Erratum: Author Correction: Identification of genes required for eye development by high-throughput screening of mouse knockouts.

[This corrects the article DOI: 10.1038/s42003-018-0226-0.]

Identification of genes required for eye development by high-throughput screening of mouse knockouts.

Despite advances in next generation sequencing technologies, determining the genetic basis of ocular disease remains a major challenge due to the limited access and prohibitive cost of human forward genetics. Thus, less than 4,000 genes currently have available phenotype information for any organ system. Here we report the ophthalmic findings from the International Mouse Phenotyping Consortium, a large-scale functional genetic screen with the goal of generating and phenotyping a null mutant for every mouse gene. Of 4364 genes evaluated, 347 were identified to influence ocular phenotypes, 75% of which are entirely novel in ocular pathology. This discovery greatly increases the current number of genes known to contribute to ophthalmic disease, and it is likely that many of the genes will subsequently prove to be important in human ocular development and disease

Identification of genes required for eye development by high-throughput screening of mouse knockouts

International audienc

New genetic loci link adipose and insulin biology to body fat distribution.

Body fat distribution is a heritable trait and a well-established predictor of adverse metabolic outcomes, independent of overall adiposity. To increase our understanding of the genetic basis of body fat distribution and its molecular links to cardiometabolic traits, here we conduct genome-wide association meta-analyses of traits related to waist and hip circumferences in up to 224,459 individuals. We identify 49 loci (33 new) associated with waist-to-hip ratio adjusted for body mass index (BMI), and an additional 19 loci newly associated with related waist and hip circumference measures (P < 5 × 10(-8)). In total, 20 of the 49 waist-to-hip ratio adjusted for BMI loci show significant sexual dimorphism, 19 of which display a stronger effect in women. The identified loci were enriched for genes expressed in adipose tissue and for putative regulatory elements in adipocytes. Pathway analyses implicated adipogenesis, angiogenesis, transcriptional regulation and insulin resistance as processes affecting fat distribution, providing insight into potential pathophysiological mechanisms

Phenotypic and molecular characteristics associated with various domains of quality of life in oncology patients and their family caregivers

Purpose Not all oncology patients and their family caregivers (FCs) experience the same quality of life (QOL). The purposes of this study were to identify latent classes of oncology patients (n = 168) and their FCs (n = 85) with distinct physical, psychological, social, and spiritual well-being trajectories from prior to through 4 months after the completion of radiation therapy and to evaluate for demographic, clinical, and genetic characteristics that distinguished between these latent classes. Methods Using growth mixture modeling, two latent classes were found for three (i.e., physical, psychological, and social well-being) of the four QOL domains evaluated. Results Across these three domains, the largest percentage of participants reported relatively high well-being scores across the 6 months of the study. Across these three QOL domains, patients and FCs who were younger, female, belonged to an ethnic minority group, had children at home, had multiple comorbid conditions, or had a lower functional status, were more likely to be classified in the lower QOL class. The social well-being domain was the only domain that had a polymorphism in nuclear factor kappa beta 2 (NFKB2) associated with latent class membership. Carrying one or two doses of the rare allele for rs7897947 was associated with a 54 % decrease in the odds of belonging to the lower social well-being class [OR (95 % CI) = .46 (.21, .99), p = .049]. Conclusions These findings suggest that a number of phenotypic and molecular characteristics contribute to differences in QOL in oncology patients and their FCs

Phenotypic and molecular characteristics associated with various domains of quality of life in oncology patients and their family caregivers

PurposeNot all oncology patients and their family caregivers (FCs) experience the same quality of life (QOL). The purposes of this study were to identify latent classes of oncology patients (n&nbsp;=&nbsp;168) and their FCs (n&nbsp;=&nbsp;85) with distinct physical, psychological, social, and spiritual well-being trajectories from prior to through 4&nbsp;months after the completion of radiation therapy and to evaluate for demographic, clinical, and genetic characteristics that distinguished between these latent classes.MethodsUsing growth mixture modeling, two latent classes were found for three (i.e., physical, psychological, and social well-being) of the four QOL domains evaluated.ResultsAcross these three domains, the largest percentage of participants reported relatively high well-being scores across the 6&nbsp;months of the study. Across these three QOL domains, patients and FCs who were younger, female, belonged to an ethnic minority group, had children at home, had multiple comorbid conditions, or had a lower functional status, were more likely to be classified in the lower QOL class. The social well-being domain was the only domain that had a polymorphism in nuclear factor kappa beta 2 (NFKB2) associated with latent class membership. Carrying one or two doses of the rare allele for rs7897947 was associated with a 54&nbsp;% decrease in the odds of belonging to the lower social well-being class [OR (95&nbsp;% CI)&nbsp;=&nbsp;.46 (.21, .99), p&nbsp;=&nbsp;.049].ConclusionsThese findings suggest that a number of phenotypic and molecular characteristics contribute to differences in QOL in oncology patients and their FCs

Latent class analysis reveals distinct subgroups of patients based on symptom occurrence and demographic and clinical characteristics

Context Cancer patients experience a broad range of physical and psychological symptoms as a result of their disease and its treatment. On average, these patients report ten unrelieved and co-occurring symptoms. Objectives To determine if subgroups of oncology outpatients receiving active treatment (n=582) could be identified based on their distinct experience with thirteen commonly occurring symptoms; to determine whether these subgroups differed on select demographic, and clinical characteristics; and to determine if these subgroups differed on quality of life (QOL) outcomes. Methods Demographic, clinical, and symptom data from one Australian and two U.S. studies were combined. Latent class analysis (LCA) was used to identify patient subgroups with distinct symptom experiences based on self-report data on symptom occurrence using the Memorial Symptom Assessment Scale (MSAS). Results Four distinct latent classes were identified (i.e., All Low (28.0%), Moderate Physical and Lower Psych (26.3%), Moderate Physical and Higher Psych (25.4%), All High (20.3%)). Age, gender, education, cancer diagnosis, and presence of metastatic disease differentiated among the latent classes. Patients in the All High class had the worst QOL scores. Conclusion Findings from this study confirm the large amount of interindividual variability in the symptom experience of oncology patients. The identification of demographic and clinical characteristics that place patients are risk for a higher symptom burden can be used to guide more aggressive and individualized symptom management interventions

Latent Class Analysis Reveals Distinct Subgroups of Patients Based on Symptom Occurrence and Demographic and Clinical Characteristics.

ContextCancer patients experience a broad range of physical and psychological symptoms as a result of their disease and its treatment. On average, these patients report 10 unrelieved and co-occurring symptoms.ObjectivesThe aims were to determine if subgroups of oncology outpatients receiving active treatment (n&nbsp;=&nbsp;582) could be identified based on their distinct experience with 13 commonly occurring symptoms; to determine whether these subgroups differed on select demographic and clinical characteristics; and to determine if these subgroups differed on quality of life (QOL) outcomes.MethodsDemographic, clinical, and symptom data from one Australian and two U.S. studies were combined. Latent class analysis was used to identify patient subgroups with distinct symptom experiences based on self-report data on symptom occurrence using the Memorial Symptom Assessment Scale.ResultsFour distinct latent classes were identified (i.e., all low [28.0%], moderate physical and lower psych [26.3%], moderate physical and higher psych [25.4%], and all high [20.3%]). Age, gender, education, cancer diagnosis, and presence of metastatic disease differentiated among the latent classes. Patients in the all high class had the worst QOL scores.ConclusionFindings from this study confirm the large amount of interindividual variability in the symptom experience of oncology patients. The identification of demographic and clinical characteristics that place patients at risk for a higher symptom burden can be used to guide more aggressive and individualized symptom management interventions