Genetic variants in the FOXO1 and ZNF469 genes are associated with keratoconus in Sweden: a case-control study.

BACKGROUND: Keratoconus (KC) is characterized by pathological thinning and bulging of the cornea that may lead to visual impairment. The etiology of sporadic KC remains enigmatic despite intensive research in recent decades. The purpose of this study was to examine the relationship between previously highlighted genetic variants associated with KC and sporadic KC in a Swedish cohort. METHODS: A total of 176 patients (age 16-70 years) with sporadic KC diagnosed by Scheimpflug-topography (Pentacam) were included. The control group (n = 418; age 70 years) was a subsample originating from the Gothenburg H70 Birth Cohort Studies of ageing. Extraction of DNA from blood samples was performed according to standard procedures, and genotyping was performed using competitive allele specific PCR (KASP) technology. A total of 11 single nucleotide polymorphisms (SNPs) were selected for analysis. RESULTS: Statistically significant associations (p = 0.005) were found between the SNPs rs2721051 and rs9938149 and sporadic KC. These results replicate earlier research that found associations between genetic variants in the FOXO1 and BANP-ZNF469 genes and sporadic KC in other populations. CONCLUSION: Genetic variations in the FOXO1 and BANP-ZNF469 genes may be involved in the pathogenesis of sporadic KC.

Association of CSF biomarkers with MRI brain changes in Alzheimer's disease.

The relation between cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) and magnetic resonance imaging (MRI) measures is poorly understood in cognitively healthy individuals from the general population. Participants' (n = 226) mean age was 70.9 years (SD = 0.4). CSF concentrations of amyloid beta (Aß)1-42, total tau (t-tau), phosphorylated tau (p-tau), neurogranin, and neurofilament light, and volumes of hippocampus, amygdala, total basal forebrain (TBF), and cortical thickness were measured. Linear associations between CSF biomarkers and MRI measures were investigated. In Aß1-42 positives, higher t-tau and p-tau were associated with smaller hippocampus (P = 0.001 and P = 0.003) and amygdala (P = 0.005 and P = 0.01). In Aß1-42 negatives, higher t-tau, p-tau, and neurogranin were associated with larger TBF volume (P = 0.001, P = 0.001, and P = 0.01). No associations were observed between the CSF biomarkers and an AD signature score of cortical thickness. AD-specific biomarkers in cognitively healthy 70-year-olds may be related to TBF, hippocampus, and amygdala. Lack of association with cortical thickness might be due to early stage of disease.

Proportion of Community-Dwelling Individuals Older Than 70 Years Eligible for Lecanemab Initiation: The Gothenburg H70 Birth Cohort Study.

OBJECTIVES: To determine the prevalence of individuals with Alzheimer disease (AD) eligible for treatment with the recently FDA-approved lecanemab based on data from a population-based sample of 70-year-olds and extrapolate an estimation of individuals eligible in Europe and the United States. METHODS: Participants from the Gothenburg H70 Birth Cohort Study with clinical data, CSF-amyloid beta 42, and brain MRI analysis were evaluated for eligibility to receive lecanemab treatment according to FDA-approved recommendations, noting factors requiring special consideration. Results were used to extrapolate the number of eligible individuals in Europe and the United States using public demographic data. RESULTS: Thirty (10.3%) of 290 participants met the indication for treatment of whom 18 (6.2%) were eligible and did not present factors requiring special consideration. Our estimate that 6.2% of all 70-year-olds in the full cohort are eligible for treatment extrapolates to an approximation that around 5.9 million Europeans and 2.2 million US residents could be eligible. DISCUSSION: Information on proportion of individuals eligible for AD treatment with lecanemab in the general public is limited. We provide information on 70-year-olds in Sweden and extrapolate these data to Europe and the United States. This study opens for larger studies on this proportion and implementation of lecanemab treatment.

Nutrient Intake and Its Association with Appendicular Total Lean Mass and Muscle Function and Strength in Older Adults: A Population-Based Study.

Treatment options for sarcopenia are currently limited, and primarily rely on two main therapeutic approaches: resistance-based physical activity and dietary interventions. However, details about specific nutrients in the diet or supplementation are unclear. We aim to investigate the relationship between nutrient intake and lean mass, function, and strength. Data were derived from the Gothenburg H70 birth cohort study in Sweden, including 719,70-year-olds born in 1944 (54.1% females). For independent variables, the diet history method (face-to-face interviews) was used to estimate habitual food intake during the preceding three months. Dependent variables were gait speed (muscle performance), hand grip strength (muscle strength), and the appendicular lean soft tissue index (ALSTI). Linear regression analyses were performed to analyze the relationship between the dependent variables and each of the covariates. Several nutrients were positively associated with ALSTI, such as polyunsaturated fatty acids (DHA, EPA), selenium, zinc, riboflavin, niacin equivalent, vitamin B12, vitamin D, iron, and protein. After correction for multiple comparisons, there were no remaining correlations with handgrip and gait speed. Findings of positive correlations for some nutrients with lean mass suggest a role for these nutrients in maintaining muscle volume. These results can be used to inform clinical trials to expand the preventive strategies and treatment options for individuals at risk of muscle loss and sarcopenia.

Temporal Muscle Thickness: A Practical Approximation for Assessing Muscle Mass in Older Adults.

OBJECTIVE: Ongoing research has evidenced the importance of muscle measurement in predicting adverse outcomes. Measurement of other muscles is promising in current research. This study aimed to determine the correlation between temporal muscle thickness (TMT) and appendicular lean soft tissue (ALSTI) in older adults. DESIGN: Cross-sectional study. SETTINGS AND PARTICIPANTS: Single cohort gathered in Gothenburg, Sweden, consisting of individuals born in 1944 (n = 1203). METHODS: We studied 657 magnetic resonance images to measure TMT. Comparisons of TMT with dual-energy X-ray absorptiometry ALSTI (kg/m2) as a reference standard were performed. Finally, TMT associations with cognition evaluated using the Mini-Mental State Examination (MMSE), gait speed, and handgrip strength were explored with linear regressions. RESULTS: The correlation between TMT and ALSTI was weak yet significant (r = 0.277, P < .001). TMT exhibited significant associations with MMSE (estimate = 0.168, P = .002), gait speed (estimate = 1.795, P < .001), and ALSTI (estimate = 0.508, P < .001). These associations varied when analyzed by sex. In women, TMT was significantly associated with gait speed (estimate = 1.857, P = .005) and MMSE (estimate = 0.223, P = .003). In men, TMT scores were significantly correlated with ALSTI scores (estimate = 0.571, P < .001). CONCLUSION AND IMPLICATIONS: Repurposing head images can be an accessible alternative to detect muscle mass and ultimately detect sarcopenia. These studies have the potential to trigger interventions or further evaluation to improve the muscle and overall health of individuals. However, additional research is warranted before translating these findings into clinical practice.

Assessing CT-based Volumetric Analysis via Transfer Learning with MRI and Manual Labels for Idiopathic Normal Pressure Hydrocephalus.

Background: Brain computed tomography (CT) is an accessible and commonly utilized technique for assessing brain structure. In cases of idiopathic normal pressure hydrocephalus (iNPH), the presence of ventriculomegaly is often neuroradiologically evaluated by visual rating and manually measuring each image. Previously, we have developed and tested a deep-learning-model that utilizes transfer learning from magnetic resonance imaging (MRI) for CT-based intracranial tissue segmentation. Accordingly, herein we aimed to enhance the segmentation of ventricular cerebrospinal fluid (VCSF) in brain CT scans and assess the performance of automated brain CT volumetrics in iNPH patient diagnostics. Methods: The development of the model used a two-stage approach. Initially, a 2D U-Net model was trained to predict VCSF segmentations from CT scans, using paired MR-VCSF labels from healthy controls. This model was subsequently refined by incorporating manually segmented lateral CT-VCSF labels from iNPH patients, building on the features learned from the initial U-Net model. The training dataset included 734 CT datasets from healthy controls paired with T1-weighted MRI scans from the Gothenburg H70 Birth Cohort Studies and 62 CT scans from iNPH patients at Uppsala University Hospital. To validate the model's performance across diverse patient populations, external clinical images including scans of 11 iNPH patients from the Universitatsmedizin Rostock, Germany, and 30 iNPH patients from the University of Alabama at Birmingham, United States were used. Further, we obtained three CT-based volumetric measures (CTVMs) related to iNPH. Results: Our analyses demonstrated strong volumetric correlations (ϱ=0.91, p<0.001) between automatically and manually derived CT-VCSF measurements in iNPH patients. The CTVMs exhibited high accuracy in differentiating iNPH patients from controls in external clinical datasets with an AUC of 0.97 and in the Uppsala University Hospital datasets with an AUC of 0.99. Discussion: CTVMs derived through deep learning, show potential for assessing and quantifying morphological features in hydrocephalus. Critically, these measures performed comparably to gold-standard neuroradiology assessments in distinguishing iNPH from healthy controls, even in the presence of intraventricular shunt catheters. Accordingly, such an approach may serve to improve the radiological evaluation of iNPH diagnosis/monitoring (i.e., treatment responses). Since CT is much more widely available than MRI, our results have considerable clinical impact.

Attrition in the Gothenburg H70 birth cohort studies, an 18-year follow-up of the 1930 cohort.

Background: Longitudinal studies are essential to understand the ageing process, and risk factors and consequences for disorders, but attrition may cause selection bias and impact generalizability. We describe the 1930 cohort of the Gothenburg H70 Birth Cohort Studies, followed from age 70 to 88, and compare baseline characteristics for those who continue participation with those who die, refuse, and drop out for any reason during follow-up. Methods: A population-based sample born 1930 was examined with comprehensive assessments at age 70 (N = 524). The sample was followed up and extended to increase sample size at age 75 (N = 767). Subsequent follow-ups were conducted at ages 79, 85, and 88. Logistic regression was used to analyze baseline characteristics in relation to participation status at follow-up. Results: Refusal to participate in subsequent examinations was related to lower educational level, higher blood pressure, and lower scores on cognitive tests. Both attrition due to death and total attrition were associated with male sex, lower educational level, smoking, ADL dependency, several diseases, poorer lung function, slower gait speed, lower scores on cognitive tests, depressive symptoms, and a larger number of medications. Attrition due to death was also associated with not having a partner. Conclusions: It is important to consider different types of attrition when interpreting results from longitudinal studies, as representativeness and results may be differently affected by different types of attrition. Besides reducing barriers to participation, methods such as imputation and weighted analyses can be used to handle selection bias.