel approach to additive-multiplicative risk modeling that can contribute to clearer interpretation of population-based case-control studies

Lung Cancer and Occupation in a Population-based Case-Control Study

The authors examined the relation between occupation and lung cancer in the large, population-based Environment And Genetics in Lung cancer Etiology (EAGLE) case-control study. In 2002–2005 in the Lombardy region of northern Italy, 2,100 incident lung cancer cases and 2,120 randomly selected population controls were enrolled. Lifetime occupational histories (industry and job title) were coded by using standard international classifications and were translated into occupations known (list A) or suspected (list B) to be associated with lung cancer. Smoking-adjusted odds ratios and 95% confidence intervals were calculated with logistic regression. For men, an increased risk was found for list A (177 exposed cases and 100 controls; odds ratio = 1.74, 95% confidence interval: 1.27, 2.38) and most occupations therein. No overall excess was found for list B with the exception of filling station attendants and bus and truck drivers (men) and launderers and dry cleaners (women). The authors estimated that 4.9% (95% confidence interval: 2.0, 7.8) of lung cancers in men were attributable to occupation. Among those in other occupations, risk excesses were found for metal workers, barbers and hairdressers, and other motor vehicle drivers. These results indicate that past exposure to occupational carcinogens remains an important determinant of lung cancer occurrence

Prevalence and clinical implications of abnormal body composition phenotypes in patients with COVID-19: a systematic review

Background: The impact of body composition (BC) abnormalities on COVID-19 outcomes remains to be determined.Objectives: We summarized the evidence on BC abnormalities and their relationship with adverse clinical outcomes in patients with COVID-19.Methods: A systematic search was conducted up until 26 September, 2022 for observational studies using BC techniques to quantify skeletal muscle mass (or related compartments), muscle radiodensity or echo intensity, adipose tissue (AT; or related compartments), and phase angle (PhA) in adults with COVID-19. Methodological quality of studies was assessed using the Newcastle-Ottawa Scale. A synthesis without meta-analysis was conducted to summarize the prevalence of BC abnormalities and their significant associations with clinical outcomes.Results: We included 62 studies (69.4% low risk of bias) with 12-1138 participants, except 3 studies with <490,301 participants. Using CT and different cutoff values, prevalence ranged approximately from 22% to 90% for low muscle mass, 12% to 85% for low muscle radiodensity, and 16% to 70% for high visceral AT. Using BIA, prevalence of high FM was 51%, and low PhA was 22% to 88%. Mortality was inversely related to PhA (3/4 studies) and positively related to intra-and intermuscular AT (4/5 studies), muscle echo intensity (2/2 studies), and BIA-estimated FM (2/2 studies). Intensive care unit (ICU) admission was positively related to visceral AT (6/7 studies) and total AT (2/3 studies). Disease severity and hospitalization outcomes were positively related to intra-and intermuscular AT (2/2 studies). Inconsistent associations were found for the rest of the BC measures and hospitalization outcomes.Conclusions: Abnormalities in BC were prevalent in patients with COVID-19. Although conflicting associations were observed among certain BC abnormalities and clinical outcomes, higher muscle echo intensity (reflective of myosteatosis) and lower PhA were more consistently associated with greater mortality risk. Likewise, high intra-and intermuscular AT and visceral AT were associated with mortality and ICU admission, respectively. This trial was registered at PROSPERO as CRD42021283031

Contribution of Common Genetic Variants to Familial Aggregation of Disease and Implications for Sequencing Studies

Despite genetics being accepted as the primary cause of familial aggregation for most diseases, it is still unclear whether afflicted families are likely to share a single highly penetrant rare variant, many minimally penetrant common variants, or a combination of the two types of variants. We therefore use recent estimates of SNP heritability and the liability threshold model to estimate the proportion of afflicted families likely to carry a rare, causal variant. We then show that Polygenic Risk Scores (PRS) may be useful for identifying families likely to carry such a rare variant and therefore for prioritizing families to include in sequencing studies with that aim. Specifically, we introduce a new statistic that estimates the proportion of individuals carrying causal rare variants based on the family structure, disease pattern, and PRS of genotyped individuals. Finally, we consider data from the MelaNostrum consortium and show that, despite an estimated PRS heritability of only 0.05 for melanoma, families carrying putative causal variants had a statistically significantly lower PRS, supporting the idea that PRS prioritization may be a useful future tool. However, it will be important to evaluate whether the presence of rare mendelian variants are generally associated with the proposed test statistic or lower PRS in future and larger studies

Contribution of Common Genetic Variants to Familial Aggregation of Disease and Implications for Sequencing Studies

Despite genetics being accepted as the primary cause of familial aggregation for most diseases, it is still unclear whether afflicted families are likely to share a single highly penetrant rare variant, many minimally penetrant common variants, or a combination of the two types of variants. We therefore use recent estimates of SNP heritability and the liability threshold model to estimate the proportion of afflicted families likely to carry a rare, causal variant. We then show that Polygenic Risk Scores (PRS) may be useful for identifying families likely to carry such a rare variant and therefore for prioritizing families to include in sequencing studies with that aim. Specifically, we introduce a new statistic that estimates the proportion of individuals carrying causal rare variants based on the family structure, disease pattern, and PRS of genotyped individuals. Finally, we consider data from the MelaNostrum consortium and show that, despite an estimated PRS heritability of only 0.05 for melanoma, families carrying putative causal variants had a statistically significantly lower PRS, supporting the idea that PRS prioritization may be a useful future tool. However, it will be important to evaluate whether the presence of rare mendelian variants are generally associated with the proposed test statistic or lower PRS in future and larger studies

Mapping clustered mutations in cancer reveals APOBEC3 mutagenesis of ecDNA

Clustered somatic mutations are common in cancer genomes and previous analyses reveal several types of clustered single-base substitutions, which include doublet- and multi-base substitutions1–5, diffuse hypermutation termed omikli6, and longer strand-coordinated events termed kataegis3,7–9. Here we provide a comprehensive characterization of clustered substitutions and clustered small insertions and deletions (indels) across 2,583 whole-genome-sequenced cancers from 30 types of cancer10. Clustered mutations were highly enriched in driver genes and associated with differential gene expression and changes in overall survival. Several distinct mutational processes gave rise to clustered indels, including signatures that were enriched in tobacco smokers and homologous-recombination-deficient cancers. Doublet-base substitutions were caused by at least 12 mutational processes, whereas most multi-base substitutions were generated by either tobacco smoking or exposure to ultraviolet light. Omikli events, which have previously been attributed to APOBEC3 activity6, accounted for a large proportion of clustered substitutions; however, only 16.2% of omikli matched APOBEC3 patterns. Kataegis was generated by multiple mutational processes, and 76.1% of all kataegic events exhibited mutational patterns that are associated with the activation-induced deaminase (AID) and APOBEC3 family of deaminases. Co-occurrence of APOBEC3 kataegis and extrachromosomal DNA (ecDNA), termed kyklonas (Greek for cyclone), was found in 31% of samples with ecDNA. Multiple distinct kyklonic events were observed on most mutated ecDNA. ecDNA containing known cancer genes exhibited both positive selection and kyklonic hypermutation. Our results reveal the diversity of clustered mutational processes in human cancer and the role of APOBEC3 in recurrently mutating and fuelling the evolution of ecDNA

NEDA-3 achievement in early highly active relapsing remitting multiple sclerosis patients treated with Ocrelizumab or Natalizumab

background: in the early stages of multiple sclerosis (MS), initiating high-efficacy disease-modifying therapy (HE DMTs) may represent an optimal strategy for delaying neurological damage and long-term disease progression, especially in highly active MS patients (HAMS). natalizumab (NAT) and Ocrelizumab (OCR) are recognized as HE DMTs with significant anti-inflammatory effects. this study investigates NEDA-3 achievement in treatment-naïve HAMS patients receiving NAT or OCR over three years. methods: we retrospectively enrolled treatment-naïve HAMS patients undergoing NAT or OCR, collecting demographic, clinical, and instrumental data before and after treatment initiation to compare with propensity score analysis disease activity, time to disability worsening, and NEDA-3 achievement. results: we recruited 281 HAMS patients with a mean age of 32.7 years (SD 10.33), treated with NAT (157) or OCR (124). after three years, the kaplan-meier probability of achieving NEDA-3 was 66.0 % (95 % CI: 57.3 % - 76.0 %) with OCR and 68.2 % (95 % CI: 59.9 % - 77.7 %) with NAT without significant differences between the two groups (p = 0.27) DISCUSSION AND CONCLUSION: starting HE DMT with monoclonal antibodies for HAMS could achieve NEDA-3 in a high percentage of patients without differences between NAT or OCR