The Rotterdam Study: 2010 objectives and design update

Metabolic syndrome, radiographic osteoarthritis progression and chronic pain of the knee among men and women from the general population: The Rotterdam study

OBJECTIVE

Although a relationship between osteoarthritis and components of metabolic syndrome (MetS) has been suggested, most of the results have been cross-sectional. We, therefore, aimed to investigate the sex-specific longitudinal association of (components of) MetS with progression of radiographic osteoarthritis and chronic pain in the knee joints in a large prospective cohort.

METHOD

In the large population-based Rotterdam study of up to 6,138 individuals, median follow-up time 5.7 (IQR 5.5) years, we examined the relation between MetS and its components (abdominal obesity, high triglycerides, low high-density lipoprotein, elevated blood pressure, and type 2 diabetes) with the progression of osteoarthritis using generalized estimating equations, generalized linear models and competing risk analysis. Analyses were stratified for sex. Covariates adjusted for: age, smoking, alcohol use, education, sub-cohort, baseline K/L grade, months between radiographs and BMI.

RESULTS

The presence of MetS (37.6 % in men, 39 % in women) and elevated blood pressure was associated with an increased risk of knee osteoarthritis progression in both men and women. MetS was associated with an increased risk of incident chronic knee pain (CKP) in men. In addition, abdominal obesity and high triglycerides showed higher riskfor incidence of CKP in men,but not in women. The associations were attenuated and no longer significant after BMI-adjustment, except for the association of MetS and high triglycerides with incidence of CKP in men that stayed significant (OR 1.04, 95 %CI 1.00-1.07 for MetS and OR 1.04, 95 %CI 1.01-1.07 for high triglycerides).

CONCLUSION

Metabolic syndrome and individual metabolic components, such as abdominal obesity and elevated blood pressure, were associated with radiographic progression of knee OA in both men and women, but not independent of BMI. Metabolic syndrome and high triglycerides were associated with incidence of CKP only in men.

The Predictive Value of Aortic Calcification on Computed Tomography for Major Cardiovascular Events

As the prevalence of cardiovascular disease continues to increase, early identification of patients at high risk of major adverse cardiovascular events (MACE) using reliable diagnostic modalities is important. Transcatheter aortic valve implantation (TAVI) is a minimally invasive percutaneous procedure used to replace the aortic valve with a bioprosthetic one, often without the need for surgery. Extra coronary calcification in the ascending and/or descending thoracic aorta, aortic arch, and abdominal aorta has recently been identified as a method to quantify the extent of atherosclerotic cardiovascular disease. However, its definitive role in the prediction of MACE remains unclear. We performed a comprehensive review to summarize the current literature on the diagnostic and predictive value of thoracic and abdominal aortic calcification, as quantified in computed tomography, for the association, risk stratification, and prediction of MACE and after TAVI procedures. Despite increasing evidence, the predictive role of thoracic calcification still remains unproven, with a need for carefully tailored studies to confirm these findings.

Factors associated with meniscus volume in knees free of degenerative features

OBJECTIVES

To explore factors that were associated with meniscus volume in knees free of radiographic osteoarthritis (OA) features and symptoms of OA.

METHODS

In the third Rotterdam Study cohort, clinical, radiographic, and magnetic resonance data were obtained at baseline (BL) and after 5 years of follow-up. Meniscus volumes and their change over time were calculated after semi-automatic segmentation on Magnetic Resonance Imaging. Knees with radiographic OA features (Kellgren and Lawrence>0) or clinical diagnosis of OA (American College of Rheumatology) at BL were excluded. Ten OA risk factors were adjusted in the multivariable analysis (generalized estimating equations), treating two knees within subjects as repeated measurements.

RESULTS

From 1065 knees (570 subjects), the average (standard deviation) age and Body mass index (BMI) of included subjects were 54.3 (3.7) years and 26.5 (4.4) kg/m2. At BL, nine factors (varus alignment, higher BMI, meniscus pathologies, meniscus extrusion, cartilage lesions, injury, greater physical activity level, quadriceps muscle strength, and higher age) were significantly associated with greater meniscus volume. Five factors (injury, meniscus pathologies, meniscus extrusion, higher age, and change of BMI) were significantly associated with meniscus volume loss.

CONCLUSIONS

Modifiable factors (varus alignment, BMI, physical activity level, and quadriceps muscle strength) and non-modifiable factors (higher age, injury, meniscus pathologies, meniscus extrusion, and cartilage lesions) were all associated with meniscus volume or meniscus volume loss over time.

Cognitive intra-individual variability in breast cancer survivors: A systematic review

Subjective and objective cognitive impairments in Breast Cancer Survivors (BCS) often do not correlate. One important contribution to the reported disparities may be the reliance on mean-based cognitive performance. Cognitive intra-individual variability (IIV) may provide important insights into these reported disparities. Cognitive IIV refers to the fluctuation in performance for an individual on either one cognitive task across a trial or dispersed across tasks within a neuropsychological test battery. The purpose of this systematic review was to search for and examine the literature on cognitive IIV in BCS. The PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) approach was used to search for all articles related to cognitive IIV in BCS. MEDLINE (via PubMed), Embase, and Scopus databases were searched using detailed search terms and strategies. Initially, 164 articles were retrieved but only 4 articles met the criteria for this systematic review. BCS differed from healthy controls in similar ways across the four studies, generally demonstrating similar performance but showing increased cognitive IIV for the more difficult tasks. Differences were enhanced later during chemotherapy. The four studies provide support for cognitive IIV as a useful measure to detect the subtle objective cognitive change often reported by BCS but frequently not detected by standard normed-based cognitive testing. Unexpectedly, measures of cognitive IIV were not consistently associated with self-reported measures of cognition.

Whole-exome sequencing of 14 389 individuals from the ESP and CHARGE consortia identifies novel rare variation associated with hemostatic factors

Plasma levels of fibrinogen, coagulation factors VII and VIII and von Willebrand factor (vWF) are four intermediate phenotypes that are heritable and have been associated with the risk of clinical thrombotic events. To identify rare and low-frequency variants associated with these hemostatic factors, we conducted whole-exome sequencing in 10 860 individuals of European ancestry (EA) and 3529 African Americans (AAs) from the Cohorts for Heart and Aging Research in Genomic Epidemiology Consortium and the National Heart, Lung and Blood Institute's Exome Sequencing Project. Gene-based tests demonstrated significant associations with rare variation (minor allele frequency < 5%) in fibrinogen gamma chain (FGG) (with fibrinogen, P = 9.1 × 10-13), coagulation factor VII (F7) (with factor VII, P = 1.3 × 10-72; seven novel variants) and VWF (with factor VIII and vWF; P = 3.2 × 10-14; one novel variant). These eight novel rare variant associations were independent of the known common variants at these loci and tended to have much larger effect sizes. In addition, one of the rare novel variants in F7 was significantly associated with an increased risk of venous thromboembolism in AAs (Ile200Ser; rs141219108; P = 4.2 × 10-5). After restricting gene-based analyses to only loss-of-function variants, a novel significant association was detected and replicated between factor VIII levels and a stop-gain mutation exclusive to AAs (rs3211938) in CD36 molecule (CD36). This variant has previously been linked to dyslipidemia but not with the levels of a hemostatic factor. These efforts represent the largest integration of whole-exome sequence data from two national projects to identify genetic variation associated with plasma hemostatic factors.

PCSK9 acts as a key regulator of Aβ clearance across the blood-brain barrier

Despite the neurodegenerative disorder Alzheimer's disease (AD) is the most common form of dementia in late adult life, there is currently no therapy available to prevent the onset or slow down the progression of AD. The progressive cognitive decline in AD correlates with a successive accumulation of cerebral amyloid-β (Aβ) due to impaired clearance mechanisms. A significant percentage is removed by low-density lipoprotein receptor-related protein 1 (LRP1)-mediated transport across the blood-brain barrier (BBB) into the periphery. Circulating proprotein convertase subtilisin/kexin type 9 (PCSK9) binds to members of the low-density lipoprotein receptor protein family at the cell surface and targets them for lysosomal degradation, which reduces the number of functional receptors. However, the adverse impact of PCSK9 on LRP1-mediated brain Aβ clearance remains elusive. By using an established BBB model, we identified reduced LRP1-mediated brain-to-blood Aβ clearance due to PCSK9 across different endothelial monolayer in vitro. Consequently, the repetitive application of FDA-approved monoclonal anti-PCSK9 antibodies into 5xFAD mice decreased the cerebral Aβ burden across variants and aggregation state, which was not reproducible in brain endothelial-specific LRP1^-/- 5xFAD mice. The peripheral PCSK9 inhibition reduced Aβ pathology in prefrontal cortex and hippocampus-brain areas critically involved in memory processing-and prevented disease-related impairment in hippocampus-dependent memory formation. Our data suggest that peripheral inhibition of PCSK9 by already available therapeutic antibodies may be a novel and easily applicable potential AD treatment.

Challenges at the APOE locus: a robust quality control approach for accurate APOE genotyping

BACKGROUND

Genetic variants within the APOE locus may modulate Alzheimer's disease (AD) risk independently or in conjunction with APOE*2/3/4 genotypes. Identifying such variants and mechanisms would importantly advance our understanding of APOE pathophysiology and provide critical guidance for AD therapies aimed at APOE. The APOE locus however remains relatively poorly understood in AD, owing to multiple challenges that include its complex linkage structure and uncertainty in APOE*2/3/4 genotype quality. Here, we present a novel APOE*2/3/4 filtering approach and showcase its relevance on AD risk association analyses for the rs439401 variant, which is located 1801 base pairs downstream of APOE and has been associated with a potential regulatory effect on APOE.

METHODS

We used thirty-two AD-related cohorts, with genetic data from various high-density single-nucleotide polymorphism microarrays, whole-genome sequencing, and whole-exome sequencing. Study participants were filtered to be ages 60 and older, non-Hispanic, of European ancestry, and diagnosed as cognitively normal or AD (n = 65,701). Primary analyses investigated AD risk in APOE*4/4 carriers. Additional supporting analyses were performed in APOE*3/4 and 3/3 strata. Outcomes were compared under two different APOE*2/3/4 filtering approaches.

RESULTS

Using more conventional APOE*2/3/4 filtering criteria (approach 1), we showed that, when in-phase with APOE*4, rs439401 was variably associated with protective effects on AD case-control status. However, when applying a novel filter that increases the certainty of the APOE*2/3/4 genotypes by applying more stringent criteria for concordance between the provided APOE genotype and imputed APOE genotype (approach 2), we observed that all significant effects were lost.

CONCLUSIONS

We showed that careful consideration of APOE genotype and appropriate sample filtering were crucial to robustly interrogate the role of the APOE locus on AD risk. Our study presents a novel APOE filtering approach and provides important guidelines for research into the APOE locus, as well as for elucidating genetic interaction effects with APOE*2/3/4.

Genetically regulated expression in late-onset Alzheimer's disease implicates risk genes within known and novel loci

Late-onset Alzheimer disease (LOAD) is highly polygenic, with a heritability estimated between 40 and 80%, yet risk variants identified in genome-wide studies explain only ~8% of phenotypic variance. Due to its increased power and interpretability, genetically regulated expression (GReX) analysis is an emerging approach to investigate the genetic mechanisms of complex diseases. Here, we conducted GReX analysis within and across 51 tissues on 39 LOAD GWAS data sets comprising 58,713 cases and controls from the Alzheimer's Disease Genetics Consortium (ADGC) and the International Genomics of Alzheimer's Project (IGAP). Meta-analysis across studies identified 216 unique significant genes, including 72 with no previously reported LOAD GWAS associations. Cross-brain-tissue and cross-GTEx models revealed eight additional genes significantly associated with LOAD. Conditional analysis of previously reported loci using established LOAD-risk variants identified eight genes reaching genome-wide significance independent of known signals. Moreover, the proportion of SNP-based heritability is highly enriched in genes identified by GReX analysis. In summary, GReX-based meta-analysis in LOAD identifies 216 genes (including 72 novel genes), illuminating the role of gene regulatory models in LOAD.

Advances in molecular mechanisms of interaction between Mycobacterium tuberculosis and lung cancer: a narrative review

Objective

We systematically review the molecular mechanism of the interaction between lung cancer (LC) and tuberculosis (TB), and put forward the existing problems in order to provide suggestions for early intervention and future research direction.

Background

TB and LC are two global public health problems affecting human health. LC is the main cause of cancer-related death worldwide and TB is one of the leading causes of death among infectious diseases, especially in resource-poor areas. Previous studies have suggested that a history of TB may be associated with an increased risk of LC. With the improvement of LC treatment, the occurrence of pulmonary tuberculosis in the course of LC treatment is also frequently reported recently.

Methods

The molecular immunological mechanisms of interaction between LC and TB, and related epidemiological literature are reviewed. The research progress and problems to be solved are summarized.

Conclusions

Chronic inflammation, immune abnormalities, scar formation, gene mutations and drug effects caused by TB may be associated with the occurrence of LC induced by abnormalities in various molecular pathways. LC and decreased immunity during treatment may also increase the risk of latent TB activation or new TB infection through immune pathways. Data on dual burden areas of TB and LC are still lacking, and more clinical studies are needed to elucidate the association.

Multiethnic Genome-Wide Association Study of Subclinical Atherosclerosis in Individuals With Type 2 Diabetes

BACKGROUND

Coronary artery calcification (CAC) and carotid artery intima-media thickness (cIMT) are measures of subclinical atherosclerosis in asymptomatic individuals and strong risk factors for cardiovascular disease. Type 2 diabetes (T2D) is an independent cardiovascular disease risk factor that accelerates atherosclerosis.

METHODS

We performed meta-analyses of genome-wide association studies in up to 2500 T2D individuals of European ancestry (EA) and 1590 T2D individuals of African ancestry with or without exclusion of prevalent cardiovascular disease, for CAC measured by cardiac computed tomography, and 3608 individuals of EA and 838 individuals of African ancestry with T2D for cIMT measured by ultrasonography within the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium.

RESULTS

We replicated 2 loci (rs9369640 and rs9349379 near PHACTR1 and rs10757278 near CDKN2B) for CAC and one locus for cIMT (rs7412 and rs445925 near APOE-APOC1) that were previously reported in the general EA populations. We identified one novel CAC locus (rs8000449 near CSNK1A1L/LINC00547/POSTN at 13q13.3) at P=2.0×10-8 in EA. No additional loci were identified with the meta-analyses of EA and African ancestry. The expression quantitative trait loci analysis with nearby expressed genes derived from arterial wall and metabolic tissues from the Genotype-Tissue Expression project pinpoints POSTN, encoding a matricellular protein involved in bone formation and bone matrix organization, as the potential candidate gene at this locus. In addition, we found significant associations (P<3.1×10-4) for 3 previously reported coronary artery disease loci for these subclinical atherosclerotic phenotypes (rs2891168 near CDKN2B-AS1 and rs11170820 near FLJ12825 for CAC, and rs7412 near APOE for cIMT).

CONCLUSIONS

Our results provide potential biological mechanisms that could link CAC and cIMT to increased cardiovascular disease risk in individuals with T2D.

A Novel Afrocentric Stroke Risk Assessment Score: Models from the Siren Study

BACKGROUND

Stroke risk can be quantified using risk factors whose effect sizes vary by geography and race. No stroke risk assessment tool exists to estimate aggregate stroke risk for indigenous African.

OBJECTIVES

To develop Afrocentric risk-scoring models for stroke occurrence.

MATERIALS AND METHODS

We evaluated 3533 radiologically confirmed West African stroke cases paired 1:1 with age-, and sex-matched stroke-free controls in the SIREN study. The 7,066 subjects were randomly split into a training and testing set at the ratio of 85:15. Conditional logistic regression models were constructed by including 17 putative factors linked to stroke occurrence using the training set. Significant risk factors were assigned constant and standardized statistical weights based on regression coefficients (β) to develop an additive risk scoring system on a scale of 0-100%. Using the testing set, Receiver Operating Characteristics (ROC) curves were constructed to obtain a total score to serve as cut-off to discriminate between cases and controls. We calculated sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) at this cut-off.

RESULTS

For stroke occurrence, we identified 15 traditional vascular factors. Cohen's kappa for validity was maximal at a total risk score of 56% using both statistical weighting approaches to risk quantification and in both datasets. The risk score had a predictive accuracy of 76% (95%CI: 74-79%), sensitivity of 80.3%, specificity of 63.0%, PPV of 68.5% and NPV of 76.2% in the test dataset. For ischemic strokes, 12 risk factors had predictive accuracy of 78% (95%CI: 74-81%). For hemorrhagic strokes, 7 factors had a predictive accuracy of 79% (95%CI: 73-84%).

CONCLUSIONS

The SIREN models quantify aggregate stroke risk in indigenous West Africans with good accuracy. Prospective studies are needed to validate this instrument for stroke prevention.

Risk prediction for new-onset atrial fibrillation using the Minnesota code electrocardiography classification system

Background

Few risk models are available to predict future onset of atrial fibrillation (AF) in workers. We aimed to develop risk prediction models for new-onset AF, using annual health checkup (HC) data with electrocardiogram findings.

Methods and Results

We retrospectively included 56,288 factory or office workers (mean age = 51.5 years, 33.0% women) who underwent a HC at a medical center and fulfilled the following criteria; age ≥ 40 years, no history of AF, and greater than 1 annual follow-up HC in 2013–2016. Using Cox models with the Akaike information criterion, we developed and compared prediction models for new-onset AF with and without the Minnesota code information. We externally validated the discrimination accuracy of the models in a general Japanese population cohort, the Hisayama cohort. During the median 3.0-year follow-up, 209 (0.37%) workers developed AF. Age, sex, waist circumference, blood pressure, LDL cholesterol, and γ-GTP were associated with new-onset of AF. Using the Minnesota code information, the AUC significantly improved from 0.82 to 0.84 in the derivation cohort and numerically improved from 0.78 to 0.79 in the validation cohort, and from 0.77 to 0.79 in the Hisayama cohort. The NRI and IDI significantly improved in all and male subjects in both the derivation and validation cohorts, and in female subjects in both the validation and the Hisayama cohorts.

Conclusions

We developed useful risk model with Minnesota code information for predicting new-onset AF from large worker population validated in the original and external cohorts, although study interpretation is limited by small improvement of AUC.

Artificial Intelligence-Electrocardiography to Predict Incident Atrial Fibrillation: A Population-Based Study

BACKGROUND

An artificial intelligence (AI) algorithm applied to electrocardiography during sinus rhythm has recently been shown to detect concurrent episodic atrial fibrillation (AF). We sought to characterize the value of AI-enabled electrocardiography (AI-ECG) as a predictor of future AF and assess its performance compared with the CHARGE-AF score (Cohorts for Aging and Research in Genomic Epidemiology-AF) in a population-based sample.

METHODS

We calculated the probability of AF using AI-ECG, among participants in the population-based Mayo Clinic Study of Aging who had no history of AF at the time of the baseline study visit. Cox proportional hazards models were fit to assess the independent prognostic value and interaction between AI-ECG AF model output and CHARGE-AF score. C statistics were calculated for AI-ECG AF model output, CHARGE-AF score, and combined AI-ECG and CHARGE-AF score.

RESULTS

A total of 1936 participants with median age 75.8 (interquartile range, 70.4-81.8) years and median CHARGE-AF score 14.0 (IQR, 13.2-14.7) were included in the analysis. Participants with AI-ECG AF model output of >0.5 at the baseline visit had cumulative incidence of AF 21.5% at 2 years and 52.2% at 10 years. When included in the same model, both AI-ECG AF model output (hazard ratio, 1.76 per SD after logit transformation [95% CI, 1.51-2.04]) and CHARGE-AF score (hazard ratio, 1.90 per SD [95% CI, 1.58-2.28]) independently predicted future AF without significant interaction (P=0.54). C statistics were 0.69 (95% CI, 0.66-0.72) for AI-ECG AF model output, 0.69 (95% CI, 0.66-0.71) for CHARGE-AF, and 0.72 (95% CI, 0.69-0.75) for combined AI-ECG and CHARGE-AF score.

CONCLUSIONS

In the present study, both the AI-ECG AF model output and CHARGE-AF score independently predicted incident AF. The AI-ECG may offer a means to assess risk with a single test and without requiring manual or automated clinical data abstraction.

Relationship between thyroid dysfunction and dementia

Background

Thyroid hormones are essential for normal development and function of the central nervous system. Thyroid dysfunction is associated with many neuropsychiatric disorders mainly cognitive impairment.

Results

We found a close correlation between thyroid status and cognitive dysfunction. Serum FT3 levels decreased, whereas the serum thyroid-stimulating hormone (TSH) level increased, with the decline in cognitive functions. Furthermore, the TSH level showed a negative correlation with the Mini-Mental State Examination (MMSE) scores. We suggested that thyroid function was associated with cognitive impairments induced by subcortical ischemic vascular dementia (SIVD).

Conclusion

We found that thyroid dysfunction especially subclinical hypothyroidism is associated with cognitive impairment. Dementia increases more with more increase in TSH, and the MMSE score decreases with the increase of age.

Logistic regression was as good as machine learning for predicting major chronic diseases

OBJECTIVE

To evaluate the performance of machine learning (ML) algorithms and to compare them with logistic regression for the prediction of risk of cardiovascular diseases (CVDs), chronic kidney disease (CKD), diabetes (DM), and hypertension (HTN) and in a prospective cohort study using simple clinical predictors.

STUDY DESIGN AND SETTING

We conducted analyses in a population-based cohort study in Asian adults (n = 6,762). Five different ML models were considered-single-hidden-layer neural network, support vector machine, random forest, gradient boosting machine, and k-nearest neighbor-and were compared with standard logistic regression.

RESULTS

The incidences at 6 years of CVD, CKD, DM, and HTN cases were 4.0%, 7.0%, 9.2%, and 34.6%, respectively. Logistic regression reached the highest area under the receiver operating characteristic curve for CKD (0.905 [0.88, 0.93]) and DM (0.768 [0.73, 0.81]) predictions. For CVD and HTN, the best models were neural network (0.753 [0.70, 0.81]) and support vector machine (0.780 [0.747, 0.812]), respectively. However, the differences with logistic regression were small (less than 1%) and nonsignificant. Logistic regression, gradient boosting machine, and neural network were systematically ranked among the best models.

CONCLUSION

Logistic regression yields as good performance as ML models to predict the risk of major chronic diseases with low incidence and simple clinical predictors.

Association of 11β-hydroxysteroid dehydrogenase type1 (HSD11b1) gene polymorphisms with outcome of antidepressant therapy and suicide attempts

The hypothalamic-pituitary-adrenal axis has been implicated in the pathophysiology of depressive disorders. HSD11B1 encodes 11β-hydroxysteroid dehydrogenase type1 enzyme, responsible for converting cortisone to cortisol. Genetic polymorphisms in HSD11B1 may impact in depression outcome and risk of suicide. This study aimed to assess whether HSD11B1 genotypes and haplotypes are associated with depression risk, severity of symptoms and suicidal attempts, considering early-life stress as an environmental factor. Here, 142 depressive patients and 103 healthy controls were included. Patients were enrolled from the Affective Disorders ambulatory and day hospital units, both within the University General Hospital of Ribeirao Preto. All subjects were clinically assessed applying the Mini-PLUS International Neuropsychiatric Interview, followed by the 21-item GRID-Hamilton Depression Scale, Childhood Trauma Questionnaire and Beck Scale for Suicidal Ideation (BSI). All subjects underwent antecubital vein puncture to obtain blood for DNA extraction. Genotyping of rs11119328 and rs11811440 were performed using allele-specific oligonucleotide polymerase chain reaction. We found a significant association of rs11119328 variant genotypes with increased risk for at least one suicide attempt (OR: 7.10, p = 0.049) and an association of variant genotypes of rs11811440 with euthymic mood under optimized pharmacological treatment (OR: 0.05, P = 0.014). These tests included correction for confounding factors. The association of genetic markers with depression risk, GRID-HAM-D21 and BSI scores and the number of suicidal attempts were nonsignificant. Haplotypes combining both markers were not associated with the studied phenotypes. We conclude that HSD11B1 polymorphisms may be relevant biomarkers for detecting subjects genetically vulnerable to poorer antidepressant response and higher risk of suicide attempts.

The systemic immune-inflammation index is associated with an increased risk of incident cancer-A population-based cohort study

Several studies found that the systemic immune-inflammation index (SII) is a prognostic factor for mortality in patients with solid tumors. It is unknown whether an increased SII in generally healthy individuals reflects a risk for developing cancer. Our objective was to investigate the association between the SII and incident cancers in a prospective cohort study. Data were obtained from the Rotterdam Study; a population-based study of individuals aged ≥45 years, between 2002 and 2013. The SII at baseline was calculated from absolute blood counts. The association between the SII and the risk of any solid incident cancer during follow-up was assessed using Cox proportional hazard models. Individuals with a prior cancer diagnosis were excluded. Data of 8,024 individuals were included in the analyses. The mean age at baseline was 65.6 years (SD 10.5 years) and the majority were women. During a maximum follow-up period of 10.7 years, 733 individuals were diagnosed with cancer. A higher SII at baseline was associated with a 30% higher risk of developing a solid cancer (HR of 1.30 [95% CI; 1.11-1.53]), after adjustment for age, sex, socioeconomic status, smoking, BMI and type 2 diabetes. The absolute cumulative 10-year cancer risk increased from 9.7% in the lowest quartile of SII to 14.7% in the highest quartile (p-value = 0.009). The risk of developing cancer was persistent over time and increased for individuals with the longest follow-up. In conclusion, a high SII is a strong and independent risk indicator for developing a solid cancer.

Genetic variants linked to myopic macular degeneration in persons with high myopia: CREAM Consortium

Purpose

To evaluate the roles of known myopia-associated genetic variants for development of myopic macular degeneration (MMD) in individuals with high myopia (HM), using case-control studies from the Consortium of Refractive Error and Myopia (CREAM).

Methods

A candidate gene approach tested 50 myopia-associated loci for association with HM and MMD, using meta-analyses of case-control studies comprising subjects of European and Asian ancestry aged 30 to 80 years from 10 studies. Fifty loci with the strongest associations with myopia were chosen from a previous published GWAS study. Highly myopic (spherical equivalent [SE] ≤ -5.0 diopters [D]) cases with MMD (N = 348), and two sets of controls were enrolled: (1) the first set included 16,275 emmetropes (SE ≤ -0.5 D); and (2) second set included 898 highly myopic subjects (SE ≤ -5.0 D) without MMD. MMD was classified based on the International photographic classification for pathologic myopia (META-PM).

Results

In the first analysis, comprising highly myopic cases with MMD (N = 348) versus emmetropic controls without MMD (N = 16,275), two SNPs were significantly associated with high myopia in adults with HM and MMD: (1) rs10824518 (P = 6.20E-07) in KCNMA1, which is highly expressed in human retinal and scleral tissues; and (2) rs524952 (P = 2.32E-16) near GJD2. In the second analysis, comprising highly myopic cases with MMD (N = 348) versus highly myopic controls without MMD (N = 898), none of the SNPs studied reached Bonferroni-corrected significance.

Conclusions

Of the 50 myopia-associated loci, we did not find any variant specifically associated with MMD, but the KCNMA1 and GJD2 loci were significantly associated with HM in highly myopic subjects with MMD, compared to emmetropes.

Spatial correlations between MRI-derived wall shear stress and vessel wall thickness in the carotid bifurcation

Background

To explore the possibility of creating three-dimensional (3D) estimation models for patient-specific wall thickness (WT) maps using patient-specific and cohort-averaged WT, wall shear stress (WSS), and vessel diameter maps in asymptomatic atherosclerotic carotid bifurcations.

Methods

Twenty subjects (aged 75 ± 6 years [mean ± standard deviation], eight women) underwent a 1.5-T MRI examination. Non-gated 3D phase-contrast gradient-echo images and proton density-weighted echo-planar images were retrospectively assessed for WSS, diameter estimation, and WT measurements. Spearman’s ρ and scatter plots were used to determine correlations between individual WT, WSS, and diameter maps. A bootstrapping technique was used to determine correlations between 3D cohort-averaged WT, WSS, and diameter maps. Linear regression between the cohort-averaged WT, WSS, and diameter maps was used to predict individual 3D WT.

Results

Spearman’s ρ averaged over the subjects was − 0.24 ± 0.18 (p < 0.001) and 0.07 ± 0.28 (p = 0.413) for WT versus WSS and for WT versus diameter relations, respectively. Cohort-averaged ρ, averaged over 1000 bootstraps, was − 0.56 (95% confidence interval [− 0.74,− 0.38]) for WT versus WSS and 0.23 (95% confidence interval [− 0.06, 0.52]) for WT versus diameter. Scatter plots did not reveal relationships between individual WT and WSS or between WT and diameter data. Linear relationships between these parameters became apparent after averaging over the cohort. Spearman’s ρ between the original and predicted WT maps was 0.21 ± 0.22 (p < 0.001).

Conclusions

With a combination of bootstrapping and cohort-averaging methods, 3D WT maps can be predicted from the individual 3D WSS and diameter maps. The methodology may help to elucidate pathological processes involving WSS in carotid atherosclerosis.

Electronic supplementary material

The online version of this article (10.1186/s41747-018-0058-1) contains supplementary material, which is available to authorized users.

A Review on the Extraction of Quantitative Retinal Microvascular Image Feature

Digital image processing is one of the most widely used computer vision technologies in biomedical engineering. In the present modern ophthalmological practice, biomarkers analysis through digital fundus image processing analysis greatly contributes to vision science. This further facilitates developments in medical imaging, enabling this robust technology to attain extensive scopes in biomedical engineering platform. Various diagnostic techniques are used to analyze retinal microvasculature image to enable geometric features measurements such as vessel tortuosity, branching angles, branching coefficient, vessel diameter, and fractal dimension. These extracted markers or characterized fundus digital image features provide insights and relates quantitative retinal vascular topography abnormalities to various pathologies such as diabetic retinopathy, macular degeneration, hypertensive retinopathy, transient ischemic attack, neovascular glaucoma, and cardiovascular diseases. Apart from that, this noninvasive research tool is automated, allowing it to be used in large-scale screening programs, and all are described in this present review paper. This paper will also review recent research on the image processing-based extraction techniques of the quantitative retinal microvascular feature. It mainly focuses on features associated with the early symptom of transient ischemic attack or sharp stroke.

Genome-wide Analysis of Large-scale Longitudinal Outcomes using Penalization -GALLOP algorithm

Genome-wide association studies (GWAS) with longitudinal phenotypes provide opportunities to identify genetic variations associated with changes in human traits over time. Mixed models are used to correct for the correlated nature of longitudinal data. GWA studies are notorious for their computational challenges, which are considerable when mixed models for thousands of individuals are fitted to millions of SNPs. We present a new algorithm that speeds up a genome-wide analysis of longitudinal data by several orders of magnitude. It solves the equivalent penalized least squares problem efficiently, computing variances in an initial step. Factorizations and transformations are used to avoid inversion of large matrices. Because the system of equations is bordered, we can re-use components, which can be precomputed for the mixed model without a SNP. Two SNP effects (main and its interaction with time) are obtained. Our method completes the analysis a thousand times faster than the R package lme4, providing an almost identical solution for the coefficients and p-values. We provide an R implementation of our algorithm.

Electrocardiogram (ECG) for the Prediction of Incident Atrial Fibrillation: An Overview

Electrocardiograms (ECGs) have been employed to medically evaluate participants in population-based studies, and ECG-derived predictors have been reported for incident atrial fibrillation (AF). Here, we reviewed the status of ECG in predicting new-onset AF. We surveyed population-based studies and revealed ECG variables to be risk factors for incident AF. When available, the predictive values of each ECG risk marker were calculated. Both the atrium-related and ventricle-related ECG variables were risk factors for incident AF, with significant hazard risks (HRs) even after multivariate adjustments. The risk factors included P-wave indices (maximum P-wave duration, its dispersion or variation and P-wave morphology) and premature atrial contractions (PACs) or runs. In addition, left ventricular hypertrophy (LVH), ST-T abnormalities, intraventricular conduction delay, QTc interval and premature ventricular contractions (PVCs) or runs were a risk of incident AF. An HR of greater than 2.0 was observed in the upper 5th percentile of the P-wave durations, P-wave durations greater than 130 ms, P-wave morpholyg, PACs (PVCs) or runs, LVH, QTc and left anterior fascicular blocks. The sensitivity , specificity and the positive and negative predictive values were 3.6-53.8%, 61.7-97.9%, 2.9-61.7% and 77.4-97.7%, respectively. ECG variables are risk factors for incident AF. The correlation between the ECG-derived AF predictors, especially P-wave indices, and underlying diseases and the effects of the reversal of the ECG-derived predictors on incident AF by treatment of comorbidities require further study.

Automatized spleen segmentation in non-contrast-enhanced MR volume data using subject-specific shape priors

To develop the first fully automated 3D spleen segmentation framework derived from T1-weighted magnetic resonance (MR) imaging data and to verify its performance for spleen delineation and volumetry. This approach considers the issue of low contrast between spleen and adjacent tissue in non-contrast-enhanced MR images. Native T1-weighted MR volume data was performed on a 1.5 T MR system in an epidemiological study. We analyzed random subsamples of MR examinations without pathologies to develop and verify the spleen segmentation framework. The framework is modularized to include different kinds of prior knowledge into the segmentation pipeline. Classification by support vector machines differentiates between five different shape types in computed foreground probability maps and recognizes characteristic spleen regions in axial slices of MR volume data. A spleen-shape space generated by training produces subject-specific prior shape knowledge that is then incorporated into a final 3D level set segmentation method. Individually adapted shape-driven forces as well as image-driven forces resulting from refined foreground probability maps steer the level set successfully to the segment the spleen. The framework achieves promising segmentation results with mean Dice coefficients of nearly 0.91 and low volumetric mean errors of 6.3%. The presented spleen segmentation approach can delineate spleen tissue in native MR volume data. Several kinds of prior shape knowledge including subject-specific 3D prior shape knowledge can be used to guide segmentation processes achieving promising results.

Serum Phosphate Is Associated With Fracture Risk: The Rotterdam Study and MrOS

Extreme phosphate levels (P) have been associated with mineralization defects and increased fracture risk. Whether P within normal range is related to bone health in the general population is not well understood. To investigate the association of P with bone mineral density (BMD) and fracture risk, we assessed two population-based cohorts: the Dutch Rotterdam Study (RS-I, RS-II, RS-III; n = 6791) and the US Osteoporotic Fractures in Men (MrOS; n = 5425) study. The relationship of P with lumbar spine (LS) and femoral neck (FN) BMD was tested in all cohorts via linear models; fracture risk was tested in RS-I, RS-II, and MrOS through Cox models, after follow-up of 8.6, 6.6, and 10.9 years, respectively. Adjustments were made for age, body mass index, smoking, serum levels of calcium, potassium, 25-hydroxyvitamin D, estimated glomerular filtration rate (eGFR), FN-BMD, prevalent diabetes, and cardiovascular disease. Additional adjustments were made for phosphate intake, parathyroid hormone, and fibroblast growth factor 23 levels in MrOS. We further stratified by eGFR. Results were pooled through study-level meta-analyses. Hazard ratios (HR) and betas (β) (from meta-analyses) are expressed per 1 mg/dL P increase. P was positively associated with fracture risk in men and women from RS, and findings were replicated in MrOS (pooled HR all [95% CI]: 1.47 [1.31-1.65]). P was associated with fracture risk in subjects without chronic kidney disease (CKD): all (1.44 [1.26-1.63]) and in men with CKD (1.93 [1.42-2.62]). P was inversely related to LS-BMD in men (β: -0.06 [-0.11 to -0.02]) and not to FN-BMD in either sex. In summary, serum P was positively related to fracture risk independently from BMD and phosphate intake after adjustments for potential confounders. P and LS-BMD were negatively related in men. Our findings suggest that increased P levels even within normal range might be deleterious for bone health in the normal population. © 2017 American Society for Bone and Mineral Research.

Securing the use of existing sample collections for future human genetic research

Hundreds of thousands of individuals have been genotyped in the past decades using genotyping arrays, representing both a valuable data resource for future biomedical research and a substantial investment in human genetic research. However, novel chip designs and their altered sets of single-nucleotide polymorphisms (SNPs) pose the question of how well established data resources, such as large samples of healthy controls genotyped on legacy arrays, can be combined with newer samples genotyped on those novel arrays using genotype imputation. We exemplarily investigated this question based on genotype data of 30 European and 30 African unrelated samples from the 1000 Genomes project and on markers present on two legacy SNP arrays, namely Affymetrix's Human SNP 6.0 and Illumina's 550k array, and three newer arrays, namely two Axiom arrays from Affymetrix and an OmniExpress array from Illumina. We cross-compared the imputation accuracy as well as efficacy and assessed genotype concordance among these arrays. Although the accuracy of genotype prediction was uniformly high across all arrays, the imputation efficacy, that is, the proportion of successfully imputed markers, differed considerably between array combinations in both sample sets, with legacy arrays showing a trend towards lower efficacy values compared with newer arrays when serving as imputation basis. We conclude that, given the substantial losses of markers covered by the legacy arrays, the re-genotyping of existing samples sets, in particular those of healthy population controls, would be a worthwhile endeavor to secure their continued use in the future.

Intake of different types of dairy and its prospective association with risk of type 2 diabetes: The Rotterdam Study

BACKGROUND AND AIMS

The prevalence of type 2 diabetes (T2DM) is increasing. Several studies have suggested a beneficial effect of several major dairy nutrients on insulin production and sensitivity. Conversely, harmful effects have been suggested as well. This study aimed to investigate the impact of the full-range of dairy products and its association with incidence T2DM in Dutch adults aged ≥55 years participating in the Rotterdam Study.

METHODS AND RESULTS

Dairy intake was assessed with a validated FFQ, including total, skimmed, semi-skimmed, full-fat, fermented, and non-fermented dairy, and subclasses of these product groups. Verified prevalent and incident diabetes were documented. Cox proportional hazards regression and spline regression were used to analyse data, adjusting for age, sex, alcohol, smoking, education, physical activity, body mass index, intake of total energy, energy-adjusted meat, and energy-adjusted fish intake. Median total dairy intake was 398 g/day (IQR 259-559 g/day). Through 9.5 ± 4.1 years of follow-up, 393 cases of incident T2DM were reported. Cox and spline regression did not point towards associations of total dairy consumption, dairy consumption based on fat content, non-fermented or fermented dairy consumption, or individual dairy product consumption with incident T2DM. The HR for total dairy intake and T2DM was 0.93 (95% CI: 0.70-1.23) in the upper quartile (P-for trend 0.76).

CONCLUSIONS

This prospective cohort study did not point towards an association between dairy consumption and T2DM.

Severe Hand Osteoarthritis Strongly Correlates With Major Joint Involvement and Surgical Intervention

BACKGROUND

The presence of hand osteoarthritis (OA) increases the risk for developing OA in other major joints. Although genetic predisposition has been implicated in its causation, its exact role has yet to be established. The association of hand OA with symptomatic and asymptomatic major joints has not been previously studied.

METHODS

Hundred consecutive patients had a hand photo taken for visual documentation of the hand joints. Radiographs of hand and all major symptomatic joints were analyzed and classified using the Kellgren-Lawrence scale by 2 independent observers including an orthopedic radiologist.

RESULTS

Severe hand OA was present in 91% of the patients. Radiographic analysis showed that the hip was involved in 88% of the patients, of whom 85.2% (75) were symptomatic and 14.7% (13) were asymptomatic. Hip arthroplasty was required by 62.5% (55) of symptomatic hip patients. Knee involvement was present in 37% of the patients; all were symptomatic and 81.1% (30) of these required knee arthroplasty. Bilateral surgery was performed in 33% (28) and "2 joint (hip and knee)" surgery was performed in 6% (5). Spine involvement was present in 72% of the patients. There was a significant correlation between hand radiographic findings of OA and hip (r = 0.68; P = .03), knee (r = 0.58; P = .042), and spine (r = .39; P = .05) involvement.

CONCLUSION

There was a significant correlation between severe hand OA and hip, knee, and spine involvement. Severity of Hand OA can have a predictive value on multiple joint involvement and risk of surgical intervention. This study emphasizes the need to investigate the genetic predisposition in causation of OA.

Validation of the Framingham Heart Study and CHARGE-AF Risk Scores for Atrial Fibrillation in Hispanics, African-Americans, and Non-Hispanic Whites

A risk score for atrial fibrillation (AF) has been developed by the Framingham Heart Study and Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE)-AF consortium. However, validation of these risk scores in an inner-city population is uncertain. Thus, a validation model was built using the Framingham Risk Score for AF and CHARGE-AF covariates. An in and outpatient electrocardiographic database was interrogated from 2000 to 2013 for the development of AF. Patients were included if their age was >45 and <95 years, had <10-year follow-up, if their initial electrocardiogram was without AF, had ≥ 2 electrocardiograms, and declared a race and/or ethnicity as non-Hispanic white, African-American, or Hispanic. For the Framingham Heart Study, 49,599 patients met inclusion criteria, of which 4,860 developed AF. Discrimination analysis using area under the curve (AUC) for original risk equations: non-Hispanic white AUC = 0.712 (95% confidence interval [CI] 0.694 to 0.731), African-American AUC = 0.733 (95% CI 0.716 to 0.751), and Hispanic AUC = 0.740 (95% CI 0.723 to 0.757). For the CHARGE-AF, 45,571 patients met inclusion criteria, of which 4,512 developed AF. Non-Hispanic white AUC = 0.673 (95% CI 0.652 to 0.694), African-American AUC = 0.706 (95% CI 0.685 to 0.727), and Hispanic AUC = 0.711 (95% CI 0.691 to 0.732). Calibration analysis showed qualitative similarities between cohorts. In conclusion, this is the first study to validate both the Framingham Heart Study and CHARGE-AF risk scores in both a Hispanic and African-American cohort. All models predicted AF well across all race and ethnic cohorts.

White Matter Lesion Progression: Genome-Wide Search for Genetic Influences

BACKGROUND AND PURPOSE

White matter lesion (WML) progression on magnetic resonance imaging is related to cognitive decline and stroke, but its determinants besides baseline WML burden are largely unknown. Here, we estimated heritability of WML progression, and sought common genetic variants associated with WML progression in elderly participants from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium.

METHODS

Heritability of WML progression was calculated in the Framingham Heart Study. The genome-wide association study included 7773 elderly participants from 10 cohorts. To assess the relative contribution of genetic factors to progression of WML, we compared in 7 cohorts risk models including demographics, vascular risk factors plus single-nucleotide polymorphisms that have been shown to be associated cross-sectionally with WML in the current and previous association studies.

RESULTS

A total of 1085 subjects showed WML progression. The heritability estimate for WML progression was low at 6.5%, and no single-nucleotide polymorphisms achieved genome-wide significance (P<5×10(-8)). Four loci were suggestive (P<1×10(-5)) of an association with WML progression: 10q24.32 (rs10883817, P=1.46×10(-6)); 12q13.13 (rs4761974, P=8.71×10(-7)); 20p12.1 (rs6135309, P=3.69×10(-6)); and 4p15.31 (rs7664442, P=2.26×10(-6)). Variants that have been previously related to WML explained only 0.8% to 11.7% more of the variance in WML progression than age, vascular risk factors, and baseline WML burden.

CONCLUSIONS

Common genetic factors contribute little to the progression of age-related WML in middle-aged and older adults. Future research on determinants of WML progression should focus more on environmental, lifestyle, or host-related biological factors.

Characterizing the Impact of Off-Axis Scan Acquisition on the Reproducibility of Total Retinal Thickness Measurements in SDOCT Volumes

PURPOSE

Off-axis acquisition of spectral domain optical coherence tomography (SDOCT) images has been shown to increase total retinal thickness (TRT) measurements. We analyzed the reproducibility of TRT measurements obtained using either the retinal pigment epithelium (RPE) or Bruch's membrane as reference surfaces in off-axis scans intentionally acquired through multiple pupil positions.

METHODS

Five volumetric SDOCT scans of the macula were obtained from one eye of 25 normal subjects. One scan was acquired through a central pupil position, while subsequent scans were acquired through four peripheral pupil positions. The internal limiting membrane, the RPE, and Bruch's membrane were segmented using automated approaches. These volumes were registered to each other and the TRT was evaluated in 9 Early Treatment of Diabetic Retinopathy Study (ETDRS) regions. The reproducibility of the TRT obtained using the RPE was computed using the mean difference, coefficient of variation (CV), and the intraclass correlation coefficient (ICC), and compared to those obtained using Bruch's membrane as the reference surface. A secondary set of 1545 SDOCT scans was also analyzed in order to gauge the incidence of off-axis scans in a typical acquisition environment.

RESULTS

The photoreceptor tips were dimmer in off-axis images, which affected the RPE segmentation. The overall mean TRT difference and CV obtained using the RPE were 7.04 ± 4.31 μm and 1.46%, respectively, whereas Bruch's membrane was 1.16 ± 1.00 μm and 0.32%, respectively. The ICCs at the subfoveal TRT were 0.982 and 0.999, respectively. Forty-one percent of the scans in the secondary set showed large tilts (> 6%).

CONCLUSIONS

RPE segmentation is confounded by its proximity to the interdigitation zone, a structure strongly affected by the optical Stiles-Crawford effect. Bruch's membrane, however, is unaffected leading to a more robust segmentation that is less dependent upon pupil position.

TRANSLATIONAL RELEVANCE

The way in which OCT images are acquired can independently affect the accuracy of automated retinal thickness measurements. Assessment of scan angle in a clinical dataset demonstrates that off-axis scans are common, which emphasizes the need for caution when relying on automated thickness parameters when this component of scan acquisition is not controlled for.

Rare and low-frequency variants and their association with plasma levels of fibrinogen, FVII, FVIII, and vWF

Fibrinogen, coagulation factor VII (FVII), and factor VIII (FVIII) and its carrier von Willebrand factor (vWF) play key roles in hemostasis. Previously identified common variants explain only a small fraction of the trait heritabilities, and additional variations may be explained by associations with rarer variants with larger effects. The aim of this study was to identify low-frequency (minor allele frequency [MAF] ≥0.01 and <0.05) and rare (MAF <0.01) variants that influence plasma concentrations of these 4 hemostatic factors by meta-analyzing exome chip data from up to 76,000 participants of 4 ancestries. We identified 12 novel associations of low-frequency (n = 2) and rare (n = 10) variants across the fibrinogen, FVII, FVIII, and vWF traits that were independent of previously identified associations. Novel loci were found within previously reported genes and had effect sizes much larger than and independent of previously identified common variants. In addition, associations at KCNT1, HID1, and KATNB1 identified new candidate genes related to hemostasis for follow-up replication and functional genomic analysis. Newly identified low-frequency and rare-variant associations accounted for modest amounts of trait variance and therefore are unlikely to increase predicted trait heritability but provide new information for understanding individual variation in hemostasis pathways.

[Incidental radiological findings]

All findings which arise in the context of radiological diagnostics, potentially affect the health of a subject but with no intention to detect the corresponding finding are considered to be incidental radiological findings (IF). The prevalence of IFs is increasing due to the wider use of modern imaging techniques, such as magnetic resonance imaging (MRI) and computed tomography (CT) in routine clinical practice and the inclusion of imaging, such as whole body MRI in large population-based cohorts. The reporting of radiological IFs can lead to further diagnostics and treatment. The management of IFs in the clinical routine is regulated by the guidelines of the various academic societies. The management of IFs in the setting of research studies differs depending on various factors, such as study design and health status of enrolled subjects. In general, IFs must be disclosed to the subject if the radiological IFs are potentially clinically relevant; however, subjects must also be protected from the consequences of false positive findings. This review article discusses radiological IFs in the setting of the clinical routine and research studies and provides a basic summary of the management recommendations for commonly occurring IFs.

Design, implementation and operation of a multimodality research imaging informatics repository

Background

Biomedical imaging research increasingly involves acquiring, managing and processing large amounts of distributed imaging data. Integrated systems that combine data, meta-data and workflows are crucial for realising the opportunities presented by advances in imaging facilities.

Methods

This paper describes the design, implementation and operation of a multi-modality research imaging data management system that manages imaging data obtained from biomedical imaging scanners operated at Monash Biomedical Imaging (MBI), Monash University in Melbourne, Australia. In addition to Digital Imaging and Communications in Medicine (DICOM) images, raw data and non-DICOM biomedical data can be archived and distributed by the system. Imaging data are annotated with meta-data according to a study-centric data model and, therefore, scientific users can find, download and process data easily.

Results

The research imaging data management system ensures long-term usability, integrity inter-operability and integration of large imaging data. Research users can securely browse and download stored images and data, and upload processed data via subject-oriented informatics frameworks including the Distributed and Reflective Informatics System (DaRIS), and the Extensible Neuroimaging Archive Toolkit (XNAT).

Risk factors for complicated grief in older adults

BACKGROUND

Older adults grieving the death of a spouse have been found to have a higher risk of complicated grief compared with younger adults.

OBJECTIVE

The study objective was to find out whether personal characteristics of the patient and the bereaved partner, or characteristics of the patient's illness, end-of-life care, and the nature of death are risk factors for complicated grief in older adults.

METHODS

We performed a nested case-control study within the Rotterdam Study. We selected 100 couples of which one person had deceased and the other person experienced "complicated grief," and 100 control couples of which one person had deceased and the other person experienced "normal grief." Complicated grief was assessed with a 17-item Inventory of Complicated Grief (ICG). Determinants were assessed using several sources of information that were available for all participants of the Rotterdam Study. Additionally, medical files of the deceased were manually screened. Logistic regression analysis was performed.

RESULTS

Only depression at baseline was significantly associated with complicated grief. Bereaved partners with depression at baseline had a higher risk of complicated grief compared to bereaved partners without depression (OR=3.48; 95% CI=1.40-8.68).

CONCLUSIONS

Our results suggest that complicated grief in older adults is not clearly related to the circumstances of dying of the deceased partner. Preexisting conditions such as depression seem to be more important in explaining the occurrence of complicated grief.

Accounting for eXentricities: analysis of the X chromosome in GWAS reveals X-linked genes implicated in autoimmune diseases

Many complex human diseases are highly sexually dimorphic, suggesting a potential contribution of the X chromosome to disease risk. However, the X chromosome has been neglected or incorrectly analyzed in most genome-wide association studies (GWAS). We present tailored analytical methods and software that facilitate X-wide association studies (XWAS), which we further applied to reanalyze data from 16 GWAS of different autoimmune and related diseases (AID). We associated several X-linked genes with disease risk, among which (1) ARHGEF6 is associated with Crohn's disease and replicated in a study of ulcerative colitis, another inflammatory bowel disease (IBD). Indeed, ARHGEF6 interacts with a gastric bacterium that has been implicated in IBD. (2) CENPI is associated with three different AID, which is compelling in light of known associations with AID of autosomal genes encoding centromere proteins, as well as established autosomal evidence of pleiotropy between autoimmune diseases. (3) We replicated a previous association of FOXP3, a transcription factor that regulates T-cell development and function, with vitiligo; and (4) we discovered that C1GALT1C1 exhibits sex-specific effect on disease risk in both IBDs. These and other X-linked genes that we associated with AID tend to be highly expressed in tissues related to immune response, participate in major immune pathways, and display differential gene expression between males and females. Combined, the results demonstrate the importance of the X chromosome in autoimmunity, reveal the potential of extensive XWAS, even based on existing data, and provide the tools and incentive to properly include the X chromosome in future studies.

Alterations in brain structure related to breast cancer and its treatment: chemotherapy and other considerations

Cognitive effects of cancer and its treatment have been a topic of increasing investigation over the past ~30 years. Recent studies have focused on better understanding the neural correlates of these effects, with an emphasis on post-chemotherapy effects in breast cancer patients. Structural MRI studies have utilized both automated and manual approaches to quantify gray and white matter characteristics (e.g., regional volume and density) in breast cancer patients treated with chemotherapy relative to patients who did not receive chemotherapy and/or healthy controls. While most work to date has been retrospective, a small number of baseline (pre-systemic therapy) and prospective longitudinal studies have been conducted. Data have consistently shown lower gray and white matter volume and density in patients treated with chemotherapy, particularly in frontal and temporal brain regions. Host factors and/or the cancer disease process and other therapies (e.g., antiestrogen treatment) also seem likely to contribute to the observed differences, though the relative contributions of these effects have not yet been investigated in detail. These structural abnormalities have been shown to relate to subjective and objective cognitive functioning, as well as to biological factors that may help to elucidate the underlying mechanism(s). This review examines the currently available published observations and discusses the major themes and promising directions for future studies.

Meta-analysis identifies loci affecting levels of the potential osteoarthritis biomarkers sCOMP and uCTX-II with genome wide significance

BACKGROUND

Research for the use of biomarkers in osteoarthritis (OA) is promising, however, adequate discrimination between patients and controls may be hampered due to innate differences. We set out to identify loci influencing levels of serum cartilage oligomeric protein (sCOMP) and urinary C-telopeptide of type II collagen (uCTX-II).

METHODS

Meta-analysis of genome-wide association studies was applied to standardised residuals of sCOMP (N=3316) and uCTX-II (N=4654) levels available in 6 and 7 studies, respectively, from TreatOA. Effects were estimated using a fixed-effects model. Six promising signals were followed up by de novo genotyping in the Cohort Hip and Cohort Knee study (N = 964). Subsequently, their role in OA susceptibility was investigated in large-scale genome-wide association studies meta-analyses for OA. Differential expression of annotated genes was assessed in cartilage.

RESULTS

Genome-wide significant association with sCOMP levels was found for a SNP within MRC1 (rs691461, p = 1.7 × 10(-12)) and a SNP within CSMD1 associated with variation in uCTX-II levels with borderline genome-wide significance (rs1983474, p = 8.5 × 10(-8)). Indication for association with sCOMP levels was also found for a locus close to the COMP gene itself (rs10038, p = 7.1 × 10(-6)). The latter SNP was subsequently found to be associated with hip OA whereas COMP expression appeared responsive to the OA pathophysiology in cartilage.

CONCLUSIONS

We have identified genetic loci affecting either uCTX-II or sCOMP levels. The genome wide significant association of MRC1 with sCOMP levels was found likely to act independent of OA subtypes. Increased sensitivity of biomarkers with OA may be accomplished by taking genetic variation into account.

Studying variability in human brain aging in a population-based German cohort-rationale and design of 1000BRAINS

The ongoing 1000 brains study (1000BRAINS) is an epidemiological and neuroscientific investigation of structural and functional variability in the human brain during aging. The two recruitment sources are the 10-year follow-up cohort of the German Heinz Nixdorf Recall (HNR) Study, and the HNR MultiGeneration Study cohort, which comprises spouses and offspring of HNR subjects. The HNR is a longitudinal epidemiological investigation of cardiovascular risk factors, with a comprehensive collection of clinical, laboratory, socioeconomic, and environmental data from population-based subjects aged 45–75 years on inclusion. HNR subjects underwent detailed assessments in 2000, 2006, and 2011, and completed annual postal questionnaires on health status. 1000BRAINS accesses these HNR data and applies a separate protocol comprising: neuropsychological tests of attention, memory, executive functions and language; examination of motor skills; ratings of personality, life quality, mood and daily activities; analysis of laboratory and genetic data; and state-of-the-art magnetic resonance imaging (MRI, 3 Tesla) of the brain. The latter includes (i) 3D-T1- and 3D-T2-weighted scans for structural analyses and myelin mapping; (ii) three diffusion imaging sequences optimized for diffusion tensor imaging, high-angular resolution diffusion imaging for detailed fiber tracking and for diffusion kurtosis imaging; (iii) resting-state and task-based functional MRI; and (iv) fluid-attenuated inversion recovery and MR angiography for the detection of vascular lesions and the mapping of white matter lesions. The unique design of 1000BRAINS allows: (i) comprehensive investigation of various influences including genetics, environment and health status on variability in brain structure and function during aging; and (ii) identification of the impact of selected influencing factors on specific cognitive subsystems and their anatomical correlates.

Annotation of loci from genome-wide association studies using tissue-specific quantitative interaction proteomics

Genome-wide association studies (GWAS) have identified thousands of loci associated wtih complex traits, but it is challenging to pinpoint causal genes in these loci and to exploit subtle association signals. We used tissue-specific quantitative interaction proteomics to map a network of five genes involved in the Mendelian disorder long QT syndrome (LQTS). We integrated the LQTS network with GWAS loci from the corresponding common complex trait, QT interval variation, to identify candidate genes that were subsequently confirmed in Xenopus laevis oocytes and zebrafish. We used the LQTS protein network to filter weak GWAS signals by identifying single nucleotide polymorphisms (SNPs) in proximity to genes in the network supported by strong proteomic evidence. Three SNPs passing this filter reached genome-wide significance after replication genotyping. Overall, we present a general strategy to propose candidates in GWAS loci for functional studies and to systematically filter subtle association signals using tissue-specific quantitative interaction proteomics.

Identifying genetic risk variants for coronary heart disease in familial hypercholesterolemia: an extreme genetics approach

Mutations in the low-density lipoprotein receptor (LDLR) gene cause familial hypercholesterolemia (FH), a disorder characterized by coronary heart disease (CHD) at young age. We aimed to apply an extreme sampling method to enhance the statistical power to identify novel genetic risk variants for CHD in individuals with FH. We selected cases and controls with an extreme contrast in CHD risk from 17,000 FH patients from the Netherlands, whose functional LDLR mutation was unequivocally established. The genome-wide association (GWA) study was performed on 249 very young FH cases with CHD and 217 old FH controls without CHD (above 65 years for males and 70 years of age for females) using the Illumina HumanHap550K chip. In the next stage, two independent samples (one from the Netherlands and one from Italy, Norway, Spain, and the United Kingdom) of FH patients were used as replication samples. In the initial GWA analysis, we identified 29 independent single nucleotide polymorphisms (SNPs) with suggestive associations with premature CHD (P<1 × 10(-4)). We examined the association of these SNPs with CHD risk in the replication samples. After Bonferroni correction, none of the SNPs either replicated or reached genome-wide significance after combining the discovery and replication samples. Therefore, we conclude that the genetics of CHD risk in FH is complex and even applying an 'extreme genetics' approach we did not identify new genetic risk variants. Most likely, this method is not as effective in leveraging effect size as anticipated, and may, therefore, not lead to significant gains in statistical power.

Large scale meta-analysis of urinary C-terminal telopeptide, serum cartilage oligomeric protein and matrix metalloprotease degraded type II collagen and their role in prevalence, incidence and progression of osteoarthritis

OBJECTIVE

To evaluate the role of three cartilage-derived biomarkers on osteoarthritis (OA): urinary C-terminal telopeptide (uCTX-II), serum cartilage oligomeric protein (sCOMP), and serum MMP degraded type II collagen (sC2M).

SUBJECTS AND METHODS

Samples from 3582 individuals from the Rotterdam Study, the Genetics osteoArthritis and Progression (GARP), the Chingford Study and the TwinsUK cohort were assayed using enzyme-linked immune sorbent assays. Log10 of concentration levels were correlated with risk of hip, hand and knee OA, hip and knee OA severity and incidence, and progression of knee OA, adjusting for age, gender and body mass index (BMI). Results were meta-analysed to assess overall significance.

RESULTS

After adjusting for covariates, sCOMP was associated with knee OA and hip and knee OA incidence. Furthermore, sC2M was associated with knee OA incidence and progression. After adjustment for multiple tests (Bonferroni P < 0.002) only the association between sCOMP and knee OA remained significant (odds ratio (OR) = 3.26 (95%CI 1.63-10.1) P = 0.0008 for each standard deviation (SD) increase in biomarker levels). Levels of uCTX-II were significantly associated with risk of hand, hip and knee OA, progression and incidence of knee OA. A receiver operating characteristics (ROC) analysis showed a consistent improvement in prediction of knee OA progression from an average area under the curve (AUC) is 0.646 for age, sex and BMI alone to an AUC = 0.668 including uCTX-II for prediction.

CONCLUSIONS

uCTX-II is the most informative biochemical marker for prediction of OA. Both sCOMP and C2M showed some association with OA, thus indicating that they are descriptive of disease activity.

Risk factors and their impact on carotid intima-media thickness in young and middle-aged ischemic stroke patients and controls: the Norwegian Stroke in the Young Study

Background

Vascular morbidity and mortality due to cardiovascular disease (CVD) are high after ischemic stroke at a young age. Data on carotid intima-media thickness (cIMT) as marker of atherosclerosis are scarce for young stroke populations. In this prospective case–control study, we examined cIMT, the burden of vascular risk factors (RF) and their associations among young and middle-aged ischemic stroke patients and controls. We aimed to detect clinical and sub-clinical arterial disease.

Methods

This study was conducted in 150 patients aged 15–60 years and 84 controls free of CVD. We related RF to ultrasonographic B-mode cIMT-measurements obtained from 12 standardized multiangle measurements in the common carotid artery (CCA), carotid bifurcation (BIF) and internal carotid artery (ICA).

Results

RF burden was higher among patients than among controls (p < 0.001). In multivariate analyses of all 234 participants, increased cIMT was associated with age in each carotid segment. Incident stroke was associated with increased ICA-IMT. ICA-IMT increase was associated with a family history of CVD among patients aged 15–44 years, and with RF at mid-age. The overall cIMT difference between patients and controls was 12% for CCA, 17% for BIF and 29% for ICA. Further, increased CCA-IMT was associated with male sex and hypertension. Increased BIF-IMT was associated with dyslipidemia, coronary heart disease and smoking. Increased ICA-IMT was associated with dyslipidemia and stroke.

Conclusions

Ischemic stroke is associated with increased ICA-IMT, related to a family history of CVD among patients aged <45 years, and to increasing RF burden with increasing age. Preventive strategies and aggressive RF treatment are indicated to avoid future cardiovascular events.

Trial registration

NOR-SYS is registered in ClinicalTrials.gov (NCT01597453).

BMI-associated alleles do not constitute risk alleles for polycystic ovary syndrome independently of BMI: a case-control study

Introduction

Polycystic Ovary Syndrome (PCOS) has a strong genetic background and the majority of patients with PCOS have elevated BMI levels. The aim of this study was to determine to which extent BMI-increasing alleles contribute to risk of PCOS when contemporaneous BMI is taken into consideration.

Methods

Patients with PCOS and controls were recruited from the United Kingdom (563 cases and 791 controls) and The Netherlands (510 cases and 2720 controls). Cases and controls were of similar BMI. SNPs mapping to 12 BMI-associated loci which have been extensively replicated across different ethnicities, i.e., BDNF, FAIM2, ETV5, FTO, GNPDA2, KCTD15, MC4R, MTCH2, NEGR1, SEC16B, SH2B1, and TMEM18, were studied in association with PCOS within each cohort using the additive genetic model followed by a combined analysis. A genetic allelic count risk score model was used to determine the risk of PCOS for individuals carrying increasing numbers of BMI-increasing alleles.

Results

None of the genetic variants, including FTO and MC4R, was associated with PCOS independently of BMI in the meta-analysis. Moreover, no differences were observed between cases and controls in the number of BMI-risk alleles present and no overall trend across the risk score groups was observed.

Conclusion

In this combined analysis of over 4,000 BMI-matched individuals from the United Kingdom and the Netherlands, we observed no association of BMI risk alleles with PCOS independent of BMI.

Predicting stroke through genetic risk functions: the CHARGE Risk Score Project

BACKGROUND AND PURPOSE

Beyond the Framingham Stroke Risk Score, prediction of future stroke may improve with a genetic risk score (GRS) based on single-nucleotide polymorphisms associated with stroke and its risk factors.

METHODS

The study includes 4 population-based cohorts with 2047 first incident strokes from 22,720 initially stroke-free European origin participants aged ≥55 years, who were followed for up to 20 years. GRSs were constructed with 324 single-nucleotide polymorphisms implicated in stroke and 9 risk factors. The association of the GRS to first incident stroke was tested using Cox regression; the GRS predictive properties were assessed with area under the curve statistics comparing the GRS with age and sex, Framingham Stroke Risk Score models, and reclassification statistics. These analyses were performed per cohort and in a meta-analysis of pooled data. Replication was sought in a case-control study of ischemic stroke.

RESULTS

In the meta-analysis, adding the GRS to the Framingham Stroke Risk Score, age and sex model resulted in a significant improvement in discrimination (all stroke: Δjoint area under the curve=0.016, P=2.3×10(-6); ischemic stroke: Δjoint area under the curve=0.021, P=3.7×10(-7)), although the overall area under the curve remained low. In all the studies, there was a highly significantly improved net reclassification index (P<10(-4)).

CONCLUSIONS

The single-nucleotide polymorphisms associated with stroke and its risk factors result only in a small improvement in prediction of future stroke compared with the classical epidemiological risk factors for stroke.

The Rotterdam Study: 2014 objectives and design update

The Rotterdam Study is a prospective cohort study ongoing since 1990 in the city of Rotterdam in The Netherlands. The study targets cardiovascular, endocrine, hepatic, neurological, ophthalmic, psychiatric, dermatological, oncological, and respiratory diseases. As of 2008, 14,926 subjects aged 45 years or over comprise the Rotterdam Study cohort. The findings of the Rotterdam Study have been presented in over a 1,000 research articles and reports (see www.erasmus-epidemiology.nl/rotterdamstudy ). This article gives the rationale of the study and its design. It also presents a summary of the major findings and an update of the objectives and methods.