human
***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Type 2 diabetes ( T2D ) is associated with increased risk of morbidity and premature mortality . Among those at high risk , incidence can be halved through healthy changes in behaviour . Information about genetic and phenotypic risk of T2D is now widely available . Whether such information motivates behaviour change is unknown . We aim to assess the effects of communicating genetic and phenotypic risk of T2D on risk-reducing health behaviours , anxiety , and other cognitive and emotional theory-based antecedents of behaviour change . In a parallel group , open r and omised controlled trial , approximately 580 adults born between 1950 and 1975 will be recruited from the on-going population -based , observational Fenl and Study ( Cambridgeshire , UK ) . Eligible participants will have undergone clinical , anthropometric , and psychosocial measurements , been genotyped for 23 single-nucleotide polymorphisms associated with T2D , and worn a combined heart rate monitor and accelerometer ( Actiheart ® ) continuously for six days and nights to assess physical activity .  Participants are r and omised to receive either st and ard lifestyle advice alone ( control group ) , or in combination with a genetic or a phenotypic risk estimate for T2D ( intervention groups ) . The primary outcome is objective ly measured physical activity . Secondary outcomes include self-reported diet , self-reported weight , intention to be physically active and to engage in a healthy diet , anxiety , diabetes-related worry , self-rated health , and other cognitive and emotional outcomes . Follow-up occurs eight weeks post-intervention . Values at follow-up , adjusted for baseline , will be compared between r and omised groups . This study will provide much needed evidence on the effects of providing information about the genetic and phenotypic risk of T2D . Importantly , it will be among the first to examine the impact of genetic risk information using a r and omised controlled trial design , a population -based sample , and an objective ly measured behavioural outcome . Results of this trial , along with recent evidence syntheses of similar studies , should inform policy concerning the availability and use of genetic risk information . Current Controlled Trials IS RCT Background There are few empirical data to inform the debate surrounding the use and regulation of direct-to-consumer ( DTC ) genome-wide disease risk tests . This study aim ed to determine the long term psychological , behavioural , and clinical impacts of genomic risk testing for common disease . Methods The Scripps Genomic Health Initiative is a prospect i ve longitudinal cohort study of adults who purchased the Navigenics Health Compass , a commercially available genomic test . Web based assessment s were administered at baseline , short ( 3 months ) , and long term ( 1 year ) follow-up . Results 2240 participants completed either or both follow-ups and a subset of 1325 completed long term follow-up . There were no significant differences from baseline in anxiety ( p=0.50 ) , fat intake ( p=0.34 ) , or exercise ( p=0.39 ) at long term follow-up , and 96.8 % of the sample had no test related distress . Longitudinal linear mixed model analyses were consistent with results of cross-sectional analyses . Screening test completion was associated with sharing genomic test results with a physician ( 36.0 % shared ; p<0.001 ) and perceived utility of the test ( 61.5 % high perceived utility ; p=0.002 ) , but was not associated with the genomic risk estimate values themselves . Conclusions Over a third of DTC genomic test recipients shared their results with their own physician during an approximate 1 year follow-up period , and this sharing was associated with higher screening test completion . Genomic testing was not associated with long term psychological risks , and most participants reportedly perceived the test to be of high personal utility Objectives To assess the performance of a panel of common single nucleotide polymorphisms ( genotypes ) associated with type 2 diabetes in distinguishing incident cases of future type 2 diabetes ( discrimination ) , and to examine the effect of adding genetic information to previously vali date d non-genetic ( phenotype based ) models developed to estimate the absolute risk of type 2 diabetes . Design Workplace based prospect i ve cohort study with three 5 yearly medical screenings . Participants 5535 initially healthy people ( mean age 49 years ; 33 % women ) , of whom 302 developed new onset type 2 diabetes over 10 years . Outcome measures Non-genetic variables included in two established risk models — the Cambridge type 2 diabetes risk score ( age , sex , drug treatment , family history of type 2 diabetes , body mass index , smoking status ) and the Framingham offspring study type 2 diabetes risk score ( age , sex , parental history of type 2 diabetes , body mass index , high density lipoprotein cholesterol , triglycerides , fasting glucose)— and 20 single nucleotide polymorphisms associated with susceptibility to type 2 diabetes . Cases of incident type 2 diabetes were defined on the basis of a st and ard oral glucose tolerance test , self report of a doctor ’s diagnosis , or the use of anti-diabetic drugs . Results A genetic score based on the number of risk alleles carried ( range 0 - 40 ; area under receiver operating characteristics curve 0.54 , 95 % confidence interval 0.50 to 0.58 ) and a genetic risk function in which carriage of risk alleles was weighted according to the summary odds ratios of their effect from meta-analyses of genetic studies ( area under receiver operating characteristics curve 0.55 , 0.51 to 0.59 ) did not effectively discriminate cases of diabetes . The Cambridge risk score ( area under curve 0.72 , 0.69 to 0.76 ) and the Framingham offspring risk score ( area under curve 0.78 , 0.75 to 0.82 ) led to better discrimination of cases than did genotype based tests . Adding genetic information to phenotype based risk models did not improve discrimination and provided only a small improvement in model calibration and a modest net reclassification improvement of about 5 % when added to the Cambridge risk score but not when added to the Framingham offspring risk score . Conclusion The phenotype based risk models provided greater discrimination for type 2 diabetes than did models based on 20 common independently inherited diabetes risk alleles . The addition of genotypes to phenotype based risk models produced only minimal improvement in accuracy of risk estimation assessed by recalibration and , at best , a minor net reclassification improvement . The major translational application of the currently known common , small effect genetic variants influencing susceptibility to type 2 diabetes  is likely to come from the insight they provide on causes of disease and potential therapeutic targets Background Obesity rates in the United States have escalated in recent decades and present a major challenge in public health prevention efforts . Currently , testing to identify genetic risk for obesity is readily available through several direct-to-consumer companies . Despite the availability of this type of testing , there is a paucity of evidence as to whether providing people with personal genetic information on obesity risk will facilitate or impede desired behavioral responses . Purpose We describe the key issues in the design and implementation of a r and omized controlled trial examining the clinical utility of providing genetic risk information for obesity . Methods Participants are being recruited from the Coriell Personalized Medicine Collaborative , an ongoing , longitudinal research cohort study design ed to determine the utility of personal genome information in health management and clinical decision making . The primary focus of the ancillary Obesity Risk Communication Study is to determine whether genetic risk information added value to traditional communication efforts for obesity , which are based on lifestyle risk factors . The trial employs a 2 × 2 factorial design in order to examine the effects of providing genetic risk information for obesity , alone or in combination with lifestyle risk information , on participants ’ psychological responses , behavioral intentions , health behaviors , and weight . Results The factorial design generated four experimental arms based on communication of estimated risk to participants : ( 1 ) no risk feedback ( control ) , ( 2 ) genetic risk only , ( 3 ) lifestyle risk only , and ( 4 ) both genetic and lifestyle risk ( combined ) . Key issues in study design pertained to the selection of algorithms to estimate lifestyle risk and determination of information to be provided to participants assigned to each experimental arm to achieve a balance between clinical st and ards and method ological rigor . Following the launch of the trial in September 2011 , implementation challenges pertaining to low enrollment and differential attrition became apparent and required immediate attention and modifications to the study protocol . Although monitoring of these efforts is ongoing , initial observations show a doubling of enrollment and reduced attrition . Limitations The trial is evaluating the short-term impact of providing obesity risk information as participants are followed for only 3 months . This study is built upon the structure of an existing personalized medicine study wherein participants have been provided with genetic information for other diseases . This nesting in a larger study may attenuate the effects of obesity risk information and has implication s for the generalizability of study findings . Conclusions This r and omized trial examines value of obesity genetic information , both when provided independently and when combined with lifestyle risk assessment , to motivate individuals to engage in healthy lifestyle behaviors . Study findings will guide future intervention efforts to effectively communicate genetic risk information OBJECTIVE To examine whether diabetes genetic risk testing and counseling can improve diabetes prevention behaviors . RESEARCH DESIGN AND METHODS We conducted a r and omized trial of diabetes genetic risk counseling among overweight patients at increased phenotypic risk for type 2 diabetes . Participants were r and omly allocated to genetic testing versus no testing . Genetic risk was calculated by summing 36 single nucleotide polymorphisms associated with type 2 diabetes . Participants in the top and bottom score quartiles received individual genetic counseling before being enrolled with untested control participants in a 12-week , vali date d , diabetes prevention program . Middle-risk quartile participants were not studied further . We examined the effect of this genetic counseling intervention on patient self-reported attitudes , program attendance , and weight loss , separately comparing higher-risk and lower-risk result recipients with control participants . RESULTS The 108 participants enrolled in the diabetes prevention program included 42 participants at higher diabetes genetic risk , 32 at lower diabetes genetic risk , and 34 untested control subjects . Mean age was 57.9 ± 10.6 years , 61 % were men , and average BMI was 34.8 kg/m2 , with no differences among r and omization groups . Participants attended 6.8 ± 4.3 group sessions and lost 8.5 ± 10.1 pounds , with 33 of 108 ( 30.6 % ) losing ≥5 % body weight . There were few statistically significant differences in self-reported motivation , program attendance , or mean weight loss when higher-risk recipients and lower-risk recipients were compared with control subjects ( P > 0.05 for all but one comparison ) . CONCLUSIONS Diabetes genetic risk counseling with currently available variants does not significantly alter self-reported motivation or prevention program adherence for overweight individuals at risk for diabetes Flaws in the design , conduct , analysis , and reporting of r and omised trials can cause the effect of an intervention to be underestimated or overestimated . The Cochrane Collaboration ’s tool for assessing risk of bias aims to make the process clearer and more Background : Genetic information , typically communicated in-person by genetic counselors , can be challenging to comprehend ; delivery of this information online - as is becoming more common - has the potential of increasing these challenges . Methods : To address the impact of the mode of delivery of genomic risk information , 300 individuals were recruited from the general public and r and omized to receive genomic risk information for type 2 diabetes mellitus in-person from a board-certified genetic counselor or online through the testing company 's website . Results : Participants were asked to indicate their genomic risk and overall lifetime risk as reported on their test report as well as to interpret their genomic risk ( increased , decreased , or same as population ) . For each question , 59 % of participants correctly indicated their risk . Participants who received their results in-person were more likely than those who review ed their results on-line to correctly interpret their genomic risk ( 72 vs. 47 % , p = 0.0002 ) and report their actual genomic risk ( 69 vs. 49 % , p = 0.002 ) . Conclusions : The delivery of personal genomic risk through a trained health professional result ed in significantly higher comprehension . Therefore , if the online delivery of genomic test results is to become more widespread , further evaluation of this method of communication may be needed to ensure the effective presentation of results to promote comprehension Objective : There is considerable hope that genetic susceptibility testing will motivate behavior that can prevent or reduce the risk of complex conditions such as obesity . This study examined potential behavioral consequences of such testing . Methods : Participants ( n = 249 ) were r and omly assigned to review one of four vignettes that asked them to imagine that they had been tested for their risk of becoming overweight or obese . The experimental factors were test type ( genetic versus hormone test ) and risk level ( increased versus average risk for obesity ) . Study measures included  behavioral intentions and perceived behavioral control related to eating a healthy diet  , as well as  weight locus of control .  Results : Participants assigned to the increased risk conditions indicated greater intentions to eat a healthy diet compared with participants assigned to the average risk conditions ( P < 0.02 ) . There were significant interaction effects of risk × perceived behavioral control ( P < 0.02 ) and risk × weight locus of control ( P < 0.003 ) on dietary intentions . Individuals with low perceived behavioral control or an external weight locus of control who were told to imagine they were at average risk expressed significantly lower intentions to eat a healthy diet . A three-way interaction of body mass index , family history of overweight/ 
    Output:
    
agent
This review found no clear or consistent evidence that genetic risk communication alone either raises motivation or translates into actual change in dietary intake or physical activity to reduce the risk of cardiometabolic disorders in adults .
***TASK*** the task is to summarize an input biomedical literature in six sentences 
    ***INPUT*** the input is a biomedical literature 
    ***OUTPUT*** the output is the summary of an input biomedical literature in six sentences 
    ***DOCUMENTATION*** 
    ***EXAMPLES*** 
    Input: Type 2 diabetes ( T2D ) is associated with increased risk of morbidity and premature mortality . Among those at high risk , incidence can be halved through healthy changes in behaviour . Information about genetic and phenotypic risk of T2D is now widely available . Whether such information motivates behaviour change is unknown . We aim to assess the effects of communicating genetic and phenotypic risk of T2D on risk-reducing health behaviours , anxiety , and other cognitive and emotional theory-based antecedents of behaviour change . In a parallel group , open r and omised controlled trial , approximately 580 adults born between 1950 and 1975 will be recruited from the on-going population -based , observational Fenl and Study ( Cambridgeshire , UK ) . Eligible participants will have undergone clinical , anthropometric , and psychosocial measurements , been genotyped for 23 single-nucleotide polymorphisms associated with T2D , and worn a combined heart rate monitor and accelerometer ( Actiheart ® ) continuously for six days and nights to assess physical activity .  Participants are r and omised to receive either st and ard lifestyle advice alone ( control group ) , or in combination with a genetic or a phenotypic risk estimate for T2D ( intervention groups ) . The primary outcome is objective ly measured physical activity . Secondary outcomes include self-reported diet , self-reported weight , intention to be physically active and to engage in a healthy diet , anxiety , diabetes-related worry , self-rated health , and other cognitive and emotional outcomes . Follow-up occurs eight weeks post-intervention . Values at follow-up , adjusted for baseline , will be compared between r and omised groups . This study will provide much needed evidence on the effects of providing information about the genetic and phenotypic risk of T2D . Importantly , it will be among the first to examine the impact of genetic risk information using a r and omised controlled trial design , a population -based sample , and an objective ly measured behavioural outcome . Results of this trial , along with recent evidence syntheses of similar studies , should inform policy concerning the availability and use of genetic risk information . Current Controlled Trials IS RCT Background There are few empirical data to inform the debate surrounding the use and regulation of direct-to-consumer ( DTC ) genome-wide disease risk tests . This study aim ed to determine the long term psychological , behavioural , and clinical impacts of genomic risk testing for common disease . Methods The Scripps Genomic Health Initiative is a prospect i ve longitudinal cohort study of adults who purchased the Navigenics Health Compass , a commercially available genomic test . Web based assessment s were administered at baseline , short ( 3 months ) , and long term ( 1 year ) follow-up . Results 2240 participants completed either or both follow-ups and a subset of 1325 completed long term follow-up . There were no significant differences from baseline in anxiety ( p=0.50 ) , fat intake ( p=0.34 ) , or exercise ( p=0.39 ) at long term follow-up , and 96.8 % of the sample had no test related distress . Longitudinal linear mixed model analyses were consistent with results of cross-sectional analyses . Screening test completion was associated with sharing genomic test results with a physician ( 36.0 % shared ; p<0.001 ) and perceived utility of the test ( 61.5 % high perceived utility ; p=0.002 ) , but was not associated with the genomic risk estimate values themselves . Conclusions Over a third of DTC genomic test recipients shared their results with their own physician during an approximate 1 year follow-up period , and this sharing was associated with higher screening test completion . Genomic testing was not associated with long term psychological risks , and most participants reportedly perceived the test to be of high personal utility Objectives To assess the performance of a panel of common single nucleotide polymorphisms ( genotypes ) associated with type 2 diabetes in distinguishing incident cases of future type 2 diabetes ( discrimination ) , and to examine the effect of adding genetic information to previously vali date d non-genetic ( phenotype based ) models developed to estimate the absolute risk of type 2 diabetes . Design Workplace based prospect i ve cohort study with three 5 yearly medical screenings . Participants 5535 initially healthy people ( mean age 49 years ; 33 % women ) , of whom 302 developed new onset type 2 diabetes over 10 years . Outcome measures Non-genetic variables included in two established risk models — the Cambridge type 2 diabetes risk score ( age , sex , drug treatment , family history of type 2 diabetes , body mass index , smoking status ) and the Framingham offspring study type 2 diabetes risk score ( age , sex , parental history of type 2 diabetes , body mass index , high density lipoprotein cholesterol , triglycerides , fasting glucose)— and 20 single nucleotide polymorphisms associated with susceptibility to type 2 diabetes . Cases of incident type 2 diabetes were defined on the basis of a st and ard oral glucose tolerance test , self report of a doctor ’s diagnosis , or the use of anti-diabetic drugs . Results A genetic score based on the number of risk alleles carried ( range 0 - 40 ; area under receiver operating characteristics curve 0.54 , 95 % confidence interval 0.50 to 0.58 ) and a genetic risk function in which carriage of risk alleles was weighted according to the summary odds ratios of their effect from meta-analyses of genetic studies ( area under receiver operating characteristics curve 0.55 , 0.51 to 0.59 ) did not effectively discriminate cases of diabetes . The Cambridge risk score ( area under curve 0.72 , 0.69 to 0.76 ) and the Framingham offspring risk score ( area under curve 0.78 , 0.75 to 0.82 ) led to better discrimination of cases than did genotype based tests . Adding genetic information to phenotype based risk models did not improve discrimination and provided only a small improvement in model calibration and a modest net reclassification improvement of about 5 % when added to the Cambridge risk score but not when added to the Framingham offspring risk score . Conclusion The phenotype based risk models provided greater discrimination for type 2 diabetes than did models based on 20 common independently inherited diabetes risk alleles . The addition of genotypes to phenotype based risk models produced only minimal improvement in accuracy of risk estimation assessed by recalibration and , at best , a minor net reclassification improvement . The major translational application of the currently known common , small effect genetic variants influencing susceptibility to type 2 diabetes  is likely to come from the insight they provide on causes of disease and potential therapeutic targets Background Obesity rates in the United States have escalated in recent decades and present a major challenge in public health prevention efforts . Currently , testing to identify genetic risk for obesity is readily available through several direct-to-consumer companies . Despite the availability of this type of testing , there is a paucity of evidence as to whether providing people with personal genetic information on obesity risk will facilitate or impede desired behavioral responses . Purpose We describe the key issues in the design and implementation of a r and omized controlled trial examining the clinical utility of providing genetic risk information for obesity . Methods Participants are being recruited from the Coriell Personalized Medicine Collaborative , an ongoing , longitudinal research cohort study design ed to determine the utility of personal genome information in health management and clinical decision making . The primary focus of the ancillary Obesity Risk Communication Study is to determine whether genetic risk information added value to traditional communication efforts for obesity , which are based on lifestyle risk factors . The trial employs a 2 × 2 factorial design in order to examine the effects of providing genetic risk information for obesity , alone or in combination with lifestyle risk information , on participants ’ psychological responses , behavioral intentions , health behaviors , and weight . Results The factorial design generated four experimental arms based on communication of estimated risk to participants : ( 1 ) no risk feedback ( control ) , ( 2 ) genetic risk only , ( 3 ) lifestyle risk only , and ( 4 ) both genetic and lifestyle risk ( combined ) . Key issues in study design pertained to the selection of algorithms to estimate lifestyle risk and determination of information to be provided to participants assigned to each experimental arm to achieve a balance between clinical st and ards and method ological rigor . Following the launch of the trial in September 2011 , implementation challenges pertaining to low enrollment and differential attrition became apparent and required immediate attention and modifications to the study protocol . Although monitoring of these efforts is ongoing , initial observations show a doubling of enrollment and reduced attrition . Limitations The trial is evaluating the short-term impact of providing obesity risk information as participants are followed for only 3 months . This study is built upon the structure of an existing personalized medicine study wherein participants have been provided with genetic information for other diseases . This nesting in a larger study may attenuate the effects of obesity risk information and has implication s for the generalizability of study findings . Conclusions This r and omized trial examines value of obesity genetic information , both when provided independently and when combined with lifestyle risk assessment , to motivate individuals to engage in healthy lifestyle behaviors . Study findings will guide future intervention efforts to effectively communicate genetic risk information OBJECTIVE To examine whether diabetes genetic risk testing and counseling can improve diabetes prevention behaviors . RESEARCH DESIGN AND METHODS We conducted a r and omized trial of diabetes genetic risk counseling among overweight patients at increased phenotypic risk for type 2 diabetes . Participants were r and omly allocated to genetic testing versus no testing . Genetic risk was calculated by summing 36 single nucleotide polymorphisms associated with type 2 diabetes . Participants in the top and bottom score quartiles received individual genetic counseling before being enrolled with untested control participants in a 12-week , vali date d , diabetes prevention program . Middle-risk quartile participants were not studied further . We examined the effect of this genetic counseling intervention on patient self-reported attitudes , program attendance , and weight loss , separately comparing higher-risk and lower-risk result recipients with control participants . RESULTS The 108 participants enrolled in the diabetes prevention program included 42 participants at higher diabetes genetic risk , 32 at lower diabetes genetic risk , and 34 untested control subjects . Mean age was 57.9 ± 10.6 years , 61 % were men , and average BMI was 34.8 kg/m2 , with no differences among r and omization groups . Participants attended 6.8 ± 4.3 group sessions and lost 8.5 ± 10.1 pounds , with 33 of 108 ( 30.6 % ) losing ≥5 % body weight . There were few statistically significant differences in self-reported motivation , program attendance , or mean weight loss when higher-risk recipients and lower-risk recipients were compared with control subjects ( P > 0.05 for all but one comparison ) . CONCLUSIONS Diabetes genetic risk counseling with currently available variants does not significantly alter self-reported motivation or prevention program adherence for overweight individuals at risk for diabetes Flaws in the design , conduct , analysis , and reporting of r and omised trials can cause the effect of an intervention to be underestimated or overestimated . The Cochrane Collaboration ’s tool for assessing risk of bias aims to make the process clearer and more Background : Genetic information , typically communicated in-person by genetic counselors , can be challenging to comprehend ; delivery of this information online - as is becoming more common - has the potential of increasing these challenges . Methods : To address the impact of the mode of delivery of genomic risk information , 300 individuals were recruited from the general public and r and omized to receive genomic risk information for type 2 diabetes mellitus in-person from a board-certified genetic counselor or online through the testing company 's website . Results : Participants were asked to indicate their genomic risk and overall lifetime risk as reported on their test report as well as to interpret their genomic risk ( increased , decreased , or same as population ) . For each question , 59 % of participants correctly indicated their risk . Participants who received their results in-person were more likely than those who review ed their results on-line to correctly interpret their genomic risk ( 72 vs. 47 % , p = 0.0002 ) and report their actual genomic risk ( 69 vs. 49 % , p = 0.002 ) . Conclusions : The delivery of personal genomic risk through a trained health professional result ed in significantly higher comprehension . Therefore , if the online delivery of genomic test results is to become more widespread , further evaluation of this method of communication may be needed to ensure the effective presentation of results to promote comprehension Objective : There is considerable hope that genetic susceptibility testing will motivate behavior that can prevent or reduce the risk of complex conditions such as obesity . This study examined potential behavioral consequences of such testing . Methods : Participants ( n = 249 ) were r and omly assigned to review one of four vignettes that asked them to imagine that they had been tested for their risk of becoming overweight or obese . The experimental factors were test type ( genetic versus hormone test ) and risk level ( increased versus average risk for obesity ) . Study measures included  behavioral intentions and perceived behavioral control related to eating a healthy diet  , as well as  weight locus of control .  Results : Participants assigned to the increased risk conditions indicated greater intentions to eat a healthy diet compared with participants assigned to the average risk conditions ( P < 0.02 ) . There were significant interaction effects of risk × perceived behavioral control ( P < 0.02 ) and risk × weight locus of control ( P < 0.003 ) on dietary intentions . Individuals with low perceived behavioral control or an external weight locus of control who were told to imagine they were at average risk expressed significantly lower intentions to eat a healthy diet . A three-way interaction of body mass index , family history of overweight/ 
    Output:
    