The Relationship Between Glycaemia, Cognitive Function, Structural Brain Outcomes and Dementia: A Mendelian Randomization Study in the UK Biobank

We investigated the relationship between glycaemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomisation (MR). Data were from UK Biobank (n~500,000). Our exposures were genetic instruments for type-2 diabetes (157 variants) and HbA1c (51 variants) and our outcomes were reaction time (RT), visual memory, hippocampal and white matter hyperintensity volumes, Alzheimer’s dementia (AD). We also investigated associations between genetic variants for RT (43 variants) and, diabetes and HbA1c. We used conventional inverse-variance weighted (IVW) MR, alongside MR sensitivity analyses. Using IVW, genetic liability to type-2 diabetes was not associated with reaction time (exponentiated ß=1.00, 95%CI=1.00; 1.00), visual memory (expß=1.00, 95%CI=0.99; 1.00), white matter hyperintensity volume (WMHV) (expß=0.99, 95%CI=0.97; 1.01), hippocampal volume (HV) (ß coefficient mm3=4.56, 95%CI=-3.98; 13.09) or AD (OR 0.89, 95%CI=0.78; 1.01). HbA1c was not associated with RT (expß=1.01, 95%CI=1.00; 1.01), WMHV (expß=0.94, 95%CI=0.81; 1.08), HV (ß=7.21, 95%CI=-54.06; 68.48), or risk of AD (OR 0.94, 95%CI=0.47; 1.86), but HbA1c was associated with visual memory (expß=1.06, 95%CI=1.05; 1.07) using a weighted median. IVW showed that reaction time was not associated with diabetes risk (OR 0.96, 95%CI=0.63; 1.46) or with HbA1c (ß coefficient mmol/mol=-0.08, 95%CI=-0.57; 0.42). Overall, we observed little evidence of causal association between genetic instruments for T2D or peripheral glycaemia and some measures of cognition and brain structure in midlife.

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The Relationship Between Glycaemia, Cognitive Function, Structural Brain Outcomes and Dementia: A Mendelian Randomization Study in the UK Biobank

10.2337/figshare.14096678.v2 ◽

2021 ◽

Author(s):

Victoria Garfield ◽

Aliki-Eleni Farmaki ◽

Ghazaleh Fatemifar ◽

Sophie V. Eastwood ◽

Rohini Mathur ◽

...

Keyword(s):

Type 2 Diabetes ◽

Reaction Time ◽

Cognitive Function ◽

White Matter ◽

Visual Memory ◽

White Matter Hyperintensity ◽

Uk Biobank ◽

The Relationship ◽

Genetic Instruments

We investigated the relationship between glycaemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomisation (MR). Data were from UK Biobank (n~500,000). Our exposures were genetic instruments for type-2 diabetes (157 variants) and HbA1c (51 variants) and our outcomes were reaction time (RT), visual memory, hippocampal and white matter hyperintensity volumes, Alzheimer’s dementia (AD). We also investigated associations between genetic variants for RT (43 variants) and, diabetes and HbA1c. We used conventional inverse-variance weighted (IVW) MR, alongside MR sensitivity analyses. Using IVW, genetic liability to type-2 diabetes was not associated with reaction time (exponentiated ß=1.00, 95%CI=1.00; 1.00), visual memory (expß=1.00, 95%CI=0.99; 1.00), white matter hyperintensity volume (WMHV) (expß=0.99, 95%CI=0.97; 1.01), hippocampal volume (HV) (ß coefficient mm3=4.56, 95%CI=-3.98; 13.09) or AD (OR 0.89, 95%CI=0.78; 1.01). HbA1c was not associated with RT (expß=1.01, 95%CI=1.00; 1.01), WMHV (expß=0.94, 95%CI=0.81; 1.08), HV (ß=7.21, 95%CI=-54.06; 68.48), or risk of AD (OR 0.94, 95%CI=0.47; 1.86), but HbA1c was associated with visual memory (expß=1.06, 95%CI=1.05; 1.07) using a weighted median. IVW showed that reaction time was not associated with diabetes risk (OR 0.96, 95%CI=0.63; 1.46) or with HbA1c (ß coefficient mmol/mol=-0.08, 95%CI=-0.57; 0.42). Overall, we observed little evidence of causal association between genetic instruments for T2D or peripheral glycaemia and some measures of cognition and brain structure in midlife.

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The Relationship Between Glycaemia, Cognitive Function, Structural Brain Outcomes and Dementia: A Mendelian Randomization Study in the UK Biobank

10.2337/figshare.14096678 ◽

2021 ◽

Author(s):

Victoria Garfield ◽

Aliki-Eleni Farmaki ◽

Ghazaleh Fatemifar ◽

Sophie V. Eastwood ◽

Rohini Mathur ◽

...

Keyword(s):

Type 2 Diabetes ◽

Reaction Time ◽

Cognitive Function ◽

White Matter ◽

Visual Memory ◽

White Matter Hyperintensity ◽

Uk Biobank ◽

The Relationship ◽

Genetic Instruments

We investigated the relationship between glycaemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomisation (MR). Data were from UK Biobank (n~500,000). Our exposures were genetic instruments for type-2 diabetes (157 variants) and HbA1c (51 variants) and our outcomes were reaction time (RT), visual memory, hippocampal and white matter hyperintensity volumes, Alzheimer’s dementia (AD). We also investigated associations between genetic variants for RT (43 variants) and, diabetes and HbA1c. We used conventional inverse-variance weighted (IVW) MR, alongside MR sensitivity analyses. Using IVW, genetic liability to type-2 diabetes was not associated with reaction time (exponentiated ß=1.00, 95%CI=1.00; 1.00), visual memory (expß=1.00, 95%CI=0.99; 1.00), white matter hyperintensity volume (WMHV) (expß=0.99, 95%CI=0.97; 1.01), hippocampal volume (HV) (ß coefficient mm3=4.56, 95%CI=-3.98; 13.09) or AD (OR 0.89, 95%CI=0.78; 1.01). HbA1c was not associated with RT (expß=1.01, 95%CI=1.00; 1.01), WMHV (expß=0.94, 95%CI=0.81; 1.08), HV (ß=7.21, 95%CI=-54.06; 68.48), or risk of AD (OR 0.94, 95%CI=0.47; 1.86), but HbA1c was associated with visual memory (expß=1.06, 95%CI=1.05; 1.07) using a weighted median. IVW showed that reaction time was not associated with diabetes risk (OR 0.96, 95%CI=0.63; 1.46) or with HbA1c (ß coefficient mmol/mol=-0.08, 95%CI=-0.57; 0.42). Overall, we observed little evidence of causal association between genetic instruments for T2D or peripheral glycaemia and some measures of cognition and brain structure in midlife.

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The relationship between glycaemia, cognitive function, structural brain outcomes and dementia: A Mendelian randomization study in the UK Biobank

10.1101/2020.05.07.20094110 ◽

2020 ◽

Author(s):

Victoria Garfield ◽

Aliki-Eleni Farmaki ◽

Ghazaleh Fatemifar ◽

Sophie V. Eastwood ◽

Rohini Mathur ◽

...

Keyword(s):

Type 2 Diabetes ◽

Reaction Time ◽

White Matter ◽

Visual Memory ◽

Hippocampal Volume ◽

White Matter Hyperintensity ◽

Uk Biobank ◽

Inverse Variance ◽

Volume Coefficient

AbstractAimsTo investigate the relationship between glycaemia and cognitive function, brain structure and incident dementia using bidirectional Mendelian randomisation (MR).MethodsUK Biobank (n~500,000) individuals, aged 40-69 years at baseline. Our exposures were genetic instruments for type-2 diabetes (163 variants) and HbA1c (52 variants) and our outcomes were reaction time (RT - milliseconds), visual memory (number of incorrect responses), hippocampal and white matter hyperintensity volumes (both mm3), Alzheimer’s disease (AD). To study potential bidirectional effects, we then investigated the associations between genetic variants for RT (43 variants) and clinical type-2 diabetes and measured HbA1c. We used conventional inverse-variance weighted (IVW) MR, alongside standard MR sensitivity analyses.ResultsUsing IVW, genetic liability to type-2 diabetes was not associated with reaction time (exponentiated ß=1.00, 95%CI=1.00; 1.00), visual memory (expß=1.00, 95%CI=0.99; 1.00), white matter hyperintensity volume (expß=0.98, 95%CI=0.93; 1.03), hippocampal volume (coefficient mm3=0.00, 95%CI=-0.01; 0.01) or risk of AD (OR 0.97, 95%CI=0.89; 1.06). HbA1c was not associated with reaction time (expß=1.01, 95%CI=1.00; 1.01), white matter hyperintensity volume (expß=0.88, 95%CI=0.73; 1.07), hippocampal volume (coefficient=-0.02, 95%CI=-0.10; 0.06), risk of AD (OR 0.94, 95%CI=0.47; 1.86), but HbA1c was associated with visual memory (expß=1.06, 95%CI=1.05; 1.07) using a weighted median approach. IVW showed no evidence that reaction time was associated with diabetes (OR 0.96, 95%CI=0.63; 1.46) or HbA1c (coefficient=-0.08, 95%CI=-0.57; 0.42). MR-Egger intercept p-values indicated no major issues with unbalanced horizontal pleiotropy (all p>0.05).ConclusionsOverall, we observed little evidence of causal associations between glycaemia and cognition, structural brain and dementia phenotypes.AbbreviationsAlzheimer’s dementia (AD)Benjamini-Hochberg false discovery rate (BH-FDR)Genome-wide association study (GWAS)Hippocampal volume (HV)Hospital episode statistics (HES)International Classification of Diseases (ICD)Inverse variance weighted (IVW)Magnetic resonance imaging (MRI)Mendelian randomization (MR)Quality control (QC)Reaction time (RT)Simulation extrapolation (SIMEX)UK Biobank (UKB)Visual memory (VM)Weighted median Estimator (WME)White matter hyperintensity volume (WMHV)

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Relationship Between Type 2 Diabetes and White Matter Hyperintensity: A Systematic Review

Frontiers in Endocrinology ◽

10.3389/fendo.2020.595962 ◽

2020 ◽

Vol 11 ◽

Author(s):

Dan-Qiong Wang ◽

Lei Wang ◽

Miao-Miao Wei ◽

Xiao-Shuang Xia ◽

Xiao-Lin Tian ◽

...

Keyword(s):

Type 2 Diabetes ◽

White Matter ◽

Structural Changes ◽

White Matter Lesions ◽

Poor Performance ◽

White Matter Hyperintensity ◽

Diabetic Microangiopathy ◽

The Relationship ◽

The Brain

White matter (WM) disease is recognized as an important cause of cognitive decline and dementia. White matter lesions (WMLs) appear as white matter hyperintensities (WMH) on T2-weighted magnetic resonance imaging (MRI) scans of the brain. Previous studies have shown that type 2 diabetes (T2DM) is associated with WMH. In this review, we reviewed the literature on the relationship between T2DM and WMH in PubMed and Cochrane over the past five years and explored the possible links among the presence of T2DM, the course or complications of diabetes, and WMH. We found that: (1) Both from a macro- and micro-scopic point of view, most studies support the relationship of a larger WMH and a decrease in the integrity of WMH in T2DM; (2) From the relationship between brain structural changes and cognition in T2DM, the poor performance in memory, attention, and executive function tests associated with abnormal brain structure is consistent; (3) Diabetic microangiopathy or peripheral neuropathy may be associated with WMH, suggesting that the brain may be a target organ for T2DM microangiopathy; (4) Laboratory markers such as insulin resistance and fasting insulin levels were significantly associated with WMH. High HbA1c and high glucose variability were associated with WMH but not glycemic control.

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Blood-based bioenergetic profiling is related to differences in brain morphology in African Americans with Type 2 diabetes

Clinical Science ◽

10.1042/cs20180690 ◽

2018 ◽

Vol 132 (23) ◽

pp. 2509-2518 ◽

Cited By ~ 2

Author(s):

Gargi Mahapatra ◽

S. Carrie Smith ◽

Timothy M. Hughes ◽

Benjamin Wagner ◽

Joseph A. Maldjian ◽

...

Keyword(s):

Type 2 Diabetes ◽

White Matter ◽

African Americans ◽

Mitochondrial Function ◽

Brain Morphology ◽

Intracranial Volume ◽

Peripheral Blood Mononuclear ◽

Relationship Of ◽

The Relationship

Blood-based bioenergetic profiling has promising applications as a minimally invasive biomarker of systemic bioenergetic capacity. In the present study, we examined peripheral blood mononuclear cell (PBMC) mitochondrial function and brain morphology in a cohort of African Americans with long-standing Type 2 diabetes. Key parameters of PBMC respiration were correlated with white matter, gray matter, and total intracranial volumes. Our analyses indicate that these relationships are primarily driven by the relationship of systemic bioenergetic capacity with total intracranial volume, suggesting that systemic differences in mitochondrial function may play a role in overall brain morphology.

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Reply to Comment to: The relationship between sleep and cognitive function in patients with prediabetes and type 2 diabetes

Acta Diabetologica ◽

10.1007/s00592-018-1190-3 ◽

2018 ◽

Vol 56 (1) ◽

pp. 121-122

Author(s):

Sunee Saetung ◽

Hataikarn Nimitphong ◽

Nantaporn Siwasaranond ◽

Rungtip Sumritsopak ◽

Panitha Jindahra ◽

...

Keyword(s):

Type 2 Diabetes ◽

Cognitive Function ◽

The Relationship

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Obesity and the relation between joint exposure to ambient air pollutants and incident type 2 diabetes: A cohort study in UK Biobank

PLoS Medicine ◽

10.1371/journal.pmed.1003767 ◽

2021 ◽

Vol 18 (8) ◽

pp. e1003767

Author(s):

Xiang Li ◽

Mengying Wang ◽

Yongze Song ◽

Hao Ma ◽

Tao Zhou ◽

...

Keyword(s):

Type 2 Diabetes ◽

Air Pollution ◽

Air Pollutants ◽

Ambient Air ◽

Uk Biobank ◽

Ambient Air Pollutants ◽

Obesity Status ◽

Increased Risk ◽

The Relationship

Background Air pollution has been related to incidence of type 2 diabetes (T2D). We assessed the joint association of various air pollutants with the risk of T2D and examined potential modification by obesity status and genetic susceptibility on the relationship. Methods and findings A total of 449,006 participants from UK Biobank free of T2D at baseline were included. Of all the study population, 90.9% were white and 45.7% were male. The participants had a mean age of 56.6 (SD 8.1) years old and a mean body mass index (BMI) of 27.4 (SD 4.8) kg/m2. Ambient air pollutants, including particulate matter (PM) with diameters ≤2.5 μm (PM2.5), between 2.5 μm and 10 μm (PM2.5–10), nitrogen oxide (NO2), and nitric oxide (NO) were measured. An air pollution score was created to assess the joint exposure to the 4 air pollutants. During a median of 11 years follow-up, we documented 18,239 incident T2D cases. The air pollution score was significantly associated with a higher risk of T2D. Compared to the lowest quintile of air pollution score, the hazard ratio (HR) (95% confidence interval [CI]) for T2D was 1.05 (0.99 to 1.10, p = 0.11), 1.06 (1.00 to 1.11, p = 0.051), 1.09 (1.03 to 1.15, p = 0.002), and 1.12 (1.06 to 1.19, p < 0.001) for the second to fifth quintile, respectively, after adjustment for sociodemographic characteristics, lifestyle factors, genetic factors, and other covariates. In addition, we found a significant interaction between the air pollution score and obesity status on the risk of T2D (p-interaction < 0.001). The observed association was more pronounced among overweight and obese participants than in the normal-weight people. Genetic risk score (GRS) for T2D or obesity did not modify the relationship between air pollution and risk of T2D. Key study limitations include unavailable data on other potential T2D-related air pollutants and single-time measurement on air pollutants. Conclusions We found that various air pollutants PM2.5, PM2.5–10, NO2, and NO, individually or jointly, were associated with an increased risk of T2D in the population. The stratified analyses indicate that such associations were more strongly associated with T2D risk among those with higher adiposity.

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527 FRAILTY AND MULTIMORBIDITY IN TYPE 2 DIABETES: A UK BIOBANK ANALYSIS

Age and Ageing ◽

10.1093/ageing/afab117.10 ◽

2021 ◽

Vol 50 (Supplement_2) ◽

pp. ii1-ii4

Author(s):

P Hanlon ◽

B D Jani ◽

E Butterly ◽

B Nicholl ◽

J Lewsey ◽

...

Keyword(s):

Type 2 Diabetes ◽

Frailty Index ◽

Baseline Risk ◽

Uk Biobank ◽

Adverse Cardiovascular Event ◽

Frailty Phenotype ◽

Long Term Conditions ◽

Treatment Targets ◽

The Relationship

Abstract Introduction Frailty and multimorbidity are common in type 2 diabetes (T2D), including people <65 years. Guidelines recommend adjustment of treatment targets in people with frailty or multimorbidity, however guidelines do not differentiate these two related states. It is unclear how recommendations to adjust treatment targets in people with frailty or multimorbidity should be applied to different ages. It is also not known if the relationship between HbA1c and outcomes is similar in people with and without frailty. We assess implications of frailty/multimorbidity in middle/older-aged people with T2D. Methods Analysis of UK Biobank participants (n = 20,566) with T2D aged 40-72 years comparing two frailty measures (frailty phenotype and frailty index) and two multimorbidity measures (Charlson comorbidity index and a simply count of 40 long-term conditions (LTCs)). Outomes: mortality (all-cause, cardiovascular- and cancer-related mortality), Major Adverse Cardiovascular Event (MACE), hospitalization with hypoglycaemia or fall/fracture. Results Measure choice influenced the population identified: 42% of participants were identified as frail/multimorbid by at least one measure; only 2.2% were identified by all four measures. Both frailty and multimorbidity, by all measures, were prevalent throughout the age range studied. Each measure was associated with mortality, MACE, hypoglycaemia and falls. The absolute 5-year mortality risk was higher in older versus younger participants with a given level of frailty (e.g. 1.9%, and 9.9% in men aged 45 and 65, respectively, using frailty phenotype) or multimorbidity (e.g. 1.3%, and 7.8% in men with 4 LTCs aged 45 and 65, respectively). Using frailty phenotype, the relationship between higher HbA1c and mortality was stronger in frail compared with pre-frail or robust participants. Conclusion Assessment of frailty/multimorbidity should be embedded within routine management of middle-aged and older people with T2D. Method of identification as well as features such as age impact baseline risk and should influence clinical decisions (e.g. glycaemic control).

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