Likelihood ratio and posterior odds in forensic genetics: Two sides of the same coin

It has become widely accepted in forensics that, owing to a lack of sensible priors, the evidential value of matching DNA profiles in trace donor identification or kinship analysis is most sensibly communicated in the form of a likelihood ratio (LR). This restraint does not abate the fact that the posterior odds (PO) would be the preferred basis for returning a verdict. A completely different situation holds for Forensic DNA Phenotyping (FDP), which is aimed at predicting externally visible characteristics (EVCs) of a trace donor from DNA left behind at the crime scene. FDP is intended to provide leads to the police investigation helping them to find unknown trace donors that are unidentifiable by DNA profiling. The statistical models underlying FDP typically yield posterior odds (PO) for an individual possessing a certain EVC. This apparent discrepancy has led to confusion as to when LR or PO is the appropriate outcome of forensic DNA analysis to be communicated to the investigating authorities. We thus set out to clarify the distinction between LR and PO in the context of forensic DNA profiling and FDP from a statistical point of view. In so doing, we also addressed the influence of population affiliation on LR and PO. In contrast to the well-known population dependency of the LR in DNA profiling, the PO as obtained in FDP may be widely population-independent. The actual degree of independence, however, is a matter of (i) how much of the causality of the respective EVC is captured by the genetic markers used for FDP and (ii) by the extent to which non-genetic such as environmental causal factors of the same EVC are distributed equally throughout populations. The fact that an LR should be communicated in cases of DNA profiling whereas the PO are suitable for FDP does not conflict with theory, but rather reflects the immanent differences between these two forensic applications of DNA information

IMHOTEP A composite score integrating popular tools for predicting the functional consequences of non-synonymous sequence variants

The in silico prediction of the functional consequences of mutations is an important goal of human pathogenetics. However, bioinformatic tools that classify mutations according to their functionality employ different algorithms so that predictions may vary markedly between tools. We therefore integrated nine popular prediction tools (PolyPhen-2, SNPs&GO, MutPred, SIFT, MutationTaster2, Mutation Assessor and FATHMM as well as conservation-based Grantham Score and PhyloP) into a single predictor. The optimal combination of these tools was selected by means of a wide range of statistical modeling techniques, drawing upon 10 029 disease-causing single nucleotide variants (SNVs) from Human Gene Mutation Database and 10 002 putatively ‘benign’ non-synonymous SNVs from UCSC. Predictive performance was found to be markedly improved by model-based integration, whilst maximum predictive capability was obtained with either random forest, decision tree or logistic regression analysis. A combination of PolyPhen-2, SNPs&GO, MutPred, MutationTaster2 and FATHMM was found to perform as well as all tools combined. Comparison of our approach with other integrative approaches such as Condel, CoVEC, CAROL, CADD, MetaSVM and MetaLR using an independent validation dataset, revealed the superiority of our newly proposed integrative approach. An online implementation of this approach, IMHOTEP (‘Integrating Molecular Heuristics and Other Tools for Effect Prediction’), is provided at http://www.uni-kiel.de/medinfo/cgi-bin/predictor/

Pre- and intratherapeutic predictors of overall survival in patients with advanced metastasized castration-resistant prostate cancer receiving Lu-177-PSMA-617 radioligand therapy

Background Systemic Lutetium-177 prostate-specific membrane antigen-617 radioligand therapy (Lu-177-PSMA-617-RLT) is a novel treatment approach in patients suffering from metastasized castration-resistant prostate cancer. Nonetheless, a therapeutic response may fail to appear in a proportion of patients. This study aims to identify routinely obtainable pre- and intratherapeutic parameters to allow a prediction of overall survival in patients receiving Lu-177-PSMA-617 radioligand therapy. Methods Between January 2015 and December 2020 52 patients treated with a total of 146 cycles Lu-177-PSMA-617-RLT were retrospectively analysed in a single-center trial. The median overall survival time (OS) was compared to pre-therapeutic serological parameters, the extend of metastatic spread and previously performed therapies using Kaplan-Meier estimators and multivariate Cox-regression. Bonferroni-Holm correction was performed on all statistical tests. Results The median OS of all patients was 55.6 weeks. Multivariate Cox-regression revealed significant lower survival for decreased pretherapeutic hemoglobin levels (HR 0.698 per g/dl; 95%-CI 0.560-0.872; p = 0.001), increased lactate dehydrogenase (LDH) levels (HR 1.073 per 25 U/l; 95%-CI 1.024-1.125; p = 0.003) and the presence of hepatic metastasis (HR 6.981; 95%-CI 2.583-18.863; p < 0.001). Increased pretherapeutic c-reactive protein (CRP), alkaline phosphatase (ALP) and gamma-glutamyltransferase (GGT) levels were also associated with a shorter survival. Conclusion Pre-therapeutic hemoglobin and LDH levels, as well as the presence of hepatic metastasis are independent predictors of overall survival in patients receiving Lu-177-PSMA-617-RLT. CRP, ALP and GGT levels cloud be utilized as additional decision aids when a Lu-177-PSMA-617-RLT is intended. Trial Registration Not applicable (retrospective observational study)

Video-based, student tutor- versus faculty staff-led ultrasound course for medical students - a prospective randomized study

Background Ultrasound education is propagated already during medical school due to its diagnostic importance. Courses are usually supervised by experienced faculty staff (FS) with patient bedside examinations or students among each other but often overbooked due to limited FS availability. To overcome this barrier, use of teaching videos may be advantageous. Likewise, peer teaching concepts solely with trained student tutors have shown to be feasible and effective. The aim was to evaluate 1) objective learning outcomes of a combined video-based, student-tutor (ViST) as compared to a FS-led course without media support, 2) acceptance and subjective learning success of the videos. Methods Two ultrasound teaching videos for basic and advanced abdominal ultrasound (AU) and transthoracic echocardiography (TTE) were produced and six students trained as tutors. Fourth-year medical students (N = 96) were randomized to either the ViST- or FS course (6 students per tutor). Learning objectives were defined equally for both courses. Acquired practical basic and advanced ultrasound skills were tested in an objective structured clinical examination (OSCE) using modified validated scoring sheets with a maximum total score of 40 points. Acceptance and subjective learning success of both videos were evaluated by questionnaires based on Kirkpatrick's evaluation model with scale-rated closed and open questions. Results 79 of 96 medical students completed the OSCE and 77 could be finally analyzed. There was no significant difference in the mean total point score of 31.3 in the ViST (N = 42) and 32.7 in the FS course (N = 35, P = 0.31) or in any of the examined basic or advanced ultrasound skill subtasks. Of the 42 ViST participants, 29 completed the AU and 27 the TTE video questionnaire. Acceptance and subjective learning success of both videos was rated positively in 14-52% and 48-88% of the rated responses to each category, respectively. Attendance of either the student or faculty tutor was deemed necessary in addition to the videos. Conclusions A ViST versus FS teaching concept was able to effectively teach undergraduate students in AU and TTE, albeit acceptance of the teaching videos alone was limited. However, the ViST concept has the potential to increase course availability and FS resource allocation

The Extended Postoperative Care-Score (EXPO-Score)-An Objective Tool for Early Identification of Indication for Extended Postoperative Care

Extended postoperative care and intensive care unit capacity is limited and efficient patient allocation is mandatory. This study aims to develop an effective yet simple score to predict indication for extended postoperative care, as there is a lack of objective criteria for early prediction of admission to extended care in surgical patients. This prospective observational study was divided into two periods (Period 1: Extended Postoperative Care-Score (EXPO)-Score generation; Period 2: EXPO-Score validation) and it was performed at a tertiary university center in Germany. A total of 4042 (Period 1) and 2198 (Period 2) adult patients ≥ 18 years old receiving elective or emergency surgery were included in this study. After identifying patient- and surgery-related risk factors by an expert panel, the EXPO-Score was developed through logistic regression from data of Period 1 and validated in Period 2. Three risk factors are sufficient for generating a reliable predictive EXPO-Score: (1) the American Society of Anesthesiologists' (ASA) physical status, (2) cardiopulmonary physical exercise status expressed in metabolic equivalents (MET), and (3) the type of surgery. The score threshold (0.23) has a sensitivity of 0.87, a specificity of 0.91, and an accuracy of 0.90 for predicting indication for extended postoperative care. The EXPO-Score provides a validated, early collectable, and easy-to-use tool for predicting indication of extended postoperative care in adult surgical patients

Including diverse and admixed populations in genetic epidemiology research

The inclusion of ancestrally diverse participants in genetic studies can lead to new discoveries and is important to ensure equitable health care benefit from research advances. Here, members of the Ethical, Legal, Social, Implications (ELSI) committee of the International Genetic Epidemiology Society (IGES) offer perspectives on methods and analysis tools for the conduct of inclusive genetic epidemiology research, with a focus on admixed and ancestrally diverse populations in support of reproducible research practices. We emphasize the importance of distinguishing socially defined population categorizations from genetic ancestry in the design, analysis, reporting, and interpretation of genetic epidemiology research findings. Finally, we discuss the current state of genomic resources used in genetic association studies, functional interpretation, and clinical and public health translation of genomic findings with respect to diverse populations

Long-Lived Individuals Show a Lower Burden of Variants Predisposing to Age-Related Diseases and a Higher Polygenic Longevity Score

Longevity is a complex phenotype influenced by both environmental and genetic factors. The genetic contribution is estimated at about 25%. Despite extensive research efforts, only a few longevity genes have been validated across populations. Long-lived individuals (LLI) reach extreme ages with a relative low prevalence of chronic disability and major age-related diseases (ARDs). We tested whether the protection from ARDs in LLI can partly be attributed to genetic factors by calculating polygenic risk scores (PRSs) for seven common late-life diseases (Alzheimer's disease (AD), atrial fibrillation (AF), coronary artery disease (CAD), colorectal cancer (CRC), ischemic stroke (ISS), Parkinson's disease (PD) and type 2 diabetes (T2D)). The examined sample comprised 1351 German LLI (≥94 years, including 643 centenarians) and 4680 German younger controls. For all ARD-PRSs tested, the LLI had significantly lower scores than the younger control individuals (areas under the curve (AUCs): ISS = 0.59, p = 2.84 × 10-35; AD = 0.59, p = 3.16 × 10-25; AF = 0.57, p = 1.07 × 10-16; CAD = 0.56, p = 1.88 × 10-12; CRC = 0.52, p = 5.85 × 10-3; PD = 0.52, p = 1.91 × 10-3; T2D = 0.51, p = 2.61 × 10-3). We combined the individual ARD-PRSs into a meta-PRS (AUC = 0.64, p = 6.45 × 10-15). Furthermore, the inclusion of nine markers from the excluded region (not in LD with each other) plus the APOE haplotype into the model raised the AUC from 0.55 to 0.61. Thus, our results highlight the importance of TOMM40/APOE/APOC1 as a longevity hub