Symptom clusters in COVID-19: A potential clinical prediction tool from the COVID Symptom Study app

As no one symptom can predict disease severity or the need for dedicated medical support in coronavirus disease 2019 (COVID-19), we asked whether documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations. Clustering was validated on an independent replication dataset between 1 and 28 May 2020. Using the first 5 days of symptom logging, the ROC-AUC (receiver operating characteristic - area under the curve) of need for respiratory support was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required

Symptom clusters in COVID-19 : A potential clinical prediction tool from the COVID Symptom Study app

As no one symptom can predict disease severity or the need for dedicated medical support in coronavirus disease 2019 (COVID-19), we asked whether documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presenta- tions. Clustering was validated on an independent replication dataset between 1 and 28 May 2020. Using the first 5 days of symptom logging, the ROC-AUC (receiver operating characteristic – area under the curve) of need for respiratory sup- port was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required.

Symptom clusters in COVID-19 : A potential clinical prediction tool from the COVID Symptom Study app

As no one symptom can predict disease severity or the need for dedicated medical support in coronavirus disease 2019 (COVID-19), we asked whether documenting symptom time series over the first few days informs outcome. Unsupervised time series clustering over symptom presentation was performed on data collected from a training dataset of completed cases enlisted early from the COVID Symptom Study Smartphone application, yielding six distinct symptom presentations. Clustering was validated on an independent replication dataset between 1 and 28 May 2020. Using the first 5 days of symptom logging, the ROC-AUC (receiver operating characteristic - area under the curve) of need for respiratory support was 78.8%, substantially outperforming personal characteristics alone (ROC-AUC 69.5%). Such an approach could be used to monitor at-risk patients and predict medical resource requirements days before they are required

Paternal origin of the de novo constitutional t(11;22)(q23;q11)

The constitutional t(11;22)(q23;q11) is a well-known recurrent non-Robertsonian translocation in humans. Although translocations generally occur in a random fashion, the break points of t(11;22)s are concentrated within several hundred base pairs on 11q23 and 22q11. These regions are characterized by palindromic AT-rich repeats (PATRRs), which appear to be responsible for the genomic instability. Translocation-specific PCR detects de novo t(11;22)s in sperm from healthy males at a frequency of 1/104–105, but never in lymphoblasts, fibroblasts or other human somatic cell lines. This suggests that the generation of t(11;22) rearrangement is linked to gametogenesis, although female germ cells have not been tested. Here, we have studied eight cases of de novo t(11;22) to determine the parental origin of the translocation using the polymorphisms on the relevant PATRRs. All of the eight translocations were found to be of paternal origin. This result implicates a possible novel mechanism of sperm-specific generation of palindrome-mediated chromosomal translocations

An unexpected finding: younger fathers have a higher risk for offspring with chromosomal aneuploidies

The past decades have seen a remarkable shift in the demographics of childbearing in Western countries. The risk for offspring with chromosomal aneuploidies with advancing maternal age is well known, but most studies failed to demonstrate a paternal age effect. Retrospectively, we analyzed two case data sets containing parental ages from pre- and postnatal cases with trisomies 21, 13 and 18. The reference data set contains the parental ages of the general Swiss population. We dichotomized all couples into two distinct groups. In the first group, the mothers' integral age was as least as the father's age or older. We compared the frequency of cases in nine 5-year intervals of maternal age. In addition, we computed logistic regression models for the binary endpoint aneuploidy yes/no where paternal ages were incorporated as linear or quadratic, as well as smooth functions within a generalized additive model framework. We demonstrated that the proportion of younger fathers is uniformly different between cases and controls of live-born trisomy 21 as well, although not reaching significance, for fetuses over all mother's ages. Logistic regression models with different strategies to incorporate paternal ages confirmed our findings. The negative paternal age effect was also found in pre- and postnatal cases taken together with trisomies 13 and 18. The couples with younger fathers face almost twofold odds for a child with Down syndrome (DS). We estimated odds curves for parental ages. If confirmation of these findings can be achieved, the management of couples at risk needs a major correction of the risk stratification.European Journal of Human Genetics advance online publication, 9 July 2014; doi:10.1038/ejhg.2014.122

Advanced age increases chromosome structural abnormalities in human spermatozoa

This study explores the relationship between sperm structural aberrations and age by using a multicolor multichromosome FISH strategy that provides information on the incidence of duplications and deletions on all the autosomes. ToTelvysion kit (Abbott Molecular, Abbott Park, IL, USA) with telomere-specific probes was used. We investigated the sperm of 10 male donors aged from 23 to 74 years old. The donors were divided into two groups according to age, a cohort of five individuals younger than 40 and a cohort of five individuals older than 60 years. The goal of this study was to determine (1) the relationship between donor age and frequency and type of chromosome structural abnormalities and (2) chromosomes more frequently involved in sperm structural aberrations. We found that the older patients had a higher rate of structural abnormalities (6.6%) compared with the younger cohort (4.9%). Although both duplications and deletions were seen more frequently in older men, our findings demonstrate the presence of an excess of duplications versus deletions in both groups at a ratio of 2 to 1. We demonstrate that the distribution of duplications and deletions was not linear along the chromosomes, although a trend toward a higher rate of abnormalities in larger chromosomes was observed. This work is the first study addressing the frequencies of sperm chromosome structural aberrations of all autosomes in a single assay thus making a contribution to the clarification of the amount and origin of damage present in human spermatozoa and in relation to age