Search

Background: Few studies have investigated the associations of childhood growth trajectories with the prenatal metabolic risks of mothers and their interaction with children's genetic susceptibility. Objective: To investigate the effects of gestational metabolic syndrome (GMS) risks and children's polygenic risk scores (PRSs), and their interaction effect on the BMI trajectory and obesity risk of offspring from birth to 6 years of age. Methods: A total of 2,603 mother-child pairs were recruited from the Ma'anshan birth cohort (Anhui Province of China) study. Data on maternal prepregnancy obesity, gestational weight gain (GWG), gestational diabetes mellitus (GDM), and hypertensive disorders of pregnancy (HDP) were used to evaluate maternal GMS risk. In addition, 1,482 cord blood samples were used to genotype 11 candidate single-nucleotide polymorphisms (SNPs) to calculate children's PRSs. The latent class growth model using the longitudinal BMI-for-age z scores (BMIz) was applied to validly capture the BMIz growth trajectory. Results: Maternal GMS status was associated with higher BMIz scores and with an increased risk of overweight/obesity. Positive relationships were revealed between PRS and the risk of overweight/obesity among girls. Additionally, maternal GMS significantly interacted with the child's PRS on BMIz scores and the risk of overweight/obesity among girls. Hierarchical BMI trajectory graphs by different exposure groups showed consistent findings, and both boys' and girls' BMIz trajectories were divided into three groups. Among girls, the higher the GMS risk or PRS they had, the higher the probability of being in the high BMIz trajectory group. Conclusions: Maternal GMS status increased BMIz scores and the risk of obesity in both boys and girls and elevated the child's BMI trajectory from birth to 6 years of age among girls. PRSs were significantly associated with children's BMI trajectory and the risk of obesity and modified the associations between maternal GMS status and obesity biomarkers only among girls. Thus, regarding childhood obesity, steps should be taken to decrease maternal metabolic risks before and during pregnancy, and sex discrepancies should be noted to identify high-risk populations after birth to hierarchically manage them. [ABSTRACT FROM AUTHOR]

Receiving polygenic risk estimates of future disease through health care or direct-to-consumer companies is expected to become more common in the coming decades. However, only a limited number of studies have examined if such estimates might evoke an adverse psychosocial reaction in receivers. The present study utilized data from a sub-section of a personalized medicine project (the P5 study) that combines genomic and traditional health data to evaluate participants' risk for certain common diseases. We investigated how communication of future disease risk estimates related to type 2 diabetes and coronary heart disease influenced respondents' risk perception, self-efficacy, disease-related worry, and other emotions. A randomized controlled trial was conducted, where the experimental group (n = 714) received risk estimates based on traditional and polygenic risk factors and the control group (n = 649) based solely on traditional risk factors. On average, higher disease risk was associated with higher perceived risk (p s, <0.001, ηp2 = 0.087–0.071), worry (p s <0.001, ηp2 = 0.061–0.028), lower self-efficacy (p <0.001, ηp2 = 0.012), less positive emotions (p s <0.04, ηp2 = 0.042–0.005), and more negative emotions (p s <0.048, ηp2 = 0.062–0.006). However, we found no evidence that adding the polygenic risk to complement the more traditional risk factors would induce any substantive psychosocial harm to the recipients (p s >0.06). [ABSTRACT FROM AUTHOR]

Receiving polygenic risk estimates of future disease through health care or direct-to-consumer companies is expected to become more common in the coming decades. However, only a limited number of studies have examined if such estimates might evoke an adverse psychosocial reaction in receivers. The present study utilized data from a sub-section of a personalized medicine project (the P5 study) that combines genomic and traditional health data to evaluate participants’ risk for certain common diseases. We investigated how communication of future disease risk estimates related to type 2 diabetes and coronary heart disease influenced respondents’ risk perception, self-efficacy, disease-related worry, and other emotions. A randomized controlled trial was conducted, where the experimental group (n = 714) received risk estimates based on traditional and polygenic risk factors and the control group (n = 649) based solely on traditional risk factors. On average, higher disease risk was associated with higher perceived risk (ps, 0.06).

Childhood epilepsy is a considerably heterogeneous neurological condition with a high worldwide incidence. Genetic diagnosis of childhood epilepsy provides the most accurate pathogenetic evidence; however, a large proportion of highly suspected cases remain undiagnosed. Accumulation of rare variants at the exome level as a multigenic burden contributing to childhood epilepsy should be further evaluated. In this retrospective analysis, exome-level sequencing was used to depict the mutation spectra of 294 childhood epilepsy patients from Shanghai Children's Medical Center, Department of Neurology. Furthermore, variant information from exome sequencing data was analyzed apart from monogenic diagnostic purposes to elucidate the possible multigenic burden of rare variants related to epilepsy pathogenesis. Exome sequencing reached a diagnostic rate of 30.61% and identified six genes not currently listed in the epilepsy-associated gene list. A multigenic burden study revealed a three-fold possibility that deleterious missense mutations in ion channel and synaptic genes in the undiagnosed cohort may contribute to the genetic risk of childhood epilepsy, whereas variants in the gene categories of cell growth, metabolic, and regulatory function showed no significant difference. Our study provides a comprehensive overview of the genetic diagnosis of a Chinese childhood epilepsy cohort and provides novel insights into the genetic background of these patients. Harmful missense mutations in genes related to ion channels and synapses are most likely to produce a multigenic burden in childhood epilepsy. [ABSTRACT FROM AUTHOR]

Background: The prevalence of insomnia and hypersomnia in depressed individuals is substantially higher than that found in the general population. Unfortunately, these concurrent sleep problems can have profound effects on the disease course. Although the full biology of sleep remains to be elucidated, a recent genome-wide association (GWAS) of insomnia, and other sleep traits in over 1 million individuals was recently published and provides many promising hits for genetics of insomnia in a population-based sample. Methods: Using data from the largest available GWAS of insomnia and other sleep traits, we sought to test if sleep variable PRS scores derived from population-based studies predicted sleep variables in samples of depressed cases [Psychiatric Genomics Consortium - Major Depressive Disorder subjects (PGC MDD)]. A leave-one-out analysis was performed to determine the effects that each individual study had on our results. Results: The only significant finding was for insomnia, where p-value threshold, p = 0.05 was associated with insomnia in our PGC MDD sample (R² = 1.75-3, p = 0.006). Conclusion: Our results reveal that <1% of variance is explained by the variants that cover the two significant p-value thresholds, which is in line with the fact that depression and insomnia are both polygenic disorders. To the best of our knowledge, this is the first study to investigate genetic overlap between the general population and a depression sample for insomnia, which has important treatment implications, such as leading to novel drug targets in future research efforts. [ABSTRACT FROM AUTHOR]

Background: The prevalence of insomnia and hypersomnia in depressed individuals is substantially higher than that found in the general population. Unfortunately, these concurrent sleep problems can have profound effects on the disease course. Although the full biology of sleep remains to be elucidated, a recent genome-wide association (GWAS) of insomnia, and other sleep traits in over 1 million individuals was recently published and provides many promising hits for genetics of insomnia in a population-based sample.Methods: Using data from the largest available GWAS of insomnia and other sleep traits, we sought to test if sleep variable PRS scores derived from population-based studies predicted sleep variables in samples of depressed cases [Psychiatric Genomics Consortium - Major Depressive Disorder subjects (PGC MDD)]. A leave-one-out analysis was performed to determine the effects that each individual study had on our results.Results: The only significant finding was for insomnia, where p-value threshold, p = 0.05 was associated with insomnia in our PGC MDD sample (R2 = 1.75−3, p = 0.006).Conclusion: Our results reveal that

Childhood epilepsy is a considerably heterogeneous neurological condition with a high worldwide incidence. Genetic diagnosis of childhood epilepsy provides the most accurate pathogenetic evidence; however, a large proportion of highly suspected cases remain undiagnosed. Accumulation of rare variants at the exome level as a multigenic burden contributing to childhood epilepsy should be further evaluated. In this retrospective analysis, exome-level sequencing was used to depict the mutation spectra of 294 childhood epilepsy patients from Shanghai Children’s Medical Center, Department of Neurology. Furthermore, variant information from exome sequencing data was analyzed apart from monogenic diagnostic purposes to elucidate the possible multigenic burden of rare variants related to epilepsy pathogenesis. Exome sequencing reached a diagnostic rate of 30.61% and identified six genes not currently listed in the epilepsy-associated gene list. A multigenic burden study revealed a three-fold possibility that deleterious missense mutations in ion channel and synaptic genes in the undiagnosed cohort may contribute to the genetic risk of childhood epilepsy, whereas variants in the gene categories of cell growth, metabolic, and regulatory function showed no significant difference. Our study provides a comprehensive overview of the genetic diagnosis of a Chinese childhood epilepsy cohort and provides novel insights into the genetic background of these patients. Harmful missense mutations in genes related to ion channels and synapses are most likely to produce a multigenic burden in childhood epilepsy.

BackgroundThe genetic architecture of psychotic disorders is complex, with hundreds of genetic risk loci contributing to a polygenic model of disease. Overlap in the genetics of psychotic disorders and brain measures has been found in European populations, but has not been explored in populations of African ancestry. The aim of this study was to determine whether a relationship exists between a schizophrenia-derived PRS and (i) methamphetamine associated psychosis (MAP), and (ii) brain structural measures, in a South African population.MethodsThe study sample consisted of three participant groups: 31 individuals with MAP, 48 with apsychotic methamphetamine dependence, and 49 healthy controls. Using PRSice, PRS was generated for each of the participants with GWAS summary statistics from the Psychiatric Genomics Consortium Schizophrenia working group (PGC-SCZ2) as the discovery dataset. Regression analyses were performed to determine associations of PRS, with diagnosis, whole brain, and regional gray and white matter measures.ResultsSchizophrenia-derived PRS did not significantly predict MAP diagnosis. After correction for multiple testing, no significant associations were found between PRS and brain measures across all groups.DiscussionThe lack of significant associations here may indicate that the study is underpowered, that brain volumes in MAP are due to factors other than polygenic risk for schizophrenia, or that PRS derived from a largely European discovery set has limited utility in individuals of African ancestry. Larger studies, that include diverse populations, and more nuanced brain measures, may help elucidate the relationship between schizophrenia-PRS, brain structural changes, and psychosis.ConclusionThis research presents the first PRS study to investigate shared genetic effects across psychotic disorders and brain structural measures in an African population. Ancestrally comparable discovery datasets may be useful for future African genetic research.

Background: The genetic architecture of psychotic disorders is complex, with hundreds of genetic risk loci contributing to a polygenic model of disease. Overlap in the genetics of psychotic disorders and brain measures has been found in European populations, but has not been explored in populations of African ancestry. The aim of this study was to determine whether a relationship exists between a schizophrenia-derived PRS and (i) methamphetamine associated psychosis (MAP), and (ii) brain structural measures, in a South African population. Methods: The study sample consisted of three participant groups: 31 individuals with MAP, 48 with apsychotic methamphetamine dependence, and 49 healthy controls. Using PRSice, PRS was generated for each of the participants with GWAS summary statistics from the Psychiatric Genomics Consortium Schizophrenia working group (PGC-SCZ2) as the discovery dataset. Regression analyses were performed to determine associations of PRS, with diagnosis, whole brain, and regional gray and white matter measures. Results: Schizophrenia-derived PRS did not significantly predict MAP diagnosis. After correction for multiple testing, no significant associations were found between PRS and brain measures across all groups. Discussion: The lack of significant associations here may indicate that the study is underpowered, that brain volumes in MAP are due to factors other than polygenic risk for schizophrenia, or that PRS derived from a largely European discovery set has limited utility in individuals of African ancestry. Larger studies, that include diverse populations, and more nuanced brain measures, may help elucidate the relationship between schizophrenia-PRS, brain structural changes, and psychosis. Conclusion: This research presents the first PRS study to investigate shared genetic effects across psychotic disorders and brain structural measures in an African population. Ancestrally comparable discovery datasets may be useful for future African genetic research. [ABSTRACT FROM AUTHOR]

Primary prevention in individuals at Clinical High Risk for psychosis (CHR-P) can ameliorate the course of psychotic disorders. Further advancements of knowledge have been slowed by the standstill of the field, which is mostly attributed to its epidemiological weakness. The latter, in turn, underlies the limited identification power of at-risk individuals and the relatively modest ability of CHR-P interviews to rule-in a state of risk for psychosis. In the first part, this perspective review discusses these limitations and traces a new approach to overcome them. Theoretical concepts to support a Psychosis Polyrisk Score (PPS) integrating genetic and non-genetic risk and protective factors for psychosis are presented. The PPS hinges on recent findings indicating that risk enrichment in CHR-P samples is accounted for by the accumulation of non-genetic factors such as: parental and sociodemographic risk factors, perinatal risk factors, later risk factors, and antecedents. In the second part of this perspective review we present a prototype of a PPS encompassing core predictors beyond genetics. The PPS prototype may be piloted in the next generation of CHR-P research and combined with genetic information to refine the detection of individuals at-risk of psychosis and the prediction of their outcomes, and ultimately advance clinical research in this field. [ABSTRACT FROM AUTHOR]