Rapid authenticity testing of artificially bred green turtles (Chelonia mydas) using microsatellite and mitochondrial DNA markers

Sea turtles are threatened by climate change and human activity, and their global populations continue to decline sharply. The Chinese government encourages artificial breeding of sea turtles to reduce the use of wild populations. However, artificial breeding of sea turtles is still fairly difficult, and some facilities may illegally purchase wild turtle eggs and then sell incubated turtles by marketing them as artificially bred turtles, which adds another threat to an already endangered species. Therefore, it is necessary to find a reliable method to distinguish the authenticity of artificially bred individuals. In this study, we investigated a turtle farm in southern China, that contained more than 400 green turtles, which were claimed to have been bred in captivity. Parentage testing of turtles from this farm was successfully conducted using two nuclear microsatellites combined with a mitochondrial D-loop DNA marker. Genetic matching of all 19 adults and randomly selected 16 juvenile turtles revealed that none of the juvenile turtles had a matching parent combination among the adult turtles. Therefore, we speculated that the green turtles in this farm were from the wild and that their origin of birth was mainly the Sulu Sea. The methods and molecular markers used in this study could be a reference for rapid authenticity testing of green turtles in future forensic enforcement and population management.

Chagas disease and SARS-CoV-2 coinfection does not lead to worse in-hospital outcomes

Chagas disease (CD) continues to be a major public health burden in Latina America. Information on the interplay between COVID-19 and CD is lacking. Our aim was to assess clinical characteristics and in-hospital outcomes of patients with CD and COVID-19, and to compare it to non-CD patients. Consecutive patients with confirmed COVID-19 were included from March to September 2020. Genetic matching for sex, age, hypertension, diabetes mellitus and hospital was performed in a 4:1 ratio. Of the 7018 patients who had confirmed COVID-19, 31 patients with CD and 124 matched controls were included (median age 72 (64–80) years-old, 44.5% were male). At baseline, heart failure (25.8% vs. 9.7%) and atrial fibrillation (29.0% vs. 5.6%) were more frequent in CD patients than in the controls (p < 0.05). C-reactive protein levels were lower in CD patients compared with the controls (55.5 [35.7, 85.0] vs. 94.3 [50.7, 167.5] mg/dL). In-hospital management, outcomes and complications were similar between the groups. In this large Brazilian COVID-19 Registry, CD patients had a higher prevalence of atrial fibrillation and chronic heart failure compared with non-CD controls, with no differences in-hospital outcomes. The lower C-reactive protein levels in CD patients require further investigation.

Long-term weight gain in obese COPD patients participating in a disease management program: a risk factor for reduced health-related quality of life

Background Little is known about how long-term weight gain affects the health perception of COPD patients. Objectives The aim is to evaluate the long-term association of BMI change and health-related quality of life (HRQoL) in obese COPD patients. Methods Claims and survey data from a COPD disease management program were used to match two groups of COPD patients with BMI ≥ 30 who have differing weight trajectories over a 5-year timespan via propensity score and genetic matching. EQ-5D-5L, including visual analog scale (VAS) and COPD Assessment Test (CAT), were used as outcomes of interest. Sociodemographic and disease-based variables were matched. Results Out of 1202 obese COPD patients, 126 with a weight increase of four or more BMI points were matched separately with 252 (propensity score matching) and 197 (genetic matching) control subjects who had relatively stable BMI. For the EQ-5D-5L, patients with BMI increase reported significantly worse health perception for VAS and all descriptive dimensions except pain/discomfort. For the CAT, especially the perception of ability to complete daily activities and overall energy results were significantly worse. VAS differences reach the range of minimal important differences. Stopping smoking and already being in obesity class II were the most influential risk factors for BMI increase. Conclusion Obese COPD patients who gain four or more BMI points over 5 years report significantly lower results in different dimensions of generic and disease-specific HRQoL than their peers with stable BMI. To improve real-world outcomes, tracking and preventing specific BMI trajectories could constitute a clinically relevant aspect of managing COPD patients.

Chagas disease and SARS-CoV-2 coinfection does not lead to worse in-hospital outcomes

Chagas disease (CD) continues to be a major public health burden in Latina America. Information on the interplay between COVID-19 and CD is lacking. Our aim was to assess clinical characteristics and in-hospital outcomes of patients with CD and COVID-19, and to compare it to non-CD patients. Consecutive patients with confirmed COVID-19 were included from March to September 2020. Genetic matching for sex, age, hypertension, diabetes mellitus and hospital was performed in a 4:1 ratio. Of the 7,018 patients who had confirmed COVID-19, 31 patients with CD and 124 matched controls were included (median age 72 (64.-80) years-old, 44.5% were male). At baseline, heart failure (25.8% vs. 9.7%) and atrial fibrillation (29.0% vs. 5.6%) were more frequent in CD patients than in the controls (p < 0.05). C-reactive protein levels were lower in CD patients compared with the controls (55.5 [35.7, 85.0] vs. 94.3 [50.7, 167.5] mg/dL). In-hospital management, outcomes and complications were similar between the groups. In this large Brazilian COVID-19 Registry, CD patients had a higher prevalence of atrial fibrillation and chronic heart failure compared with non-CD controls, with no differences in-hospital outcomes. The lower C-reactive protein levels in CD patients require further investigation.

P–548 High-risk genetic matching on gamete donors: complete genes analysis or genotyping test?

Study question What carrier screening test is better to reduce the risk of offspring being affected by recessive diseases when genetic matching is performed with gamete donors: complete or targeted genes analysis? Summary answer The use of complete genes analysis in the carrier screening of gamete donors reduces the risk of offspring being affected by recessive diseases. What is known already Legislative measures and scientific societies alike call for more research to be conducted into recessive diseases in gamete donors, in order to reduce reproductive risk. However, it is still unclear which genes should be studied and what type of data analysis, targeted or nontargeted, should be performed. Study design, size, duration This descriptive observational study of 923 oocyte donors and 895 semen donors was conducted from January 2017 to August 2020, at a private gamete bank. Participants/materials, setting, methods 1818 gamete donors screened by NGS and nontargeted analysis of the variants, the pathogenic variants detected were analysed to estimate the probability of high-risk genetic matching and to determine the results that would have been obtained if the three most commonly used genotyping tests for carriers of recessive diseases in ART had been applied. Main results and the role of chance The probability of high-risk genetic matching with gamete donation, screened by NGS and complete genes analysis, was 5.48%, versus the 0.57–2.8% that would have been obtained if the genotyping test had been applied. Of the 1739 total variants found, only 28.69% would have been detected by all three targeted tests considered and 45.66% of the variants would not have been detected by any of them. Limitations, reasons for caution The study was not based in the general population, was limited to a population of Mediterranean ethnic origin. In addition, our study only analysed 302 recessive diseases of the 1,300 plus that have been described. Wider implications of the findings: Our study highlights the considerable heterogeneity of the genotyping tests commonly used in ART, which present significant differences in their ability to detect pathogenic variants. Therefore, the use of genotyping tests for genetic matching is associated with a higher reproductive risk, compared to the use of complete genes analysis. Trial registration number Not applicable

Diagnosis of Rare Diseases: A scoping review of clinical decision support systems

Background Rare Diseases (RD), which are defined as diseases affecting not more than 5 out of 10,000 people, are often severe, chronic, degenerative and life-threating. A main problem is the delay in diagnosis of RD. Clinical Decision Support Systems (CDSS) for RD are software-systems to support physicians in the diagnosis of patients with RD. It would therefore be useful to get a comprehensive overview of which CDSS are available and can be used under what conditions. In this work we provide a review of current CDSS in RD and which functionality and data are used by the CDSS. Methods We searched Pubmed and Cochrane for CDSS in RD published between December 1, 2008 and December 16, 2018. Only English articles, original peer reviewed journals and conference paper describing a clinical prototype or a routine use of CDSS where included. A total of 2076 articles were found and following a screening step 16 articles (describing 13 different CDSS) were considered as relevant for the final analysis. We then described and compared the CDSS using the defined categories “functionality”, “development status”, “type of clinical data” and “system availability”. Results Three types of CDSS for RD were identified: “Machine Learning and Information retrieval”, “Web Search”, and “Phenotypic and genetic matching”. 8 of the 13 reviewed CDSS are publicly available and for use by physicians. The other remaining CDSS are clinical prototypes which have been applied in clinical studies but are not accessible to others. Only one clinical prototype online. The approaches of the CDSS differ depending on what type of clinical data is used. “Machine Learning and information retrieval” can show recommendations for a diagnosis, while Web “search CDSS” will retrieve articles from literature databases (e.g. case reports), which may provide hints for a possible Diagnosis. CDSS in “Phenotypic and genetic matching” can identify similar patients based on genetic or phenotypic data. Conclusions Different CDSS for different purposes have been established and physicians have to decide which CDSS is more accurate for a particular patient case. It remains to be seen which of the CDSS will be used and maintained in the future.