A cross-sectional observational study for ethno-geographical disparities in sleep quality, brain morphometry and cognition (a SOLACE study) in Indians residing in India, and South Asians and Europeans residing in the UK - a study protocol.

Introduction: As individuals age, their sleep patterns change, and sleep disturbances can increase the risk of dementia. Poor sleep quality can be a risk factor for mild cognitive impairment (MCI) and dementia. Epidemiological studies show a connection between sleep quality and cognitive changes, with brain imaging revealing grey matter volume reduction and amyloid beta accumulation in Alzheimer's disease. However, most research has focused on Europeans, with little attention to other ethnic groups. Methods: This is a cross sectional study comparing effects across countries and ethnicities. Group 1 (n = 193) will be Indians residing in India (new participant recruitment), Group 2 will be South Asians residing in UK and group 3 will be Europeans residing in the UK. For group 2 and 3 (n = 193), data already collected by UK-based Southall and Brent REvisited (SABRE) tri-ethnic study will be used. For group 1, Pittsburgh Sleep Quality Index questionnaire (PSQI) will be used for assessment of sleep quality, Indian Council of Medical Research (Neurocognitive ToolBox) (ICMR-NCTB) for cognition testing and a 3 T MRI cerebral scan for brain morphometry. The data will be compared to sleep, cognitive function and brain MRI parameters from SABRE. Discussion: Racial and ethnic differences can impact the relationships of cognitive function, sleep quality and brain structure in older adults. Earlier studies have highlighted higher prevalence of poor sleep among black individuals compared to white individuals. Genetic or epigenetic mechanisms may contribute to these variations. Socio-cultural and environmental factors, such as neighbourhood, migration, lifestyle, stress and perceived discrimination may influence sleep patterns. The aim of the study is to examine the ethnogeographic variations in sleep quality, cognitive performance and brain morphometry among Indians living in India, and South Asians and Europeans residing in the UK.

Early-life cumulative exposure to excess bodyweight and midlife cognitive function: longitudinal analysis in three British birth cohorts.

BACKGROUND: Excess bodyweight (BMI >25 kg/m2) in midlife (age 40-65 years) has been linked to future cognitive decline and an increased risk of dementia. Whether chronic exposure to excess bodyweight in the early decades of life (<40 years) is associated with compromised cognitive function by midlife, however, remains unclear. This study therefore aimed to test potential bidirectional direct and indirect pathways linking cumulative exposure to excess bodyweight and cognitive function in the early decades of life. METHODS: In this longitudinal analysis, harmonised measures of BMI and cognitive function were available in 19 742 participants aged 47-53 years recruited to the 1946 National Survey of Health and Development (n=2131), the 1958 National Child Development Study (n=9385), and the 1970 British Cohort Study (n=8226). Individual BMI trajectories spanning three decades from age 10-40 years were created for each participant and excess bodyweight duration, BMI change between ages, and cumulative excess bodyweight exposure were calculated. Harmonised measures of verbal and non-verbal ability, mathematical ability, and reading ability were used to create a latent factor for childhood cognitive function, and immediate and delayed recall, animal naming, and letter-search speed tests were used for midlife cognitive function. Multivariable linear regression and structural equation models (SEM) were used to test for potential bidirectional relationships between cognition and excess bodyweight in both individual cohorts and pooled datasets while accounting for other potential early-life confounders. FINDINGS: Increases in BMI during adolescence and greater cumulative exposure to excess bodyweight across early life were associated with lower midlife cognitive function in all cohorts (eg, pooled difference in cognitive function per 10 years excess bodyweight duration -0·10; 95% CI -0·12 to -0·08; p<0·001). Further adjustment for childhood cognitive function attenuated many of these associations towards the null (eg, pooled difference in cognitive function per 10 years excess bodyweight duration -0·04; 95% CI -0·06 to -0·02; p=0·001), however, with any remaining associations then fully attenuating once further adjusted for other early-life factors (eg, pooled difference in cognitive function per 10 years excess bodyweight duration 0, -0·03 to 0·01; p=0·38). In the reverse direction, low childhood cognition was associated with greater cumulative exposure to excess bodyweight over the next four decades, although much of this relationship was found to probably be explained via other potentially modifiable upstream early-life factors such as childhood disadvantage. SEM in all cohorts suggested the presence of modest direct and indirect pathways connecting earlier cognitive function to later excess bodyweight, but scarce evidence for an effect of early-life excess bodyweight on cognitive function by midlife. INTERPRETATION: The association between cumulative exposure to excess bodyweight in early life and lower cognitive function in midlife is probably confounded by a persistently lower cognitive function from childhood. Initiatives to improve early-life factors such as childhood disadvantage and education, however, might exert dual but independent benefits on both of these factors before old age. FUNDING: Alzheimer's Research UK, Diabetes Research and Wellness Foundation, Diabetes UK, British Heart Foundation, and Medical Research Council.

Associations of a multidimensional polygenic sleep health score and a sleep lifestyle index on health outcomes and their interaction in a clinical biobank.

Sleep is a complex behavior regulated by genetic and environmental factors, and is known to influence health outcomes. However, the effect of multidimensional sleep encompassing several sleep dimensions on diseases has yet to be fully elucidated. Using the Mass General Brigham Biobank, we aimed to examine the association of multidimensional sleep with health outcomes and investigate whether sleep behaviors modulate genetic predisposition to unfavorable sleep on mental health outcomes. First, we generated a Polygenic Sleep Health Score using previously identified single nucleotide polymorphisms for sleep health and constructed a Sleep Lifestyle Index using data from self-reported sleep questions and electronic health records; second, we performed phenome-wide association analyses between these indexes and clinical phenotypes; and third, we analyzed the interaction between the indexes on prevalent mental health outcomes. Fifteen thousand eight hundred and eighty-four participants were included in the analysis (mean age 54.4; 58.6% female). The Polygenic Sleep Health Score was associated with the Sleep Lifestyle Index (ß=0.050, 95%CI=0.032, 0.068) and with 114 disease outcomes spanning 12 disease groups, including obesity, sleep, and substance use disease outcomes (p<3.3×10-5). The Sleep Lifestyle Index was associated with 458 disease outcomes spanning 17 groups, including sleep, mood, and anxiety disease outcomes (p<5.1×10-5). No interactions were found between the indexes on prevalent mental health outcomes. These findings suggest that favorable sleep behaviors and genetic predisposition to healthy sleep may independently be protective of disease outcomes. This work provides novel insights into the role of multidimensional sleep on population health and highlights the need to develop prevention strategies focused on healthy sleep habits.

The Role of Circadian Rhythms and Sleep in Anorexia Nervosa.

Importance: Observational studies have associated anorexia nervosa with circadian rhythms and sleep traits. However, the direction of causality and the extent of confounding by psychosocial comorbidities in these associations are unknown. Objectives: To investigate the association between anorexia nervosa and circadian and sleep traits through mendelian randomization and to test the associations between a polygenic risk score (PRS) for anorexia nervosa and sleep disorders in a clinical biobank. Design, Setting, and Participants: This genetic association study used bidirectional 2-sample mendelian randomization with summary-level genetic associations between anorexia nervosa (from the Psychiatric Genomics Consortium) and chronotype and sleep traits (primarily from the UK Biobank). The inverse-variance weighted method, in addition to other sensitivity approaches, was used. From the clinical Mass General Brigham (MGB) Biobank (n = 47 082), a PRS for anorexia nervosa was calculated for each patient and associations were tested with prevalent sleep disorders derived from electronic health records. Patients were of European ancestry. All analyses were performed between February and August 2023. Exposures: Genetic instruments for anorexia nervosa, chronotype, daytime napping, daytime sleepiness, insomnia, and sleep duration. Main Outcomes and Measures: Chronotype, sleep traits, risk of anorexia nervosa, and sleep disorders derived from a clinical biobank. Results: The anorexia nervosa genome-wide association study included 16 992 cases (87.7%-97.4% female) and 55 525 controls (49.6%-63.4% female). Genetic liability for anorexia nervosa was associated with a more morning chronotype (ß = 0.039; 95% CI, 0.006-0.072), and conversely, genetic liability for morning chronotype was associated with increased risk of anorexia nervosa (ß = 0.178; 95% CI, 0.042-0.315). Associations were robust in sensitivity and secondary analyses. Genetic liability for insomnia was associated with increased risk of anorexia nervosa (ß = 0.369; 95% CI, 0.073-0.666); however, sensitivity analyses indicated bias due to horizontal pleiotropy. The MGB Biobank analysis included 47 082 participants with a mean (SD) age of 60.4 (17.0) years and 25 318 (53.8%) were female. A PRS for anorexia nervosa was associated with organic or persistent insomnia in the MGB Biobank (odds ratio, 1.10; 95% CI, 1.03-1.17). No associations were evident for anorexia nervosa with other sleep traits. Conclusions and Relevance: The results of this study suggest that in contrast to other metabo-psychiatric diseases, anorexia nervosa is a morningness eating disorder and further corroborate findings implicating insomnia in anorexia nervosa. Future studies in diverse populations and with subtypes of anorexia nervosa are warranted.

A brief comparison of polygenic risk scores and Mendelian randomisation.

Mendelian randomisation and polygenic risk score analysis have become increasingly popular in the last decade due to the advent of large-scale genome-wide association studies. Each approach has valuable applications, some of which are overlapping, yet there are important differences which we describe here.

Validity of European-centric cardiometabolic polygenic scores in multi-ancestry populations.

Polygenic scores (PGSs) provide an individual level estimate of genetic risk for any given disease. Since most PGSs have been derived from genome wide association studies (GWASs) conducted in populations of White European ancestry, their validity in other ancestry groups remains unconfirmed. This is especially relevant for cardiometabolic diseases which are known to disproportionately affect people of non-European ancestry. Thus, we aimed to evaluate the performance of PGSs for glycaemic traits (glycated haemoglobin, and type 1 and type 2 diabetes mellitus), cardiometabolic risk factors (body mass index, hypertension, high- and low-density lipoproteins, and total cholesterol and triglycerides) and cardiovascular diseases (including stroke and coronary artery disease) in people of White European, South Asian, and African Caribbean ethnicity in the UK Biobank. Whilst PGSs incorporated some GWAS data from multi-ethnic populations, the vast majority originated from White Europeans. For most outcomes, PGSs derived mostly from European populations had an overall better performance in White Europeans compared to South Asians and African Caribbeans. Thus, multi-ancestry GWAS data are needed to derive ancestry stratified PGSs to tackle health inequalities.

Selection of genetic instruments in Mendelian randomisation studies of sleep traits.

This review explores the criteria used for the selection of genetic instruments of sleep traits in the context of Mendelian randomisation studies. This work was motivated by the fact that instrument selection is the most important decision when designing a Mendelian randomisation study. As far as we are aware, no review has sought to address this to date, even though the number of these studies is growing rapidly. The review is divided into the following sections which are essential for genetic instrument selection: 1) Single-gene region vs polygenic analysis; 2) Polygenic analysis: biologically-vs statistically-driven approaches; 3) P-value; 4) Linkage disequilibrium clumping; 5) Sample overlap; 6) Type of exposure; 7) Total (R2) and average strength (F-statistic) metrics; 8) Number of single-nucleotide polymorphisms; 9) Minor allele frequency and palindromic variants; 10) Confounding. Our main aim is to discuss how instrumental choice impacts analysis and compare the strategies that Mendelian randomisation studies of sleep traits have used. We hope that our review will enable more researchers to take a more considered approach when selecting genetic instruments for sleep exposures.

Chronic inflammation does not mediate the effect of adiposity on grip strength: results from a multivariable Mendelian randomization study.

The relationship between adiposity and grip strength (GS) is complex. We investigated whether one pathway through which adiposity affects GS was via chronic inflammation. 367,583 UK Biobank participants had body mass index (BMI), waist-hip-ratio (WHR), C-reactive protein (CRP) and GS data. Univariable Mendelian randomization (MR) and multivariable Mendelian randomization (MVMR) analyses (using inverse variance weighted (IVW) weighted median estimates (WME) and MR-Egger models) estimated total, direct and indirect effects of adiposity traits on GS using genetic instruments for BMI and WHR (exposures) and CRP (mediator). Observational findings suggested higher BMI was associated with stronger grip, e.g., in males, per standard deviation (SD) higher BMI, GS was higher by 0.48 kg (95% confidence interval(CI):0.44,0.51), independent of CRP. For males MR estimates were directionally consistent; for females, estimates were consistent with the null. Observational findings for WHR suggested that higher WHR was associated with weaker grip. In multivariable MR-IVW analyses, effects in males were consistent with the null. In females, there were consistent effects such that higher WHR was associated with stronger grip, e.g., 1-SD higher WHR was associated with 1.25 kg (MVMR-Egger; 95% CI:0.72,1.78) stronger grip, independent of CRP. Across sexes and adiposity indicators, CRP's mediating role was minor. Greater adiposity may increase GS in early old age, but effects vary by sex and adiposity location. There was no evidence that inflammation mediated these effects.

Sex-specific risks for cardiovascular disease across the glycaemic spectrum: a population-based cohort study using the UK Biobank.

Background: We sought to examine sex-specific risks for incident cardiovascular disease (CVD) across the full glycaemic spectrum. Methods: Using data from UK Biobank, we categorised participants' glycated haemoglobin (HbA1c) at baseline as low-normal (<35 mmol/mol), normal (35-41 mmol/mol), pre-diabetes (42-47 mmol/mol), undiagnosed diabetes (≥48 mmol/mol), or diagnosed diabetes. Our outcomes were coronary artery disease (CAD), atrial fibrillation, deep vein thrombosis (DVT), pulmonary embolism (PE), stroke, heart failure, and a composite outcome of any CVD. Cox regression estimated sex-specific associations between HbA1c and each outcome, sequentially adjusting for socio-demographic, lifestyle, and clinical characteristics. Findings: Among 427,435 people, CVD rates were 16.9 and 9.1 events/1000 person-years for men and women, respectively. Both men and women with pre-diabetes, undiagnosed diabetes, and, more markedly, diagnosed diabetes were at higher risks of CVD than those with normal HbA1c, with relative increases more pronounced in women than men. Age-adjusted HRs for pre-diabetes and undiagnosed diabetes ranged from 1.30 to 1.47; HRs for diagnosed diabetes were 1.55 (1.49-1.61) in men and 2.00 (1.89-2.12) in women (p-interaction <0.0001). Excess risks attenuated and were more similar between men and women after adjusting for clinical and lifestyle factors particularly obesity and antihypertensive or statin use (fully adjusted HRs for diagnosed diabetes: 1.06 [1.02-1.11] and 1.17 [1.10-1.24], respectively). Interpretation: Excess risks in men and women were largely explained by modifiable factors, and could be ameliorated by attention to weight reduction strategies and greater use of antihypertensive and statin medications. Addressing these risk factors could reduce sex disparities in risk of CVD among people with and without diabetes. Funding: Diabetes UK (#15/0005250) and British Heart Foundation (SP/16/6/32726).

Artificial intelligence for dementia genetics and omics.

Genetics and omics studies of Alzheimer's disease and other dementia subtypes enhance our understanding of underlying mechanisms and pathways that can be targeted. We identified key remaining challenges: First, can we enhance genetic studies to address missing heritability? Can we identify reproducible omics signatures that differentiate between dementia subtypes? Can high-dimensional omics data identify improved biomarkers? How can genetics inform our understanding of causal status of dementia risk factors? And which biological processes are altered by dementia-related genetic variation? Artificial intelligence (AI) and machine learning approaches give us powerful new tools in helping us to tackle these challenges, and we review possible solutions and examples of best practice. However, their limitations also need to be considered, as well as the need for coordinated multidisciplinary research and diverse deeply phenotyped cohorts. Ultimately AI approaches improve our ability to interrogate genetics and omics data for precision dementia medicine. HIGHLIGHTS: We have identified five key challenges in dementia genetics and omics studies. AI can enable detection of undiscovered patterns in dementia genetics and omics data. Enhanced and more diverse genetics and omics datasets are still needed. Multidisciplinary collaborative efforts using AI can boost dementia research.

Is there an association between daytime napping, cognitive function, and brain volume? A Mendelian randomization study in the UK Biobank.

OBJECTIVES: Daytime napping has been associated with cognitive function and brain health in observational studies. However, it remains elusive whether these associations are causal. Using Mendelian randomization, we studied the relationship between habitual daytime napping and cognition and brain structure. METHODS: Data were from UK Biobank (maximum n = 378,932 and mean age = 57 years). Our exposure (daytime napping) was instrumented using 92 previously identified genome-wide, independent genetic variants (single-nucleotide polymorphisms, SNPs). Our outcomes were total brain volume, hippocampal volume, reaction time, and visual memory. Inverse-variance weighted was implemented, with sensitivity analyses (Mendelian randomization-Egger and Weighted Median Estimator) for horizontal pleiotropy. We tested different daytime napping instruments to ensure the robustness of our results. RESULTS: Using Mendelian randomization, we found an association between habitual daytime napping and larger total brain volume (unstandardized ß = 15.80 cm3 and 95% CI = 0.25; 31.34) but not hippocampal volume (ß = -0.03 cm3 and 95% CI = -0.13;0.06), reaction time (expß = 1.01 and 95% CI = 1.00;1.03), or visual memory (expß = 0.99 and 95% CI = 0.94;1.05). Additional analyses with 47 SNPs (adjusted for excessive daytime sleepiness), 86 SNPs (excluding sleep apnea), and 17 SNPs (no sample overlap with UK Biobank) were largely consistent with our main findings. No evidence of horizontal pleiotropy was found. CONCLUSIONS: Our findings suggest a modest causal association between habitual daytime napping and larger total brain volume. Future studies could focus on the associations between napping and other cognitive or brain outcomes and replication of these findings using other datasets and methods.

The relationship between adiposity and cognitive function: a bidirectional Mendelian randomization study in UK Biobank.

BACKGROUND: There may be a bidirectional relationship between cognition and adiposity, whereby poor cognition leads to increased adiposity and vice versa. We aimed to determine whether these findings are causal, by undertaking a bidirectional Mendelian randomization (MR) study. METHODS: A total of 378 877 UK Biobank participants had three adiposity indicators [body fat percentage (BF%), body mass index (BMI) and waist-hip ratio] and two cognitive function measures (reaction time, visual memory). We examined observational associations between each adiposity indicator and cognitive function and vice versa. Using bidirectional inverse-variance weighted MR, we estimated the strength of the adiposity-cognitive function association using genetic instruments for adiposity indicators as our exposures, and we repeated this in the opposite direction using instruments for cognitive function. RESULTS: In the direction adiposity to cognitive function, MR analyses were generally directionally consistent with observational findings, but all confidence intervals contained the null. In the opposite direction, MR estimates for all adiposity measures on reaction time were imprecise and directionally inconsistent. MR estimates for the effects of visual memory on all adiposity measures indicated worse visual memory was associated with lower adiposity. For example, a 1-unit worse visual memory score was associated with a 1.32% [ß = -1.32; 95% confidence interval (CI): -0.77,-1.88] and 3.57% (ß = -3.64; 95% CI: -1.84,-5.15) lower absolute body fat percentage and relative body mass index, respectively. CONCLUSIONS: Observational associations of adiposity on cognitive function are likely not causal. In the reverse direction, our consistent findings that worse visual memory is associated with three adiposity indicators provide support for a causal link between worse visual memory and lower adiposity.

A Guide for Selection of Genetic Instruments in Mendelian Randomization Studies of Type 2 Diabetes and HbA1c: Toward an Integrated Approach.

In this study we examine the instrument selection strategies currently used throughout the type 2 diabetes and HbA1c Mendelian randomization (MR) literature. We then argue for a more integrated and thorough approach, providing a framework to do this in the context of HbA1c and diabetes. We conducted a literature search for MR studies that have instrumented diabetes and/or HbA1c. We also used data from the UK Biobank (UKB) (N = 349,326) to calculate instrument strength metrics that are key in MR studies (the F statistic for average strength and R2 for total strength) with two different methods ("individual-level data regression" and Cragg-Donald formula). We used a 157-single nucleotide polymorphism (SNP) instrument for diabetes and a 51-SNP instrument (with partition into glycemic and erythrocytic as well) for HbA1c. Our literature search yielded 48 studies for diabetes and 22 for HbA1c. Our UKB empirical examples showed that irrespective of the method used to calculate metrics of strength and whether the instrument was the main one or included partition by function, the HbA1c genetic instrument is strong in terms of both average and total strength. For diabetes, a 157-SNP instrument was shown to have good average strength and total strength, but these were both substantially lesser than those of the HbA1c instrument. We provide a careful set of five recommendations to researchers who wish to genetically instrument type 2 diabetes and/or HbA1c. In MR studies of glycemia, investigators should take a more integrated approach when selecting genetic instruments, and we give specific guidance on how to do this.

Linear and Nonlinear Associations Between Vitamin D and Grip Strength: A Mendelian Randomization Study in UK Biobank.

BACKGROUND: Low vitamin D status is a widespread phenomenon. Similarly, muscle weakness, often indicated by low grip strength, is another public health concern; however, the vitamin D-grip strength relationship is equivocal. It is important to understand whether variation in vitamin D status causally influences muscle strength to elucidate whether supplementation may help prevent/treat muscle weakness. METHODS: UK Biobank participants, aged 37-73 years, with valid data on Vitamin D status (circulating 25-hydroxyvitamin D [25(OH)D] concentration) and maximum grip strength were included (N = 368,890). We examined sex-specific cross-sectional associations between 25(OH)D and grip strength. Using Mendelian randomization (MR), we estimated the strength of the 25(OH)D-grip strength associations using genetic instruments for 25(OH)D as our exposure. Crucially, because potential effects of vitamin D supplementation on strength could vary by underlying 25(OH)D status, we allowed for nonlinear relationships between 25(OH)D and strength in all analyses. RESULTS: Mean (SD) of 25(OH)D was 50 (21) nmol/L in males and females. In cross-sectional analyses, there was evidence of nonlinear associations between 25(OH)D and strength, for example, compared to males with 50 nmol/L circulating 25(OH)D, males with 75 nmol/L had 0.36 kg (0.31,0.40) stronger grip; males with 25 nmol/L had 1.01 kg (95% confidence interval [CI]: 0.93, 1.08) weaker grip. In MR analyses, linear and nonlinear models fitted the data similarly well, for example, 25 nmol/L higher circulating 25(OH)D in males was associated with 0.25 kg (-0.05, 0.55) greater grip (regardless of initial 25(OH)D status). Results were similar, albeit weaker, for females. CONCLUSIONS: Using two different methods to triangulate evidence, our findings suggest moderate to small causal links between circulating 25(OH)D and grip strength.

Are infections associated with cognitive decline and neuroimaging outcomes? A historical cohort study using data from the UK Biobank study linked to electronic health records.

While there is growing evidence of associations between infections and dementia risk, associations with cognitive impairment and potential structural correlates of cognitive decline remain underexplored. Here we aimed to investigate the presence and nature of any associations between common infections, cognitive decline and neuroimaging parameters. The UK Biobank is a large volunteer cohort (over 500,000 participants recruited aged 40-69) with linkage to primary and secondary care records. Using linear mixed effects models, we compared participants with and without a history of infections for changes in cognitive function during follow-up. Linear regression models were used to investigate the association of infections with hippocampal and white matter hyperintensity (WMH) volume. 16,728 participants (median age 56.0 years [IQR 50.0-61.0]; 51.3% women) had baseline and follow-up cognitive measures. We found no evidence of an association between the presence of infection diagnoses and cognitive decline for mean correct response time (slope difference [infections versus no infections] = 0.40 ms, 95% CI: -0.17-0.96 per year), visual memory (slope difference 0.0004 log errors per year, 95% CI: -0.003-0.004, fluid intelligence (slope difference 0.007, 95% CI: -0.010-0.023) and prospective memory (OR 0.88, 95% CI: 0.68-1.14). No evidence of an association was found between infection site, setting or frequency and cognitive decline except for small associations on the visual memory test. We found no association between infections and hippocampal or WMH volume. Limitations of our study include selection bias, potential practice effects and the relatively young age of our cohort. Our findings do not support a major role for common midlife infections in contributing to cognitive decline for this cohort. Further research is warranted in individuals with more severe infections, for infections occurring later in life.

Adiposity and grip strength: a Mendelian randomisation study in UK Biobank.

BACKGROUND: Muscle weakness, which increases in prevalence with age, is a major public health concern. Grip strength is commonly used to identify weakness and an improved understanding of its determinants is required. We aimed to investigate if total and central adiposity are causally associated with grip strength. METHODS: Up to 470,786 UK Biobank participants, aged 38-73 years, with baseline data on four adiposity indicators (body mass index (BMI), body fat percentage (BF%), waist circumference (WC) and waist-hip-ratio (WHR)) and maximum grip strength were included. We examined sex-specific associations between each adiposity indicator and grip strength. We explored whether associations varied by age, by examining age-stratified associations (< 50 years, 50-59 years, 60-64 years,65 years +). Using Mendelian randomisation (MR), we estimated the strength of the adiposity-grip strength associations using genetic instruments for each adiposity trait as our exposure. RESULTS: In males, observed and MR associations were generally consistent: higher BMI and WC were associated with stronger grip; higher BF% and WHR were associated with weaker grip: 1-SD higher BMI was associated with 0.49 kg (95% CI: 0.45 kg, 0.53 kg) stronger grip; 1-SD higher WHR was associated with 0.45 kg (95% CI:0.41 kg, 0.48 kg) weaker grip (covariate adjusted observational analyses). Associations of BMI and WC with grip strength were weaker at older ages: in males aged < 50 years and 65 years + , 1-SD higher BMI was associated with 0.93 kg (95% CI: 0.84 kg, 1.01 kg) and 0.13 kg (95% CI: 0.05 kg, 0.21 kg) stronger grip, respectively. In females, higher BF% was associated with weaker grip and higher WC was associated with stronger grip; other associations were inconsistent. CONCLUSIONS: Using different methods to triangulate evidence, our findings suggest causal links between adiposity and grip strength. Specifically, higher BF% (in both sexes) and WHR (males only) were associated with weaker grip strength.

Understanding the inter-relationships of type 2 diabetes and hypertension with brain and cognitive health: A UK Biobank study.

AIM: To understand the impact of diabetes and co-morbid hypertension on cognitive and brain health. MATERIALS AND METHODS: We used data from the UK Biobank cohort consisting of ~500 000 individuals aged 40 to 69 years. Our outcomes included brain structural magnetic resonance imaging variables and cognitive function tests in a maximum of 38 918 individuals. We firstly tested associations with all outcomes between those with diabetes (n = 2043) and without (n = 36 875) and, secondly, compared those with co-morbid diabetes/hypertension (n = 1283) with those with only diabetes (n = 760), hypertension (n = 9649) and neither disease (n = 27 226). Our analytical approach comprised linear regression models, with adjustment for a range of demographic and health factors. Standardized betas are reported. RESULTS: Those with diabetes had worse brain and cognitive health for the majority of neuroimaging and cognitive measures, with the exception of g fractional anisotropy (white matter integrity), amygdala, pairs matching and tower rearranging. Compared with individuals with co-morbid diabetes and hypertension, those with only hypertension had better brain health overall, with the largest difference observed in the pallidum (ß = .189, 95% CI = 0.241; 0.137), while those with only diabetes differed in total grey volume (ß = .150, 95% CI = 0.122; 0.179). Individuals with only diabetes had better verbal and numeric reasoning (ß = .129, 95% CI = 0.077; 0.261), whereas those with only hypertension performed better on the symbol-digit substitution task (ß = .117, 95% CI = 0.048; 0.186). CONCLUSIONS: Individuals with co-morbid diabetes and hypertension have worse brain and cognitive health compared with those with only one of these diseases. These findings potentially suggest that prevention of both diabetes and hypertension may delay changes in brain structure, as well as cognitive decline and dementia diagnosis.

Type 2 diabetes risks and determinants in second-generation migrants and mixed ethnicity people of South Asian and African Caribbean descent in the UK.

AIMS/HYPOTHESIS: Excess risks of type 2 diabetes in UK South Asians (SA) and African Caribbeans (AC) compared with Europeans remain unexplained. We studied risks and determinants of type 2 diabetes in first- and second-generation (born in the UK) migrants, and in those of mixed ethnicity. METHODS: Data from the UK Biobank, a population-based cohort of ~500,000 participants aged 40-69 at recruitment, were used. Type 2 diabetes was assigned using self-report and HbA1c. Ethnicity was both self-reported and genetically assigned using admixture level scores. European, mixed European/South Asian (MixESA), mixed European/African Caribbean (MixEAC), SA and AC groups were analysed, matched for age and sex to enable comparison. In the frames of this cross-sectional study, we compared type 2 diabetes in second- vs first-generation migrants, and mixed ethnicity vs non-mixed groups. Risks and explanations were analysed using logistic regression and mediation analysis, respectively. RESULTS: Type 2 diabetes prevalence was markedly elevated in SA (599/3317 = 18%) and AC (534/4180 = 13%) compared with Europeans (140/3324 = 4%). Prevalence was lower in second- vs first-generation SA (124/1115 = 11% vs 155/1115 = 14%) and AC (163/2200 = 7% vs 227/2200 = 10%). Favourable adiposity (i.e. lower waist/hip ratio or BMI) contributed to lower risk in second-generation migrants. Type 2 diabetes in mixed populations (MixESA: 52/831 = 6%, MixEAC: 70/1045 = 7%) was lower than in comparator ethnic groups (SA: 18%, AC: 13%) and higher than in Europeans (4%). Greater socioeconomic deprivation accounted for 17% and 42% of the excess type 2 diabetes risk in MixESA and MixEAC compared with Europeans, respectively. Replacing self-reported with genetically assigned ethnicity corroborated the mixed ethnicity analysis. CONCLUSIONS/INTERPRETATION: Type 2 diabetes risks in second-generation SA and AC migrants are a fifth lower than in first-generation migrants. Mixed ethnicity risks were markedly lower than SA and AC groups, though remaining higher than in Europeans. Distribution of environmental risk factors, largely obesity and socioeconomic status, appears to play a key role in accounting for ethnic differences in type 2 diabetes risk.

Association between sleep quality and type 2 diabetes at 20-year follow-up in the Southall and Brent REvisited (SABRE) cohort: a triethnic analysis.

BACKGROUND: The risk of developing type 2 diabetes associated with poor sleep quality is comparable to other lifestyle factors (eg, overweight, physical inactivity). In the UK, these risk factors could not explain the two to three-fold excess risks in South-Asian and African-Caribbean men compared with Europeans. This study investigates (1) the association between mid-life sleep quality and later-life type 2 diabetes risk and (2) the potential modifying effect of ethnicity. METHODS: The Southall and Brent REvisited cohort is composed of Europeans, South-Asians and African-Caribbeans (median follow-up 19 years). Complete-case analysis was performed on 2189 participants without diabetes at baseline (age=51.7±7 SD). Competing risks regressions were used to estimate the HRs of developing diabetes associated with self-reported baseline sleep (difficulty falling asleep, early morning waking, waking up tired, snoring and a composite sleep score), adjusting for confounders. Modifying effects of ethnicity were analysed by conducting interaction tests and ethnicity-stratified analyses. RESULTS: There were 484 occurrences of incident type 2 diabetes (22%). Overall, there were no associations between sleep exposures and diabetes risk. Interaction tests suggested a possible modifying effect for South-Asians compared with Europeans for snoring only (p=0.056). The ethnicity-stratified analysis found an association with snoring among South-Asians (HR 1.41, 95% CI 1.08 to 1.85), comparing those who snored often/always versus occasionally/never. There were no elevated risks for the other sleep exposures. CONCLUSION: The association between snoring and type 2 diabetes appeared to be modified by ethnicity, and was strongest in South-Asians.