Improved selection of participants in genetic longevity studies: family scores revisited

Background: Although human longevity tends to cluster within families, genetic studies on longevity have had limited success in identifying longevity loci. One of the main causes of this limited success is the selection of participants. Studies generally include sporadically long-lived individuals, i.e. individuals with the longevity phenotype but without a genetic predisposition for longevity. The inclusion of these individuals causes phenotype heterogeneity which results in power reduction and bias. A way to avoid sporadically long-lived individuals and reduce sample heterogeneity is to include family history of longevity as selection criterion using a longevity family score. A main challenge when developing family scores are the large differences in family size, because of real differences in sibship sizes or because of missing data.Methods: We discussed the statistical properties of two existing longevity family scores: the Family Longevity Selection Score (FLoSS) and the Longevity Relatives Count (LRC) score and we evaluated their performance dealing with differential family size. We proposed a new longevity family score, the mLRC score, an extension of the LRC based on random effects modeling, which is robust for family size and missing values. The performance of the new mLRC as selection tool was evaluated in an intensive simulation study and illustrated in a large real dataset, the Historical Sample of the Netherlands (HSN).Results: Empirical scores such as the FLOSS and LRC cannot properly deal with differential family size and missing data. Our simulation study showed that mLRC is not affected by family size and provides more accurate selections of long-lived families. The analysis of 1105 sibships of the Historical Sample of the Netherlands showed that the selection of long-lived individuals based on the mLRC score predicts excess survival in the validation set better than the selection based on the LRC score .Conclusions: Model-based score systems such as the mLRC score help to reduce heterogeneity in the selection of long-lived families. The power of future studies into the genetics of longevity can likely be improved and their bias reduced, by selecting long-lived cases using the mLRC.Development and application of statistical models for medical scientific researc

The AccelerAge framework: a new statistical approach to predict biological age based on time-to-event data

Aging is a multifaceted and intricate physiological process characterized by a gradual decline in functional capacity, leading to increased susceptibility to diseases and mortality. While chronological age serves as a strong risk factor for age-related health conditions, considerable heterogeneity exists in the aging trajectories of individuals, suggesting that biological age may provide a more nuanced understanding of the aging process. However, the concept of biological age lacks a clear operationalization, leading to the development of various biological age predictors without a solid statistical foundation. This paper addresses these limitations by proposing a comprehensive operationalization of biological age, introducing the “AccelerAge” framework for predicting biological age, and introducing previously underutilized evaluation measures for assessing the performance of biological age predictors. The AccelerAge framework, based on Accelerated Failure Time (AFT) models, directly models the effect of candidate predictors of aging on an individual’s survival time, aligning with the prevalent metaphor of aging as a clock. We compare predictors based on the AccelerAge framework to a predictor based on the GrimAge predictor, which is considered one of the best-performing biological age predictors, using simulated data as well as data from the UK Biobank and the Leiden Longevity Study. Our approach seeks to establish a robust statistical foundation for biological age clocks, enabling a more accurate and interpretable assessment of an individual’s aging status.Molecular Epidemiolog

Randomized Trial of Ciclosporin with 2-h Monitoring vs. Tacrolimus with Trough Monitoring in Liver Transplantation:DELTA Study

Background and Aims: Previous trials comparing cyclosporine and tacrolimus after liver transplantation (LT) showed conflicting results. Most used trough monitoring for cyclosporine (C0), leading to less accurate dosing than with 2-h monitoring (C2). Only one larger trial compared C2 with tacrolimus based on trough level (T0) after LT, with similar treated biopsy-proven acute rejection (tBPAR) and graft loss, while a smaller trial had less tBPAR with C2 compared to T0. Therefore, it is still unclear which calcineurin inhibitor is preferred after LT. We aimed to demonstrate superior efficacy (tBPAR), tolerability, and safety of C2 or T0 after first LT. Methods: Patients after first LT were randomized to C2 or T0. tBPAR, patient-and graft survival, safety and tolerability were the main endpoints, with analysis by Fisher test, Kaplan–Meier survival analysis and log-rank test. Results: In intention-to treat analysis 84 patients on C2 and 85 on T0 were included. Cumulative incidence of tBPAR C2 vs. T0 was 17.7% vs. 8.4% at 3 months (p=0.104), and 21.9% vs. 9.7% at 6 and 12 months (p=0.049). One-year cumulative mortality C2 vs. T0 was 15.5% vs. 5.9% (p=0.049) and graft loss 23.8% vs. 9.4% (p=0.015). Serum triglyceride and LDL-cholesterol was lower with T0 than with C2. Incidence of diarrhea in T0 vs, C2 was 64% vs. 31% (p≤0.001), with no other differences in safety and tolerability. Conclusions: In the first year after LT immunosuppression with T0 leads to less tBPAR and better patient-/re-transplant-free survival as compared to C2.</p

Structured alcohol cessation support program versus current practice in acute alcoholic pancreatitis (PANDA):Study protocol for a multicentre cluster randomised controlled trial

Background/objectives: The most important risk factor for recurrent pancreatitis after an episode of acute alcoholic pancreatitis is continuation of alcohol use. Current guidelines do not recommend any specific treatment strategy regarding alcohol cessation. The PANDA trial investigates whether implementation of a structured alcohol cessation support program prevents pancreatitis recurrence after a first episode of acute alcoholic pancreatitis. Methods: PANDA is a nationwide cluster randomised superiority trial. Participating hospitals are randomised for the investigational management, consisting of a structured alcohol cessation support program, or current practice. Patients with a first episode of acute pancreatitis caused by harmful drinking (AUDIT score &gt;7 and &lt; 16 for men and &gt;6 and &lt; 14 for women) will be included. The primary endpoint is recurrence of acute pancreatitis. Secondary endpoints include cessation or reduction of alcohol use, other alcohol-related diseases, mortality, quality of life, quality-adjusted life years (QALYs) and costs. The follow-up period comprises one year after inclusion. Discussion: This is the first multicentre trial with a cluster randomised trial design to investigate whether a structured alcohol cessation support program reduces recurrent acute pancreatitis in patients after a first episode of acute alcoholic pancreatitis, as compared with current practice. Trial registration: Netherlands Trial Registry (NL8852). Prospectively registered.</p

Drawing quantum contextuality with 'dessins d'enfants'

The Frontiers Collection: "It from Bit orBit from It", ed. by A. Aguirre, B. Foster, Z. Meralli (Springer, 2014), pp 37-50International audienceIn the standard formulation of quantum mechanics, there exists an inherent feedback of the measurement setting on the elementary object under scrutiny. Thus one cannot assume that an 'element of reality' prexists to the measurement and, it is even more intriguing that unperformed/counterfactual observables enter the game. This is called quantum contextuality. Simple finite projective geometries are a good way to picture the commutation relations of quantum observables entering the context, at least for systems with two or three parties. In the essay, it is further discovered a mathematical mechanism for 'drawing' the contexts. The so-called 'dessins d'enfants' of the celebrated mathematician Alexandre Grothendieck feature group, graph, topological, geometric and algebraic properties of the quantum contexts that would otherwise have been 'hidden' in the apparent randomness of measurement outcomes

Effects of Family History on Relative and Absolute Risks for Colorectal Cancer: A Systematic Review and Meta-Analysis

Analysis and support of clinical decision makin

Genotype-phenotype correlations for pancreatic cancer risk in Dutch melanoma families with pathogenic CDKN2A variants

BACKGROUND: Pathogenic variants in the CDKN2A gene are generally associated with the development of melanoma and pancreatic ductal adenocarcinoma (PDAC), but specific genotype-phenotype correlations might exist and the extent of PDAC risk is not well established for many variants. METHODS: Using the Dutch national familial melanoma database, we identified all families with a pathogenic CDKN2A variant and investigated the occurrence of PDAC within these families. We also estimated the standardised incidence ratio and lifetime PDAC risk for carriers of a highly prevalent variant in these families. RESULTS: We identified 172 families in which 649 individuals carried 15 different pathogenic variants. The most prevalent variant was the founder mutation c.225_243del (p16-Leiden, 484 proven carriers). Second most prevalent was c.67G>C (55 proven carriers). PDAC developed in 95 of 163 families (58%, including 373 of 629 proven carriers) harbouring a variant with an effect on the p16INK4a protein, whereas PDAC did not occur in the 9 families (20 proven carriers) with a variant affecting only p14ARF. In the c.67G>C families, PDAC occurred in 12 of the 251 (5%) persons at risk. The standardised incidence ratio was 19.1 (95% CI 8.3 to 33.6) and the cumulative PDAC incidence at age 75 years (lifetime risk) was 19% (95% CI 7.5% to 30.1%). CONCLUSIONS: Our results support the notion that pathogenic CDKN2A variants affecting the p16INK4a protein, including c.67G>C, are associated with increased PDAC risk and carriers of such variants should be offered pancreatic cancer surveillance. There is no clinical evidence that impairment of only the p14ARF protein leads to an increased PDAC risk

Intergenerational transmission of longevity is not affected by other familial factors: evidence from 16,905 Dutch families from Zeeland, 1812-1962

Studies have shown that long-lived individuals seem to pass their survival advantage on to their offspring. Offspring of long-lived parents had a lifelong survival advantage over individuals without long-lived parents, making them more likely to become long-lived themselves. We test whether the survival advantage enjoyed by offspring of long-lived individuals is explained by environmental factors. 101,577 individuals from 16,905 families in the 1812–1886 Zeeland cohort were followed over time. To prevent that certain families were overrepresented in our data, disjoint family trees were selected. Offspring was included if the age at death of both parents was known. Our analyses show that multiple familial resources are associated with survival within the first 5 years of life, with stronger maternal than paternal effects. However, between ages 5 and 100 both parents contribute equally to offspring’s survival chances. After age 5, offspring of long-lived fathers and long-lived mothers had a 16-19% lower chance of dying at any given point in time than individuals without long-lived parents. This survival advantage is most likely genetic in nature, as it could not be explained by other, tested familial resources and is transmitted equally by fathers and mothers

Performance of BRCA1/2 mutation prediction models in male breast cancer patients

To establish whether existing mutation prediction models can identify which male breast cancer (MBC) patients should be offered BRCA1 and BRCA2 diagnostic DNA screening, we compared the performance of BOADICEA (Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm), BRCAPRO (BRCA probability) and the Myriad prevalence table ("Myriad"). These models were evaluated using the family data of 307 Dutch MBC probands tested for BRCA1/2, 58 (19%) of whom were carriers. We compared the numbers of observed vs predicted carriers and assessed the Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) for each model. BOADICEA predicted the total number of BRCA1/2 mutation carriers quite accurately (observed/predicted ratio: 0.94). When a cut-off of 10% and 20% prior probability was used, BRCAPRO showed a non-significant better performance (observed/predicted ratio BOADICEA: 0.81, 95% confidence interval [CI]: [0.60-1.09] and 0.79, 95% CI: [0.57-1.09], vs. BRCAPRO: 1.02, 95% CI: [0.75-1.38] and 0.94, 95% CI: [0.68-1.31], respectively). Myriad underestimated the number of carriers in up to 69% of the cases. BRCAPRO showed a non-significant, higher AUC than BOADICEA (0.798 vs 0.776). Myriad showed a significantly lower AUC (0.671). BRCAPRO and BOADICEA can efficiently identify MBC patients as BRCA1/2 mutation carriers. Besides their general applicability, these tools will be of particular value in countries with limited healthcare resources