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Adolescents who are actively requesting Huntington's predictive testing of their own accord pose a dilemma to those providing testing. In the absence of empirical evidence as regards the impact of genetic testing on minors, current policy and guidelines, based on the ethical principles of non-maleficence and respect for individual autonomy and confidentiality, generally exclude the testing of minors. It is argued that adherence to an age based exclusion criterion in Huntington's disease predictive testing protocols is out of step with trends in UK case law concerning minors' consent to medical treatment. Furthermore, contributions from developmental psychology and research into adolescents' decision making competence suggest that adolescents can make informed choices about their health and personal lives. Criteria for developing an assessment approach to such requests are put forward and the implications of a case by case evaluation of competence to consent in terms of clinicians' tolerance for uncertainty are discussed.

This paper reflects on experience gained from presymptomatic testing for Huntington disease. An approach is presented which considers the role of the clinician and aims of the interview. Irrespective of the disease being tested for, it is suggested that the psychological aim of presymptomatic testing is to foster emotional insight and understanding that will help clients in their decision‐making process about testing and their subsequent adjustment to the result. Based on these aims the process of presymptomatic testing, counseling is considered in terms of clarification, consideration, education, and reflection, followed by decision making. Practical approaches are discussed and illustrated with clinical examples.

Predictive genetic testing for Huntington's disease has been available in Cardiff since 1987 using linked genetic markers, and since 1993 using direct mutation testing, which can also be used as a diagnostic test. During this period there have been numerous referrals that have required liaison with psychiatric services at all stages of the testing programme. A series of cases was selected to highlight issues from both genetic prediction and diagnosis that are relevant to psychiatric practice and have arisen during the testing programme. Issues have been raised concerning competence to consent to testing in the context of psychotic illness; depression and suicidal ideation in test candidates; requests for testing from third parties such as psychiatrists, social services and the courts; and testing of children. As genetic testing becomes possible for more disorders the lessons learned from Huntington's disease will provide valuable guidelines for counselling.

AbstractObjectivesTo provide updated evidence about the risk of cervical intraepithelial neoplasia grade 3 or higher (CIN3+) and cervical cancer after a negative human papillomavirus (HPV) test in primary cervical screening, by age group and test assay.DesignObservational study.SettingReal world data from the English HPV screening pilot’s first and second rounds (2013-16, follow-up to end of 2019).Participants1 341 584 women.InterventionsCervical screening with HPV testing or liquid based cytological testing (cytology or smear tests). Women screened with cytology were referred to colposcopy after high grade cytological abnormalities or after borderline or low grade abnormalities combined with a positive HPV triage test. Women screened with HPV testing who were positive were referred at baseline if their cytology triage test showed at least borderline abnormalities or after a retest (early recall) at 12 and 24 months if they had persistent abnormalities.Main outcome measuresDetection of CIN3+ and cervical cancer after a negative HPV test.ResultsFor women younger than 50 years, second round detection of CIN3+ in this study was significantly lower after a negative HPV screen in the first round than after cytology testing (1.21/1000 v 4.52/1000 women screened, adjusted odds ratio 0.26, 95% confidence interval 0.23 to 0.30), as was the risk of interval cervical cancer (1.31/100 000 v 2.90/100 000 woman years, adjusted hazard ratio 0.44, 0.23 to 0.84). Risk of an incident CIN3+ detected at the second screening round in the pilot five years after a negative HPV test was even lower in women older than 50 years, than in three years in women younger than 50 years (0.57/1000 v 1.21/1000 women screened, adjusted odds ratio 0.46, 0.27 to 0.79). Women with negative HPV tests at early recall after a positive HPV screening test without cytological abnormalities had a higher detection rate of CIN3+ at the second routine recall than women who initially tested HPV negative (5.39/1000 v 1.21/1000 women screened, adjusted odds ratio 3.27, 95% confidence interval 2.21 to 4.84). Detection after a negative result on a clinically validated APTIMA mRNA HPV test was similar to that after clinically validated cobas and RealTime DNA tests (for CIN3+ at the second round 1.32/1000 v 1.14/1000 women screened, adjusted odds ratio 1.05, 0.73 to 1.50).ConclusionsThese data support an extension of the screening intervals, regardless of the test assay used: to five years after a negative HPV test in women aged 25-49 years, and even longer for women aged 50 years and older. The screening interval for HPV positive women who have negative HPV tests at early recall should be kept at three years.

Due to the high prevalence of Alzheimer's disease (AD) in adults with Down syndrome (DS), trisomy 21 is now considered a genetic form of AD (DSAD). A better understanding of factors that can prevent or delay AD is vital to improve outcomes for adults with DS. In this narrative review, we apply AD and cognitive aging research frameworks to study resistance and resilience in DSAD. Given the variability in the timing of pathology and symptoms, we discuss the evidence supporting the role of genetic, biological, socio‐behavioral, lifestyle, and environmental factors in resistance and resilience to DSAD. We also consider how co‐occurring health conditions in DS may influence resistance and resilience, and how methods from AD research can be applied to DSAD. Ultimately, this framework aims to guide future research and translate findings into clinical interventions to improve outcomes in DSAD. Highlights Definitions of resistance and resilience in the genetic form of Alzheimer's disease (DSAD) are proposed for guiding the field. Variability in the timing of AD pathology and symptoms suggests the potential for resistance and resilience mechanisms in DSAD. Genetic, biological, socio‐behavioral, lifestyle, and environmental factors have the potential to build resistance or resilience in DSAD. Future research will require longitudinal and experimental designs, life course approaches, and large cohort studies.

Background Late‐life cognitive trajectories display heterogeneity between individuals and across cognitive domains. We aimed to identify latent classes of cognitive trajectories among three cognitive domains (memory, executive function, and language) and to investigate their association with baseline demographic and clinical characteristics. Method Harmonized data were obtained from 14 longitudinal cohorts of cognitive aging and dementia. Participants were restricted to those with at least 3 observations for each domain (memory, language and executive function). We developed three latent class linear mixed models, whereby each composite domain was modeled as both a linear and quadratic function of age. Separate models were developed with 1 through 5 classes. We assessed goodness of fit through a comparison of class proportions, AIC, BIC, and entropy. Baseline variables were compared across classes, with ANOVA for continuous and Chi‐square for categorical variables. Result We included 38,358 participants (73% non‐Hispanic white, 41% male, age=73 ± 9 years, education = 15 ± 4, mild cognitive impairment=19%, Alzheimer's disease = 14%, APOE‐ε4=31%, APOE‐ε2=13%) (Table 1). Across domains, the 4‐class model displayed the best performance (Figure 1) including non‐decliners, slow decliners, steady decliners, and rapid decliners. The memory classes deviated from the other two domains with the rapid decliners class displaying poor performance at younger ages with a less precipitous decline, whereas the rapid decline group in the other two domains declined rapidly with age. Across domains, the non‐decliners had the highest proportion of non‐Hispanic Black, cognitively unimpaired, ε2 carriers, and lowest proportion of ε4 carriers. Slow decliners were older and included more ε2 carriers. Steady decliners had the second highest proportion of AD at baseline and had the highest or second highest proportion of ε4 carriers. Rapid decliners had the highest proportion of AD at baseline, and the highest or second highest proportion of ε4 carriers. Conclusion While multiple subgroups move from cognitively normal to dementia, our latent class approach highlights subtypes that decline at different times and at different rates. Future work will seek to integrate disease time into models, clarify the stability of the observed subgroups of decliners, and characterize the neuropathological and neuroimaging features that contribute to the distinct etiologies of decline across domains.

Late-life cognitive trajectories display heterogeneity between individuals and across cognitive domains. We aimed to identify latent classes of cognitive trajectories among three cognitive domains (memory, executive function, and language) and to investigate their association with baseline demographic and clinical characteristics. Harmonized data were obtained from 14 longitudinal cohorts of cognitive aging and dementia. Participants were restricted to those with at least 3 observations for each domain (memory, language and executive function). We developed three latent class linear mixed models, whereby each composite domain was modeled as both a linear and quadratic function of age. Separate models were developed with 1 through 5 classes. We assessed goodness of fit through a comparison of class proportions, AIC, BIC, and entropy. Baseline variables were compared across classes, with ANOVA for continuous and Chi-square for categorical variables. We included 38,358 participants (73% non-Hispanic white, 41% male, age=73 ± 9 years, education = 15 ± 4, mild cognitive impairment=19%, Alzheimer's disease = 14%, APOE-ε4=31%, APOE-ε2=13%) (Table 1). Across domains, the 4-class model displayed the best performance (Figure 1) including non-decliners, slow decliners, steady decliners, and rapid decliners. The memory classes deviated from the other two domains with the rapid decliners class displaying poor performance at younger ages with a less precipitous decline, whereas the rapid decline group in the other two domains declined rapidly with age. Across domains, the non-decliners had the highest proportion of non-Hispanic Black, cognitively unimpaired, ε2 carriers, and lowest proportion of ε4 carriers. Slow decliners were older and included more ε2 carriers. Steady decliners had the second highest proportion of AD at baseline and had the highest or second highest proportion of ε4 carriers. Rapid decliners had the highest proportion of AD at baseline, and the highest or second highest proportion of ε4 carriers. While multiple subgroups move from cognitively normal to dementia, our latent class approach highlights subtypes that decline at different times and at different rates. Future work will seek to integrate disease time into models, clarify the stability of the observed subgroups of decliners, and characterize the neuropathological and neuroimaging features that contribute to the distinct etiologies of decline across domains.