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Background Patients with schizophrenia are at a higher risk for suicide compared with the general population. Dopamine beta‐hydroxylase (DβH) plays a key role in the conversion of dopamine to norepinephrine, which is related to suicidal behavior and cognitive regulation. Objective To examine whether there is the effect of DβH 5′‐insertion/deletion (Ins/Del) polymorphism on cognitive performance in suicide attempters with chronic schizophrenia. Methods This polymorphism was detected in 114 suicide attempters and 617 non‐suicide attempters with chronic schizophrenia. Cognitive performance was assessed by the Repeatable Battery for the Assessment of Neuropsychological Status (RBANS). Results The allelic and genotypic frequencies of this polymorphism between two groups did not differ after controlling for covariates (both, p > .05). There were no differences in RBANS scores between two groups after adjusting for covariates (all, p > .05). However, based on the genotype grouping in suicide attempters and non‐attempters, the attention score significantly differed after adjusting for covariates (both, p < .05). Further analysis indicated that this polymorphism was associated with attention score in suicide attempters (p < .05), but not in non‐suicide attempters (p > .05). Conclusions DβH 5′‐Ins/Del polymorphism was not a risk locus of suicide attempters, but it was implicated in attention regulation in suicide attempters with chronic schizophrenia.

Background Noninvasive prenatal testing (NIPT) for common fetal aneuploidies has been widely adopted in clinical practice for its sensitivity and accuracy. However, detection of pathogenic copy number variations (pCNVs) or monogenic disorders (MDs) is inaccurate and not cost effective. Here we developed an assay, the noninvasive prenatal testing based on goodness‐of‐fit and graphical analysis of polymorphic sites (GGAP‐NIPT), to simultaneously detect fetal aneuploidies, pCNVs, and MDs. Methods Polymorphic sites were amplicon sequenced, followed by fetal fraction estimation using allelic reads counts and a robust linear regression model. The genotype of each polymorphic site or MD variant was then determined by allelic goodness‐of‐fit test or graphical analysis of its different alleles. Finally, aneuploidies and pCNVs were detected using collective goodness‐of‐fit test to select each best fit from all possible chromosomal models. Results Of the simulated 1,692 chromosomes and 1,895 pCNVs, all normals and variants were correctly identified (accuracy 100%, sensitivity 100%, specificity 100%). Of the 713,320 simulated MD variants, more than 90% of the genotypes were determined correctly (accuracy: 98.3 ± 1.0%; sensitivity: 98.7 ± 1.96%; specificity: 99.7 ± 0.6%). The detection accuracies of three public MD datasets were 95.70%, 93.43%, and 96.83%. For an MD validation dataset, 75% detection accuracy was observed when a site with sample replicates was analyzed individually, and 100% accuracy was achieved when analyzed collectively. Conclusions Fetal aneuploidies, pCNVs, and MDs could be detected simultaneously and with high accuracy through amplicon sequencing of polymorphic and target sites, which showed the potential of extending NIPT to an expanded panel of genetic disorders.

Non-invasive prenatal testing (NIPT) for common fetal aneuploidies using circulating cell free DNA in maternal plasma has been widely adopted in clinical practice for its sensitivity and accuracy. However, the detection of subchromosomal abnormalities or monogenetic variations using such a method showed no cost-effectiveness or satisfactory accuracy. Here we show that with the aid of polymorphic sites sequencing, fetal fraction of the sample and genotype of the target site were determined with high accuracy. Then genetic variations at the chromosomal, subchromosomal and nucleotide levels were detected using the overall allelic goodness-of-fit test of all target polymorphic sites to each possible genetic model. Finally, relative allelic distributions for each amplicon were visualized and genetic variations at the chromosomal, subchromosomal and nucleotide levels were determined by distinct characteristic clusters on allelic distribution plot of each possible genetic model. As no parental genetic information was required and all allelic information retained for amplicon sequencing, the reported approach has the potential to simultaneously detect genetic variations at different levels, facilitating the extension of NIPT to all common genetic conditions for general low-risk pregnancies and target variations for certain high-risk pregnancy groups.