Autoimmune diseases in primary sclerosing cholangitis and their first-degree relatives.

BACKGROUND AND AIMS: Primary sclerosing cholangitis (PSC) is linked to inflammatory bowel disease (IBD). However, there is limited overlap between IBD and PSC risk genes, but a stronger association between PSC and other autoimmune conditions. We aimed to assess the coexistence and familial association of autoimmune disorders in PSC, and the influence of autoimmune comorbidity on severe outcomes. APPROACH AND RESULTS: In a matched cohort study, 1378 individuals with PSC and 13,549 general population comparators and their first-degree relatives were evaluated. National registries provided data on diagnoses and outcomes (liver transplantation, hepatobiliary cancer, and liver-related death). The OR of autoimmune disease was estimated by logistic regression. The Fine and Gray competing risk regression estimated HRs for severe outcomes. The prevalence of non-IBD, non-autoimmune hepatitis, and autoimmune disease was 18% in PSC and 11% in comparators, OR: 1.77 (95% CI: 1.53-2.05). Highest odds were seen for celiac disease [OR: 4.36 (95% CI: 2.44-7.49)], sarcoidosis [OR: 2.74 (95% CI: 1.29-5.33)], diabetes type 1 [OR: 2.91 (95% CI: 2.05-4.05)], and autoimmune skin disease [OR: 2.15 (95% CI: 1.52-2.96)]. First-degree relatives of individuals with PSC had higher odds of developing IBD, autoimmune hepatitis, and any autoimmune disease than relatives of the comparators [OR: 3.25 (95% CI: 2.68-3.91); OR: 5.94 (95% CI: 2.82-12.02); OR: 1.34 (95% CI: 1.19-1.50)]. Autoimmune comorbidity in PSC was not associated with poorer outcomes [HR: 0.96 (95% CI: 0.71-1.28)]. CONCLUSIONS: Individuals with PSC and their first-degree relatives had higher odds of autoimmune disease compared to matched comparators. This finding provides validation for prior genetic discoveries at a phenotypic level. Autoimmune comorbidity did not impact severe outcomes.

Breastfeeding, cognitive ability, and residual confounding: A comment on studies by Pereyra-Elìas et al.

Recent studies found positive effects of breastfeeding on the child's cognitive ability and educational outcomes even when adjusting for maternal cognitive ability in addition to a large number of other potential confounders. The authors claimed an important role of breastfeeding for the child's cognitive scores. However, it is well known that error in the measurement of confounders can leave room for residual confounding. In the present reanalyses, we found incongruent effects indicating simultaneous increasing and decreasing effects of breastfeeding on the child's cognitive ability and educational outcomes. We conclude that findings in the reanalyses may have been due to residual confounding due to error in the measurement of maternal cognitive ability. Consequently, it appears premature to assume a genuine increasing effect of breastfeeding on the child's cognitive ability and educational outcomes and claims in this regard may be challenged.

The cascade of care for patients with chronic hepatitis delta in Southern Stockholm, Sweden for the past 30 years.

BACKGROUND AND AIMS: Previous studies have shown suboptimal screening for hepatitis D virus (HDV) among patients with chronic hepatitis B (CHB). This study presents the cascade of care for HDV infection in a major secondary referral centre in Southern Stockholm, Sweden. METHODS: HBsAg+ve patients attending Karolinska University Hospital (KUH) from 1992 to 2022 were identified. The prevalence of anti-HDV and/or HDV RNA positivity, interferon (IFN) therapy and maintained virological responses (MVR) after HDV treatment were assessed. Also, time to anti-HDV testing was analysed in relation to liver-related outcomes with logistic regression. RESULTS: Among 4095 HBsAg+ve persons, 3703 (90.4%) underwent an anti-HDV screening; within a median of 1.8 months (range 0.0-57.1) after CHB diagnosis. This screening rate increased over time, to 97.9% in the last decade. Overall, 310 (8.4%) were anti-HDV+ve, of which 202 (65.2%) were HDV RNA+ve. Eighty-five (42%) received IFN, and 9 (10.6%) achieved MVR at the last follow-up. The predictive factors for anti-HDV screening were Asian origin, diagnosis after the year 2012, HIV co-infection (negative factor) and HBV DNA level < 2000 IU/mL in univariable analysis, while HIV co-infection was the only remaining factor in multivariable analysis. Delayed anti-HDV test >5 years was independently associated with worsened liver-related outcomes (adjusted odds ratio = 7.6, 95% CI 1.8-31.6). CONCLUSION: Higher frequency of HDV screening than previously published data could be seen among CHB patients at KUH in a low-endemic setting. Receiving a delayed screening test seems to be associated with worse outcomes, stressing the need of a strategy for timely HDV diagnosis.

Age-specific and sex-specific risks for HCC in African-born persons with chronic hepatitis B without cirrhosis.

BACKGROUND: The international recommendations of HCC surveillance for African-born persons with chronic hepatitis B (CHB) without cirrhosis are divergent, probably due to scarce data on incidence rate (IR) for HCC. METHODS: We assembled a cohort with prospectively collected data of Swedish residents of African origin with diagnosed CHB without cirrhosis at baseline from 1990 to 2015. Data from nationwide registers were used to calculate the sex-specific IR and IR ratio (incidence rate ratios) in relation to age, comorbidities, and birth region, using a generalized linear model with a log-link function and Poisson distribution. RESULTS: Among 3865 African-born persons with CHB without cirrhosis at baseline, 31 (0.8%; 77.4% men) developed HCC during a median of 11.1 years of follow-up, with poor survival after HCC diagnosis. The mean age at HCC diagnosis was 46.8 (SD±14.7; range 23-79) in men. HCC IR exceeded the recommended surveillance threshold of 0.2%/year at ages 54 and 59 years in men and women, respectively, and at ages 20-40 years if HCV or HDV co-infection was present. African-born men with CHB had an incidence rate ratios of 10.6 (95% CI 4.4-31.5) for HCC compared to matched African-born peers without CHB, and an incidence rate ratios of 35.3 (95% CI 16.0-88.7) compared to a matched general population. CONCLUSIONS: African-born men with CHB without cirrhosis reached an IR of 0.2%/year between 50 and 60 years, and at younger ages if HCV or HDV co-infection was present. Our findings need further confirmation, and new cost-effectiveness analyses specific for young populations are needed, to provide personalized and cost-effective HCC surveillance.

Unmasking artifactual links: A reanalysis reveals No direct causal relationship between self-esteem and quality of social relations.

A meta-analysis conducted by Harris and Orth (2020) found positive prospective cross-lagged effects between quality of social relations and self-esteem in included longitudinal studies. Harris and Orth concluded that the link between self-esteem and quality of social relations is reciprocal and characterized by a positive feedback loop. However, meta-analytic effects were estimated while controlling for a prior measurement of the outcome and such effects are known to be susceptible to artifactual (i.e. spurious) effects due to correlations with measurement errors and reversion to mediocrity. We reanalyzed the same data and found paradoxical effects indicating, simultaneously, both increasing and decreasing effects between self-esteem and social relations. These findings suggest that prospective effects between self-esteem and quality of social relations are artifactual rather than due to a true reciprocal effect. Thus, these findings have important theoretical implications and challenge both the risk regulation model, which posits that self-esteem has a causal effect on quality of social relations, and the sociometer theory, which claims that quality of relations is the cause and self-esteem the effect. The present results prompt further investigation into the underlying mechanisms driving these artifactual associations. Additionally, the study highlights the importance of considering methodological limitations in future meta-analyses to improve the accuracy of causal inferences.

Dangers of including outcome at baseline as a covariate in latent change score models: Results from simulations and empirical re-analyses.

Latent change score modeling is a type of structural equation modeling used for estimating change over time. Often change is regressed on the initial value of the outcome variable. However, similarly to other regression analyses, this procedure may be susceptible to regression to the mean. The present study employed simulations as well as re-analyses of previously published data, claimed to indicate reciprocal promoting effects of vocabulary and matrix reasoning on each other's longitudinal development. Both in simulations and empirical re-analyses, when adjusting for initial value on the outcome, latent change score modeling tended to indicate an effect of a predictor on the change in an outcome even when no change had taken place. Furthermore, analyses tended to indicate a paradoxical effect on change both forward and backward in time. We conclude that results from latent change score modeling are susceptible to regression to the mean when adjusting for the initial value on the outcome. Researchers are recommended not to regress change on the initial value included in the calculation of the change score when employing latent change score modeling but, instead, to define this parameter as a covariance.

Questioning the vulnerability model: Prospective associations between low self-esteem and subsequent depression ratings may be spurious.

BACKGROUND: According to the vulnerability model, low self-esteem makes people more depressed. Support for the vulnerability model comes almost exclusively from analyses using cross-lagged panel models, showing a negative effect of initial self-esteem on subsequent depression ratings when adjusting for initial depression. However, it is well known that such adjusted effects are susceptible to regression toward the mean. METHODS: Data from four waves of measurements in five different samples (total N = 2703) were analyzed with two different cross-lagged panel models, two different random intercept cross-lagged panel models, and two different latent change score models, predicting change forwards as well as backwards in time. RESULTS: High initial self-esteem predicted both decreased and increased depression ratings between measurements and an increase in self-esteem between measurements predicted a concurrent decrease in depression ratings. LIMITATIONS: Only data from two western countries, Switzerland and USA, were analyzed. Whether the main finding, that a prospective effect of self-esteem on subsequent depression ratings might be spurious, applies to other countries and cultures remains an open question. CONCLUSIONS: Due to the incongruent results, any causal effect of self-esteem on depression ratings, and thus the vulnerability model as such, cannot be corroborated by the data and models analyzed here. Instead, we propose, tentatively, that prospective associations between self-esteem and depression ratings may be spurious due to a combination of reasons, including regression toward the mean. The indication that depression might not be affected by measures to improve individuals' self-esteem is of clinical relevance.

Regression to the mean in latent change score models: an example involving breastfeeding and intelligence.

BACKGROUND: Latent change score models are often used to study change over time in observational data. However, latent change score models may be susceptible to regression to the mean. Earlier observational studies have identified a positive association between breastfeeding and child intelligence, even when adjusting for maternal intelligence. METHOD: In the present study, we investigate regression to the mean in the case of breastfeeding and intelligence of children. We used latent change score modeling to analyze intergenerational change in intelligence, both from mothers to children and backward from children to mothers, in the 1979 National Longitudinal Survey of Youth (NLSY79) dataset (N = 6283). RESULTS: When analyzing change from mothers to children, breastfeeding was found to have a positive association with intergenerational change in intelligence, whereas when analyzing backward change from children to mothers, a negative association was found. CONCLUSIONS: These discrepant findings highlight a hidden flexibility in the analytical space and call into question the reliability of earlier studies of breastfeeding and intelligence using observational data.

Sleepy drivers on a slippery road: A pilot study using a driving simulator.

Sleepy drivers have problems with keeping the vehicle within the lines, and might often need to apply a sudden or hard corrective steering wheel movement. Such movements, if they occur while driving on a slippery road, might increase the risk of ending off road due to the unforgiving nature of slippery roads. We tested this hypothesis. Twelve young men participated in a driving simulator experiment with two counterbalanced conditions; dry versus slippery road × day (alert) versus night (sleepy) driving. The participants drove 52.5 km on a monotonous two-lane highway and rated their sleepiness seven times using the Karolinska Sleepiness Scale. Blink durations were extracted from an electrooculogram. The standard deviation of lateral position and the smoothness of steering events were measures of driving performance. Each outcome variable was analysed with mixed-effect models with road condition, time-of-day and time-on-task as predictors. The Karolinska Sleepiness Scale increased with time-on-task (p < 0.001) and was higher during night drives (p < 0.001), with a three-way interaction suggesting a small increased sleepiness with driving time at night with slippery road conditions (p = 0.012). Blink durations increased with time-on-task (p < 0.01) with an interaction between time-of-day and road condition (p = 0.040) such that physiological sleepiness was lower for sleep-deprived participants in demanding road conditions. The standard deviation of lateral position increased with time-on-task (p = 0.026); however, during night driving it was lower on a slippery road (p = 0.025). The results indicate that driving in demanding road condition (i.e. slippery road) might further exhaust already sleepy drivers, although this is not clearly reflected in driving performance.

A comparison of models with weight, height, and BMI as predictors of mortality.

INTRODUCTION: Body mass index (BMI) is a composite variable of weight and height, often used as a predictor of health outcomes, including mortality. The main purpose of combining weight and height in one variable is to obtain a measure of obesity independent of height. It is however unclear how accurate BMI is as a predictor of mortality compared with models including both weight and height or a weight × height interaction as predictors. METHODS: The current study used conscription data on weight, height, and BMI of Swedish men (N = 48,904) in 1969/70 as well as linked data on mortality (3442 deaths) between 1969 and 2008. Cox proportional hazard models including combinations of weight, height, and BMI at conscription as predictors of subsequent all-cause and cause-specific mortality were fitted to data. RESULTS: An increase by one standard deviation on weight and BMI were associated with an increase in hazard for all-cause mortality by 5.4% and 11.5%, respectively, while an increase by one standard deviation on height was associated with a decrease in hazard for all-cause mortality by 9.4%. The best-fitting model indicated lowest predicted all-cause mortality for those who weighed 60.5 kg at conscription, regardless of height. Further analyses of cause-specific mortality suggest that this weight seems to be a compromise between lower optimal weights to avoid cancer and CVD mortality and a higher optimal weight to not die by suicide. CONCLUSIONS: According to the present findings, there are several ways to make better use of measured weight and height than to calculate BMI when predicting mortality.

Quantifying Cognitive Impairment After Sleep Deprivation at Different Times of Day: A Proof of Concept Using Ultra-Short Smartphone-Based Tests.

Cognitive functioning is known to be impaired following sleep deprivation and to fluctuate depending on the time of day. However, most methods of assessing cognitive performance remain impractical for environments outside of the lab. This study investigated whether 2-min smartphone-based versions of commonly used cognitive tests could be used to assess the effects of sleep deprivation and time of day on diverse cognitive functions. After three nights of normal sleep, participants (N = 182) were randomised to either one night of sleep deprivation or a fourth night of normal sleep. Using the Karolinska WakeApp (KWA), participants completed a battery of 2-min cognitive tests, including measures of attention, arithmetic ability, episodic memory, working memory, and a Stroop test for cognitive conflict and behavioural adjustment. A baseline measurement was completed at 22:30 h, followed by three measurements the following day at approximately 08:00 h, 12:30 h, and 16:30 h. Sleep deprivation led to performance impairments in attention, arithmetic ability, episodic memory, and working memory. No effect of sleep deprivation was observed in the Stroop test. There were variations in attention and arithmetic test performance across different times of day. The effect of sleep deprivation on all cognitive tests was also found to vary at different times of day. In conclusion, this study shows that the KWA's 2-min cognitive tests can be used to detect cognitive impairments following sleep deprivation, and fluctuations in cognitive performance relating to time of day. The results demonstrate the potential of using brief smartphone-based tasks to measure a variety of cognitive abilities within sleep and fatigue research.

The new accounting for expected adjusted effect test (AEAE test) has higher positive predictive value than a zero-order significance test.

OBJECTIVE: The present simulation study aimed to assess positive predictive value (PPV) and negative predictive value (NPV) for our newly introduced Accounting for Expected Adjusted Effect test (AEAE test) and compare it to PPV and NPV for a traditional zero-order significance test. RESULTS: The AEAE test exhibited greater PPV compared to a traditional zero-order significance test, especially with a strong true adjusted effect, low prior probability, high degree of confounding, large sample size, high reliability in the measurement of predictor X and outcome Y, and low reliability in the measurement of confounder Z. The zero-order significance test, on the other hand, exhibited higher NPV, except for some combinations of high degree of confounding and large sample size, or low reliability in the measurement of Z and high reliability in the measurement of X/Y, in which case the zero-order significance test can be completely uninformative. Taken together, the findings demonstrate desirable statistical properties for the AEAE test compared to a traditional zero-order significance test.

Accounting for Expected Adjusted Effect.

The point that adjustment for confounders do not always guarantee protection against spurious findings and type 1-errors has been made before. The present simulation study indicates that for traditional regression methods, this risk is accentuated by a large sample size, low reliability in the measurement of the confounder, and high reliability in the measurement of the predictor and the outcome. However, this risk might be attenuated by calculating the expected adjusted effect, or the required reliability in the measurement of the possible confounder, with equations presented in the present paper.

Sleepiness as motivation: a potential mechanism for how sleep deprivation affects behavior.

STUDY OBJECTIVES: To determine how sleepiness and sleep deprivation drive the motivation to engage in different behaviors. METHODS: We studied the sleepiness of 123 participants who had been randomized to sleep deprivation or normal sleep, and their willingness to engage in a range of everyday behaviors. RESULTS: Self-reported sleepiness was a strong predictor of the motivation to engage in sleep-preparatory behaviors such as shutting one's eyes (OR = 2.78, 95% CI: 2.19-3.52 for each step up on the Karolinska Sleepiness Scale) and resting (OR = 3.20, CI: 2.46-4.16). Sleepiness was also related to the desire to be cared for by a loved one (OR = 1.49, CI: 1.22-1.82), and preparedness to utilize monetary and energy resources to get to sleep. Conversely, increased sleepiness was associated with a decreased motivation for social and physical activities (e.g. be with friends OR = 0.71, CI: 0.61-0.82; exercise OR = 0.65, CI: 0.56-0.76). Sleep deprivation had similar effects as sleepiness on these behaviors. Neither sleepiness nor sleep deprivation had strong associations with hunger, thirst, or food preferences. CONCLUSIONS: Our findings indicate that sleepiness is a dynamic motivational drive that promotes sleep-preparatory behaviors and competes with other drives and desired outcomes. Consequently, sleepiness may be a central mechanism by which impaired alertness, for example, due to insufficient sleep, contributes to poor quality of life and adverse health. We propose that sleepiness helps organize behaviors toward the specific goal of assuring sufficient sleep, in competition with other needs and incentives. A theoretical framework on sleepiness and its behavioral consequences are likely to improve our understanding of several disease mechanisms.

Threshold-like associations as a function of disturbance.

According to the intelligence-creativity threshold hypothesis, there should be a positive association between intelligence and creative potential up to a certain point, the threshold, after which a further increase in intelligence should have no association with creativity. In the present simulation study, the measured intelligence and creativity of virtual subjects were affected by their true abilities as well as a disturbance factor that varied in magnitude between subjects. The results indicate that the hypothesized threshold-like association could be due to some disturbing factor, for example, low motivation, illness, or linguistic confusion, that varies between individuals and that affects both measured intelligence and measured creativity, especially if the actual association between intelligence and creativity is weak. This, together with previous negative findings, calls the validity of the intelligence-creativity threshold hypothesis into question.

The pain alarm response - an example of how conscious awareness shapes pain perception.

Pain is subjective and largely shaped by context, yet, little is known about the boundaries for such influences, in particular in relation to conscious awareness. Here, we investigated processing of noxious stimuli during sleep. Four experiments were performed where participants (n = 114) were exposed to repetitions of noxious heat, either when awake or during sleep. A test-phase followed where participants were awake and exposed to painful stimuli and asked to rate pain. Two control experiments included only the test-phase, without any prior pain exposures. Participants in the awake condition rated all test-phase stimuli the same. Conversely, participants who had been sleeping, and thus unaware of getting noxious heat, displayed heightened pain during the first part of the test-phase. This heightened reaction to noxious stimuli-a pain alarm response-was further pronounced in the control conditions where participants were naïve to noxious heat. Results suggest that the pain alarm response is partly dependent on conscious awareness.

Sleep during naturally occurring respiratory infections: A pilot study.

There is strong experimental support that infections increase the drive for sleep in animals, and it is widely believed that more sleep is part of an adaptive immune response. While respiratory infections (RI) are very prevalent in humans, there is a striking lack of systematic knowledge on how it affects sleep. We recruited 100 people, among whom 28 became sick with an RI during the study period (fulfilling criteria for influenza-like illness, ILI, or acute respiratory infection, ARI). We measured sick participants' sleep at home, both objectively (actigraphy) and subjectively (diary ratings), for one week as well as four weeks later when healthy. During the week with RI, people spent objectively longer time in bed and had a longer total sleep time compared to the healthy week. During the infection, participants also had more awakenings, but no significant differences in sleep latency or sleep efficiency. While sick, people also reported increased difficulties falling asleep, worse sleep quality, more restless sleep and more shallow sleep, while they did not report sleep to be less sufficient. Most problems occurred at the beginning of the sickness week, when symptoms were strong, and showed signs of recovery thereafter (as indicated by interactions between condition and day/night of data collection for all the 10 sleep outcomes). The degree of symptoms of RI was related to a worse sleep quality and more restless sleep, but not to any of the objective sleep outcomes or the other subjective sleep variables. Having a higher body temperature was not significantly related to any of the sleep variables. This study suggests that having a respiratory infection is associated with spending more time in bed and sleeping longer, but also with more disturbed sleep, both objectively and subjectively. This novel study should be seen as being of pilot character. There is a need for larger studies which classify pathogen type and include baseline predictors, or that manipulate sleep, in order to understand whether the sleep alterations seen during infections are adaptive and whether sleep interventions could be used to improve recovery from respiratory infections.

Predicting the Effect of a Predictor When Controlling for Baseline.

The present simulation study indicates that a method where the regression effect of a predictor (X) on an outcome at follow-up (Y1) is calculated while adjusting for the outcome at baseline (Y0) can give spurious findings, especially when there is a strong correlation between X and Y0 and when the test-retest correlation between Y0 and Y1 is relatively weak. Researchers wishing to avoid spurious findings and Type 1 errors should be aware of this phenomenon and are recommended to verify found effects by an unadjusted effect of X on the Y1-Y0 difference.