Polygenic risk scores (PRS), often aggregating the results from genome-wide association studies, can bridge the gap between the initial discovery efforts and clinical applications for disease risk estimation. However, there is remarkable heterogeneity in the reporting of these risk scores. This lack of adherence to reporting standards hinders the translation of PRS into clinical care. The ClinGen Complex Disease Working Group, in a collaboration with the Polygenic Score (PGS) Catalog, have updated the Genetic Risk Prediction (GRIPS) Reporting Statement to the current state of the field and to enable downstream utility. Drawing upon experts in epidemiology, statistics, disease-specific applications, implementation, and policy, this 22-item reporting framework defines the minimal information needed to interpret and evaluate a PRS, especially with respect to any downstream clinical applications. Items span detailed descriptions of the study population (recruitment method, key demographic and clinical characteristics, inclusion/exclusion criteria, and outcome definition), statistical methods for both PRS development and validation, and considerations for potential limitations of the published risk score and downstream clinical utility. Additionally, emphasis has been placed on data availability and transparency to facilitate reproducibility and benchmarking against other PRS, such as deposition in the publicly available PGS Catalog. By providing these criteria in a structured format that builds upon existing standards and ontologies, the use of this framework in publishing PRS will facilitate translation of PRS into clinical care and progress towards defining best practices.Summary In recent years, polygenic risk scores (PRS) have increasingly been used to capture the genome-wide liability underlying many human traits and diseases, hoping to better inform an individual’s genetic risk. However, a lack of adherence to existing reporting standards has hindered the translation of this important tool into clinical and public health practice; in particular, details necessary for benchmarking and reproducibility are underreported. To address this gap, the ClinGen Complex Disease Working Group and Polygenic Score (PGS) Catalog have updated the Genetic Risk Prediction (GRIPS) Reporting Statement into the 22-item Polygenic Risk Score Reporting Statement (PRS-RS). This framework provides the minimal information expected of authors to promote the validity, transparency, and reproducibility of PRS by encouraging authors to detail the study population, statistical methods, and potential clinical utility of a published score. The widespread adoption of this framework will encourage rigorous methodological consideration and facilitate benchmarking to ensure high quality scores are translated into the clinic.Competing Interest StatementMIM is on the advisory panels Pfizer, Novo Nordisk, and Zoe Global; Honoraria: Merck, Pfizer, Novo Nordisk, and Eli Lilly; Research funding: Abbvie, Astra Zeneca, Boehringer Ingelheim, Eli Lilly, Janssen, Merck, Novo Nordisk, Pfizer, Roche, Sanofi Aventis, Servier & Takeda. As of June 2019, he is an employee of Genentech with stock and stock options in Roche. No other authors have competing interests to declare.Funding StatementClinGen is primarily funded by the National Human Genome Research Institute (NHGRI), through the following three grants: U41HG006834, U41HG009649, U41HG009650. ClinGen also receives support for content curation from the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD), through the following three grants: U24HD093483, U24HD093486, U24HD093487. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Additionally, the views expressed in this article are those of the author(s) and not necessarily those of the NHS, the NIHR, or the Department of Health. Research reported in this publication was supported by the National Human Genome Research Institute of the National Institutes of Health under Award Number U41HG007823 (EBI-NHGRI GWAS Catalog, PGS Catalog). In addition, we acknowledge funding from the European Molecular Biology Laboratory. Individuals were funded from the following sources: MIM was a Wellcome Investigator and an NIHR Senior Investigator with funding from NIDDK (U01-DK105535); Wellcome (090532, 098381, 106130, 203141, 212259). MI, SAL, and JD were supported by core funding from: the UK Medical Research Council (MR/L003120/1), the British Heart Foundation (RG/13/13/30194; RG/18/13/33946) and the National Institute for Health Research (Cambridge Biomedical Research Centre at the Cambridge University Hospitals NHS Foundation Trust). SAL is supported by a Canadian Institutes of Health Research postdoctoral fellowship (MFE-171279). JD holds a British Heart Foundation Personal Chair and a National Institute for Health Research Senior Investigator Award. This work was also supported by Health Data Research UK, which is funded by the UK Medical Research Council, Engineering and Physical Sciences Research Council, Economic and Social Research Council, Department of Health and Social Care (England), Chief Scientist Office of the Scottish Government Health and Social Care Directorates, Health and Social Care Research and Development Division (Welsh Government), Public Health Agency (Northern Ireland), British Heart Foundation and Wellcome.Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:N/AAll necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable.YesN/A

COVID-19 dramatically accelerated evolving changes in the way we define the “work environment” in the United States. In response to COVID-19, many employers have offered increased flexibility for where employees work, including remote (an employee’s workstation is at home) and hybrid work (an employee works both at the employer worksite and remotely, on pre-determined schedules). Accordingly, worksite physical activity (PA) and sedentary behaviors (SB) such as extended sitting time (ST) may have changed.1,2 However, little is known about whether these work arrangements are associated with changes in employer support for PA. Interviews were conducted to assess this gap in understanding. Because little is known about employer support for equity with respect to PA and SB, this study sought to identify potential strategies to assure equity in PA opportunities across work environments.

Polygenic risk scores (PRSs), which often aggregate results from genome-wide association studies, can bridge the gap between initial discovery efforts and clinical applications for the estimation of disease risk using genetics. However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. Here, in a collaboration between the Clinical Genome Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, we present the Polygenic Risk Score Reporting Standards (PRS-RS), in which we update the Genetic Risk Prediction Studies (GRIPS) Statement to reflect the present state of the field. Drawing on the input of experts in epidemiology, statistics, disease-specific applications, implementation and policy, this comprehensive reporting framework defines the minimal information that is needed to interpret and evaluate PRSs, especially with respect to downstream clinical applications. Items span detailed descriptions of study populations, statistical methods for the development and validation of PRSs and considerations for the potential limitations of these scores. In addition, we emphasize the need for data availability and transparency, and we encourage researchers to deposit and share PRSs through the PGS Catalog to facilitate reproducibility and comparative benchmarking. By providing these criteria in a structured format that builds on existing standards and ontologies, the use of this framework in publishing PRSs will facilitate translation into clinical care and progress towards defining best practice.

Clearance of acute infection with hepatitis C virus (HCV) is associated with the chr19q13.13 region containing the rs368234815 (TT/ΔG) polymorphism. We fine-mapped this region to detect possible causal variants that may contribute to HCV clearance. First, we performed sequencing of IFNL1-IFNL4 region in 64 individuals sampled according to rs368234815 genotype: TT/clearance (N = 16) and ΔG/persistent (N = 15) (genotype-outcome concordant) or TT/persistent (N = 19) and ΔG/clearance (N = 14) (discordant). 25 SNPs had a difference in counts of alternative allele >5 between clearance and persistence individuals. Then, we evaluated those markers in an association analysis of HCV clearance conditioning on rs368234815 in two groups of European (692 clearance/1 025 persistence) and African ancestry (320 clearance/1 515 persistence) individuals. 10/25 variants were associated (P < 0.05) in the conditioned analysis leaded by rs4803221 (P value = 4.9 × 10(-04)) and rs8099917 (P value = 5.5 × 10(-04)). In the European ancestry group, individuals with the haplotype rs368234815ΔG/rs4803221C were 1.7× more likely to clear than those with the rs368234815ΔG/rs4803221G haplotype (P value = 3.6 × 10(-05)). For another nearby SNP, the haplotype of rs368234815ΔG/rs8099917T was associated with HCV clearance compared to rs368234815ΔG/rs8099917G (OR: 1.6, P value = 1.8 × 10(-04)). We identified four possible causal variants: rs368234815, rs12982533, rs10612351 and rs4803221. Our results suggest a main signal of association represented by rs368234815, with contributions from rs4803221, and/or nearby SNPs including rs8099917.

In an effort to improve health and business outcomes, workplaces are supplementing traditional physical activity programs focused on individual behavior change with policies designed to change workplace culture. However, confusion exists about how to define workplace policies. In practice, worksites implement programs, benefit designs, and environmental strategies and describe these as policies. The purpose of this essay is to provide a definition for worksite policy and discuss how policy approaches can support employers’ efforts to promote physical activity. We also describe worksite physical activity policies that employers can adopt and implement.

BACKGROUND: Melanoma, the deadliest form of skin cancer, is the second most common cancer diagnosed before age 30. Little is known about potentially modifiable or intervenable risk factors specific to developing melanoma at a young age. The objective was to determine if high birth weight or higher early life ultraviolet (UV) radiation exposure would be associated with increased risk of melanoma in young patients. METHODS: Population-based, case-control study of 1,396 cases of melanoma diagnosed before age 30 in 1988-2013 and 27,920 controls, obtained by linking cancer registry data to birth records in California. RESULTS: High birth weight (>4000g) was associated with 19% higher risk of melanoma (OR:1.19; 95% CI: 1.02, 1.39), while low birth weight (<2500g) was associated with 41% lower risk (OR:0.59; 95% CI: 0.43, 0.82), compared to normal birth weight (2500-4000g); dose-response per 1000g increase was also evident (OR:1.24; 95% CI:1.13, 1.36). All quartiles of birthplace UV greater than the lowest quartile were associated with increased melanoma risk. The strongest relationship between birthplace UV and melanoma was for 15-19 years of age at diagnosis. CONCLUSIONS: High birth weight and high early-life UV exposure may be important independent risk factors for melanoma diagnosis before age 30. The implication is that adopting skin-protective behaviors as early as infancy could be important for primary prevention of melanoma in younger people. However, research that accounts for early-life behavioral patterns of skin protection during infancy is needed to advance our understanding of how birth weight and early-life UV may influence development of early onset melanoma.

The 21(st) century has seen the rise of Internet-based participatory surveillance systems for infectious diseases. These systems capture voluntarily submitted symptom data from the general public and can aggregate and communicate that data in near real-time. We reviewed participatory surveillance systems currently running in 13 different countries. These systems have a growing evidence base showing a high degree of accuracy and increased sensitivity and timeliness relative to traditional healthcare-based systems. They have also proven useful for assessing risk factors, vaccine effectiveness, and patterns of healthcare utilization while being less expensive, more flexible, and more scalable than traditional systems. Nonetheless, they present important challenges including biases associated with the population that chooses to participate, difficulty in adjusting for confounders, and limited specificity because of reliance only on syndromic definitions of disease limits. Overall, participatory disease surveillance data provides unique disease information that is not available through traditional surveillance sources.

PROBLEM/CONDITION: Autism spectrum disorders (ASDs) are a group of developmental disabilities characterized by impairments in social interaction and communication and by restricted, repetitive, and stereotyped patterns of behavior. Symptoms typically are apparent before age 3 years. The complex nature of these disorders, coupled with a lack of biologic markers for diagnosis and changes in clinical definitions over time, creates challenges in monitoring the prevalence of ASDs. Accurate reporting of data is essential to understand the prevalence of ASDs in the population and can help direct research. PERIOD COVERED: 2008. DESCRIPTION OF SYSTEM: The Autism and Developmental Disabilities Monitoring (ADDM) Network is an active surveillance system that estimates the prevalence of ASDs and describes other characteristics among children aged 8 years whose parents or guardians reside within 14 ADDM sites in the United States. ADDM does not rely on professional or family reporting of an existing ASD diagnosis or classification to ascertain case status. Instead, information is obtained from children's evaluation records to determine the presence of ASD symptoms at any time from birth through the end of the year when the child reaches age 8 years. ADDM focuses on children aged 8 years because a baseline study conducted by CDC demonstrated that this is the age of identified peak prevalence. A child is included as meeting the surveillance case definition for an ASD if he or she displays behaviors (as described on a comprehensive evaluation completed by a qualified professional) consistent with the American Psychiatric Association's Diagnostic and Statistical Manual-IV, Text Revision (DSM-IV-TR) diagnostic criteria for any of the following conditions: Autistic Disorder; Pervasive Developmental Disorder-Not Otherwise Specified (PDD-NOS, including Atypical Autism); or Asperger Disorder. The first phase of the ADDM methodology involves screening and abstraction of comprehensive evaluations completed by professional providers at multiple data sources in the community. Multiple data sources are included, ranging from general pediatric health clinics to specialized programs for children with developmental disabilities. In addition, many ADDM sites also review and abstract records of children receiving special education services in public schools. In the second phase of the study, all abstracted evaluations are reviewed by trained clinicians to determine ASD case status. Because the case definition and surveillance methods have remained consistent across all ADDM surveillance years to date, comparisons to results for earlier surveillance years can be made. This report provides updated ASD prevalence estimates from the 2008 surveillance year, representing 14 ADDM areas in the United States. In addition to prevalence estimates, characteristics of the population of children with ASDs are described, as well as detailed comparisons of the 2008 surveillance year findings with those for the 2002 and 2006 surveillance years. RESULTS: For 2008, the overall estimated prevalence of ASDs among the 14 ADDM sites was 11.3 per 1,000 (one in 88) children aged 8 years who were living in these communities during 2008. Overall ASD prevalence estimates varied widely across all sites (range: 4.8-21.2 per 1,000 children aged 8 years). ASD prevalence estimates also varied widely by sex and by racial/ethnic group. Approximately one in 54 boys and one in 252 girls living in the ADDM Network communities were identified as having ASDs. Comparison of 2008 findings with those for earlier surveillance years indicated an increase in estimated ASD prevalence of 23% when the 2008 data were compared with the data for 2006 (from 9.0 per 1,000 children aged 8 years in 2006 to 11.0 in 2008 for the 11 sites that provided data for both surveillance years) and an estimated increase of 78% when the 2008 data were compared with the data for 2002 (from 6.4 per 1,000 children aged 8 years in 2002 to 11.4 in 2008 for the 13 sites that provided data for both surveillance years). Because the ADDM Network sites do not make up a nationally representative sample, these combined prevalence estimates should not be generalized to the United States as a whole. INTERPRETATION: These data confirm that the estimated prevalence of ASDs identified in the ADDM network surveillance populations continues to increase. The extent to which these increases reflect better case ascertainment as a result of increases in awareness and access to services or true increases in prevalence of ASD symptoms is not known. ASDs continue to be an important public health concern in the United States, underscoring the need for continued resources to identify potential risk factors and to provide essential supports for persons with ASDs and their families. PUBLIC HEALTH ACTION: Given substantial increases in ASD prevalence estimates over a relatively short period, overall and within various subgroups of the population, continued monitoring is needed to quantify and understand these patterns. With 5 biennial surveillance years completed in the past decade, the ADDM Network continues to monitor prevalence and characteristics of ASDs and other developmental disabilities for the 2010 surveillance year. Further work is needed to evaluate multiple factors contributing to increases in estimated ASD prevalence over time. ADDM Network investigators continue to explore these factors, with a focus on understanding disparities in the identification of ASDs among certain subgroups and on how these disparities have contributed to changes in the estimated prevalence of ASDs. CDC is partnering with other federal and private partners in a coordinated response to identify risk factors for ASDs and to meet the needs of persons with ASDs and their families.

PROBLEM/CONDITION: Autism spectrum disorders (ASDs) are a group of developmental disabilities characterized by atypical development in socialization, communication, and behavior. ASDs typically are apparent before age 3 years, with associated impairments affecting multiple areas of a person's life. Because no biologic marker exists for ASDs, identification is made by professionals who evaluate a child's developmental progress to identify the presence of developmental disorders. REPORTING PERIOD: 2006. METHODS: Earlier surveillance efforts indicated that age 8 years is a reasonable index age at which to monitor peak prevalence. The identified prevalence of ASDs in U.S. children aged 8 years was estimated through a systematic retrospective review of evaluation records in multiple sites participating in the Autism and Developmental Disabilities Monitoring (ADDM) Network. Data were collected from existing records in 11 ADDM Network sites (areas of Alabama, Arizona, Colorado, Florida, Georgia, Maryland, Missouri, North Carolina, Pennsylvania, South Carolina, and Wisconsin) for 2006. To analyze changes in identified ASD prevalence, CDC compared the 2006 data with data collected from 10 sites (all sites noted above except Florida) in 2002. Children aged 8 years with a notation of an ASD or descriptions consistent with an ASD were identified through screening and abstraction of existing health and education records containing professional assessments of the child's developmental progress at health-care or education facilities. Children aged 8 years whose parent(s) or legal guardian(s) resided in the respective areas in 2006 met the case definition for an ASD if their records documented behaviors consistent with the Diagnostic and Statistical Manual of Mental Disorders, 4th edition, text revision (DSM-IV-TR) criteria for autistic disorder, pervasive developmental disorder--not otherwise specified (PDD NOS), or Asperger disorder. Presence of an identified ASD was determined through a review of data abstracted from developmental evaluation records by trained clinician reviewers. RESULTS: For the 2006 surveillance year, 2,757 (0.9%) of 308,038 [corrected] children aged 8 years residing in the 11 ADDM sites were identified as having an ASD, indicating an overall average prevalence of 9.0 per 1,000 population (95% confidence interval [CI] = 8.6--9.3). ASD prevalence per 1,000 children aged 8 years ranged from 4.2 in Florida to 12.1 in Arizona and Missouri, with prevalence for the majority of sites ranging between 7.6 and 10.4. For 2006, ASD prevalence was significantly lower in Florida (p<0.001) and Alabama (p<0.05) and higher in Arizona and Missouri (p<0.05) than in all other sites. The ratio of males to females ranged from 3.2:1 in Alabama to 7.6:1 in Florida. ASD prevalence varied by type of ascertainment source, with higher average prevalence in sites with access to health and education records (10.0) compared with sites with health records only (7.5). Although parental or professional concerns regarding development before age 36 months were noted in the evaluation records of the majority of children who were identified as having an ASD, the median age of earliest documented ASD diagnosis was much later (range: 41 months [Florida]-60 months [Colorado]). Of 10 sites that collected data for both the 2002 and 2006 surveillance years, nine observed an increase in ASD prevalence (range: 27%-95% increase; p<0.01), with increases among males in all sites and among females in four of 11 sites, and variation among other subgroups. INTERPRETATION: In 2006, on average, approximately 1% or one child in every 110 in the 11 ADDM sites was classified as having an ASD (approximate range: 1:80-1:240 children [males: 1:70; females: 1:315]). The average prevalence of ASDs identified among children aged 8 years increased 57% in 10 sites from the 2002 to the 2006 ADDM surveillance year. Although improved ascertainment accounts for some of the prevalence increases documented in the ADDM sites, a true increase in the risk for children to develop ASD symptoms cannot be ruled out. On average, although delays in identification persisted, ASDs were being diagnosed by community professionals at earlier ages in 2006 than in 2002. PUBLIC HEALTH ACTIONS: These results indicate an increased prevalence of identified ASDs among U.S. children aged 8 years and underscore the need to regard ASDs as an urgent public health concern. Continued monitoring is needed to document and understand changes over time, including the multiple ascertainment and potential risk factors likely to be contributing. Research is needed to ascertain the factors that put certain persons at risk, and concerted efforts are essential to provide support for persons with ASDs, their families, and communities to improve long-term outcome.