Aaron Leong

Vitamin D and Risk of Multiple Sclerosis: A Mendelian Randomization Study

Background Observational studies have demonstrated an association between decreased vitamin D level and risk of multiple sclerosis (MS); however, it remains unclear whether this relationship is causal. We undertook a Mendelian randomization (MR) study to evaluate whether genetically lowered vitamin D level influences the risk of MS. Methods and Findings We identified single nucleotide polymorphisms (SNPs) associated with 25-hydroxyvitamin D (25OHD) level from SUNLIGHT, the largest (n = 33,996) genome-wide association study to date for vitamin D. Four SNPs were genome-wide significant for 25OHD level (p-values ranging from 6 × 10−10 to 2 × 10−109), and all four SNPs lay in, or near, genes strongly implicated in separate mechanisms influencing 25OHD. We then ascertained their effect on 25OHD level in 2,347 participants from a population-based cohort, the Canadian Multicentre Osteoporosis Study, and tested the extent to which the 25OHD-decreasing alleles explained variation in 25OHD level. We found that the count of 25OHD-decreasing alleles across these four SNPs was strongly associated with lower 25OHD level (n = 2,347, F-test statistic = 49.7, p = 2.4 × 10−12). Next, we conducted an MR study to describe the effect of genetically lowered 25OHD on the odds of MS in the International Multiple Sclerosis Genetics Consortium study, the largest genetic association study to date for MS (including up to 14,498 cases and 24,091 healthy controls). Alleles were weighted by their relative effect on 25OHD level, and sensitivity analyses were performed to test MR assumptions. MR analyses found that each genetically determined one-standard-deviation decrease in log-transformed 25OHD level conferred a 2.0-fold increase in the odds of MS (95% CI: 1.7–2.5; p = 7.7 × 10−12; I 2 = 63%, 95% CI: 0%–88%). This result persisted in sensitivity analyses excluding SNPs possibly influenced by population stratification or pleiotropy (odds ratio [OR] = 1.7, 95% CI: 1.3–2.2; p = 2.3 × 10−5; I 2 = 47%, 95% CI: 0%–85%) and including only SNPs involved in 25OHD synthesis or metabolism (ORsynthesis = 2.1, 95% CI: 1.6–2.6, p = 1 × 10−9; ORmetabolism = 1.9, 95% CI: 1.3–2.7, p = 0.002). While these sensitivity analyses decreased the possibility that pleiotropy may have biased the results, residual pleiotropy is difficult to exclude entirely. Conclusions A genetically lowered 25OHD level is strongly associated with increased susceptibility to MS. Whether vitamin D sufficiency can delay, or prevent, MS onset merits further investigation in long-term randomized controlled trials.

Systematic Review and Meta-Analysis of Validation Studies on a Diabetes Case Definition from Health Administrative Records

Objectives Health administrative data are frequently used for diabetes surveillance. We aimed to determine the sensitivity and specificity of a commonly-used diabetes case definition (two physician claims or one hospital discharge abstract record within a two-year period) and their potential effect on prevalence estimation. Methods Following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, we searched Medline (from 1950) and Embase (from 1980) databases for validation studies through August 2012 (keywords: “diabetes mellitus”; “administrative databases”; “validation studies”). Reviewers abstracted data with standardized forms and assessed quality using Quality Assessment of Diagnostic Accuracy Studies (QUADAS) criteria. A generalized linear model approach to random-effects bivariate regression meta-analysis was used to pool sensitivity and specificity estimates. We applied correction factors derived from pooled sensitivity and specificity estimates to prevalence estimates from national surveillance reports and projected prevalence estimates over 10 years (to 2018). Results The search strategy identified 1423 abstracts among which 11 studies were deemed relevant and reviewed; 6 of these reported sensitivity and specificity allowing pooling in a meta-analysis. Compared to surveys or medical records, sensitivity was 82.3% (95%CI 75.8, 87.4) and specificity was 97.9% (95%CI 96.5, 98.8). The diabetes case definition underestimated prevalence when it was ≤10.6% and overestimated prevalence otherwise. Conclusion The diabetes case definition examined misses up to one fifth of diabetes cases and wrongly identifies diabetes in approximately 2% of the population. This may be sufficiently sensitive and specific for surveillance purposes, in particular monitoring prevalence trends. Applying correction factors to adjust prevalence estimates from this definition may be helpful to increase accuracy of estimates.

Spousal diabetes as a diabetes risk factor: A systematic review and meta-analysis

BackgroundDiabetes history in biologically-related individuals increases diabetes risk. We assessed diabetes concordance in spouses (that is, biologically unrelated family members) to gauge the importance of socioenvironmental factors.MethodsWe selected cross-sectional, case–control and cohort studies examining spousal association for diabetes and/or prediabetes (impaired fasting glucose or impaired glucose tolerance), indexed in Medline, Embase or Scopus (1 January 1997 to 28 February 2013). Effect estimates (that is, odds ratios, incidence rate ratios, and so on) with body mass index (BMI) adjustment were pooled separately from those without BMI adjustment (random effects models) to distinguish BMI-dependent and independent concordance.ResultsSearches yielded 2,705 articles; six were retained (n = 75,498 couples) for systematic review and five for meta-analysis. Concordance was lowest in a study that relied on women’s reports of diabetes in themselves and their spouses (effect estimate 1.1, 95% CI 1.0 to 1.30) and highest in a study with systematic assessment of glucose tolerance (2.11, 95% CI 1.74 to 5.10). The random-effects pooled estimate adjusted for age and other covariates but not BMI was 1.26 (95% CI 1.08 to 1.45). The estimate with BMI adjustment was lower (1.18, 95% CI 0.97 to 1.40). Two studies assessing between-spouse associations of diabetes/prediabetes determined by glucose testing reported high concordance (OR 1.92, 95% CI 1.55 to 2.37 without BMI adjustment; 2.32, 95% CI 1.87 to 3.98 with BMI adjustment). Two studies did not distinguish type 1 and type 2 diabetes. However given that around 95% of adults is type 2, this is unlikely to have influenced the results.ConclusionsOur pooled estimate suggests that a spousal history of diabetes is associated with a 26% diabetes risk increase. Recognizing shared risk between spouses may improve diabetes detection and motivate couples to increase collaborative efforts to optimize eating and physical activity habits.

A Mendelian randomization study of the effect of type-2 diabetes on coronary heart disease

In observational studies, type-2 diabetes (T2D) is associated with an increased risk of coronary heart disease (CHD), yet interventional trials have shown no clear effect of glucose-lowering on CHD. Confounding may have therefore influenced these observational estimates. Here we use Mendelian randomization to obtain unconfounded estimates of the influence of T2D and fasting glucose (FG) on CHD risk. Using multiple genetic variants associated with T2D and FG, we find that risk of T2D increases CHD risk (odds ratio (OR)=1.11 (1.05–1.17), per unit increase in odds of T2D, P=8.8 × 10−5; using data from 34,840/114,981 T2D cases/controls and 63,746/130,681 CHD cases/controls). FG in non-diabetic individuals tends to increase CHD risk (OR=1.15 (1.00–1.32), per mmol·per l, P=0.05; 133,010 non-diabetic individuals and 63,746/130,681 CHD cases/controls). These findings provide evidence supporting a causal relationship between T2D and CHD and suggest that long-term trials may be required to discern the effects of T2D therapies on CHD risk.

Strategies to optimize participation in diabetes prevention programs following gestational diabetes: a focus group study.

Objective We performed a qualitative study among women within 5 years of Gestational Diabetes (GDM) diagnosis. Our aim was to identify the key elements that would enhance participation in a type 2 diabetes (DM2) prevention program. Research Design and Methods Potential participants received up to three invitation letters from their GDM physician. Four focus groups were held. Discussants were invited to comment on potential facilitators/barriers to participation and were probed on attitudes towards meal replacement and Internet/social media tools. Recurring themes were identified through qualitative content analysis of discussion transcripts. Results Among the 1,201 contacted and 79 eligible/interested, 29 women attended a focus group discussion. More than half of discussants were overweight/obese, and less than half were physically active. For DM2 prevention, a strong need for social support to achieve changes in dietary and physical activity habits was expressed. In this regard, face-to-face interactions with peers and professionals were preferred, with adjunctive roles for Internet/social media. Further, direct participation of partners/spouses in a DM2 prevention program was viewed as important to enhance support for behavioural change at home. Discussants highlighted work and child-related responsibilities as potential barriers to participation, and emphasized the importance of childcare support to allow attendance. Meal replacements were viewed with little interest, with concerns that their use would provide a poor example of eating behaviour to children. Conclusions Among women within 5 years of a GDM diagnosis who participated in a focus group discussion, participation in a DM2 prevention program would be enhanced by face-to-face interactions with professionals and peers, provision of childcare support, and inclusion of spouses/partners.

Estimating the Population Prevalence of Diagnosed and Undiagnosed Diabetes

OBJECTIVE Health administrative data are frequently used for diabetes surveillance, but validation studies are limited, and undiagnosed diabetes has not been considered in previous studies. We compared the test properties of an administrative definition with self-reported diabetes and estimated prevalence of undiagnosed diabetes by measuring glucose levels in mailed-in capillary blood samples. RESEARCH DESIGN AND METHODS A stratified random sample of 6,247 individuals (Quebec province) was surveyed by telephone and asked to mail in fasting blood samples on filter paper to a central laboratory. An administrative definition was applied (two physician claims or one hospitalization for diabetes within a 2-year period) and compared with self-reported diabetes alone and with self-reported diabetes or elevated blood glucose level (≥7 mmol/L). Population-level prevalence was estimated with the use of the administrative definition corrected for its sensitivity and specificity. RESULTS Compared with self-reported diabetes, sensitivity and specificity were 84.3% (95% CI 79.3–88.5%) and 97.9% (97.4–98.4%), respectively. Compared with diabetes by self-report and/or glucose testing, sensitivity was lower at 58.2% (52.2–64.6%), whereas specificity was similar at 98.7% (98.0–99.3%). Adjusted for sampling weights, population-level prevalence of physician-diagnosed diabetes was 7.2% (6.3–8.0%). Prevalence of total diabetes (physician-diagnosed and undiagnosed) was 13.4% (11.7–15.0%), indicating that ∼40% of diabetes cases are undiagnosed. CONCLUSIONS A substantial proportion of diabetes cases are missed by surveillance methods that use health administrative databases. This finding is concerning because individuals with undiagnosed diabetes are likely to have a delay in treatment and, thus, a higher risk for diabetes-related complications.

Genetically Driven Hyperglycemia Increases Risk of Coronary Artery Disease Separately From Type 2 Diabetes

OBJECTIVE This study tested the hypothesis that genetically raised hyperglycemia increases coronary artery disease (CAD) risk separately from the risk conferred by type 2 diabetes as a whole. RESEARCH DESIGN AND METHODS We conducted a Mendelian randomization (MR) analysis using summary-level statistics from the largest published meta-analyses of genome-wide association studies (GWAS) for fasting glucose (FG) (n = 133,010 participants free of diabetes) and CAD (n = 63,746 case subjects and 130,681 control subjects) of predominantly European ancestry. FG-increasing variants associated with type 2 diabetes from the largest GWAS for type 2 diabetes were excluded. Variants with pleiotropic effects on other CAD risk factors (blood lipids, blood pressure, and obesity) were excluded using summary-level data from the largest published GWAS. Data from the Framingham Heart Study were used to validate the MR instrument and to build an FG genetic risk score (GRS). RESULTS In an instrumental variable analysis comprising 12 FG-raising variants, a 1 mmol/L increase in FG revealed an effect-size estimate of 1.43 CAD odds (95% CI 1.14–1.79). The association was preserved after excluding variants for heterogeneity and pleiotropic effects on other CAD risk factors (odds ratio [OR] 1.33 [95% CI 1.02–1.73]). The 12 FG-increasing variants did not significantly increase type 2 diabetes risk (OR 1.05 [95% CI 0.91–1.23]), and its prevalence was constant across FG GRS quintiles (P = 0.72). CONCLUSIONS Our data support that genetic predisposition to hyperglycemia raises the odds of CAD separately from type 2 diabetes and other CAD risk factors. These findings suggest that modulating glycemia may provide cardiovascular benefit.

Type 2 Diabetes Genetic Predisposition, Obesity, and All-Cause Mortality Risk in the U.S.: A Multiethnic Analysis

OBJECTIVE Type 2 diabetes (T2D) is associated with increased mortality in ethnically diverse populations, although the extent to which this association is genetically determined is unknown. We sought to determine whether T2D-related genetic variants predicted all-cause mortality, even after accounting for BMI, in the Third National Health and Nutrition Examination Survey. RESEARCH DESIGN AND METHODS We modeled mortality risk using a genetic risk score (GRS) from a weighted sum of risk alleles at 38 T2D-related single nucleotide polymorphisms. In age-, sex-, and BMI-adjusted logistic regression models, accounting for the complex survey design, we tested the association with mortality in 6,501 participants. We repeated the analysis within ethnicities (2,528 non-Hispanic white [NHW], 1,979 non-Hispanic black [NHB], and 1,994 Mexican American [MA]) and within BMI categories (<25, 25–30, and ≥30 kg/m2). Significance was set at P < 0.05. RESULTS Over 17 years, 1,556 participants died. GRS was associated with mortality risk (OR 1.04 [95% CI 1.00–1.07] per T2D-associated risk allele, P = 0.05). Within ethnicities, GRS was positively associated with mortality risk in NHW and NHB, but not in MA (0.95 [0.90–1.01], P = 0.07). The negative trend in MA was largely driven by those with BMI <25 kg/m2 (0.91 [0.82–1.00]). In NHW, the positive association was strongest among those with BMI ≥30 kg/m2 (1.07 [1.02–1.12]). CONCLUSIONS In the U.S., a higher T2D genetic risk was associated with increased mortality risk, especially among obese NHW. The underlying genetic basis for mortality likely involves complex interactions with factors related to ethnicity, T2D, and body weight.

A Mendelian randomization study of the effect of type‐2 diabetes and glycemic traits on bone mineral density

Type‐2 diabetes (T2D) is associated in observational studies with both higher bone mineral density (BMD) and higher fracture risk for given BMD. These relationships may however be confounded by factors such as body mass index (BMI). Here we used Mendelian randomization (MR) to obtain non‐confounded estimates of the effect of T2D and glycemic traits on BMD. We identified genetic variants strongly associated with T2D risk (34,840 T2D cases and 114,981 controls) and fasting glucose (133,010 nondiabetic individuals), but not associated with BMI, and determined the effects of these variants on BMD (up to 83,894 individuals). Using these variants as instrumental variables, we found that a genetically‐increased risk of T2D increased femoral neck BMD (+0.034 SD in BMD per unit increase in log‐odds of T2D [95% CI, 0.001 to 0.067; p = 0.044]). Genetically‐increased fasting glucose also increased femoral neck BMD (+0.13 SD in BMD per mmol/L increase in fasting glucose [95% CI, 0.01 to 0.25; p = 0.034]). Similar nonsignificant trends were observed for the effects of T2D and fasting glucose on lumbar spine BMD. Our results indicate that both genetically‐increased T2D risk and genetically‐increased fasting glucose have weak positive effects on BMD.

Hypoglycemia in Diabetes Mellitus as a Coronary Artery Disease Risk Factor in Patients at Elevated Vascular Risk

CONTEXT Although clinical trials have shown that hypoglycemia is associated with coronary artery disease (CAD), little is known whether hypoglycemia is a CAD risk factor in primary care. OBJECTIVE We sought to determine whether previous hypoglycemia was associated with incident CAD, and whether this association differed in patients of different underlying vascular risk. DESIGN, SETTING AND PARTICIPANTS This is a longitudinal cohort study of diabetes patients without CAD before January 1, 2006 (n = 9173) followed at an academic network of 13 primary care practices from January 1, 2006 to June 30, 2012. Hypoglycemic events before January 1, 2006 were identified via International Classification of Diseases Ninth Revision codes from emergency department, inpatient and outpatient visits. MAIN OUTCOME MEASURE Patients were followed until incident CAD or June 30, 2012. Cox regression with time interaction was used to determine the association between hypoglycemia and CAD (significance set at P ≤ .05). We then tested the association among high vascular risk patients (age ≥ 55 y, hemoglobin A1c ≥ 7.5%, ≥2 risk factors [dyslipidemia, hypertension or obesity]), a subset of high vascular risk patients aged 65 years or older, and the remaining patients with lower vascular risk. RESULTS Three percent of patients (n = 285) had previous hypoglycemia. Hypoglycemia was associated with a 2-fold CAD risk (hazard ratio [HR] 2.15; 95% confidence interval [95%CI] 1.24-3.74), adjusting for time interaction and vascular risk factors. Among high vascular risk patients, the risk was 3-fold (HR 3.01 [95%CI 1.15-7.91], n = 1823 [20% of cohort]), and over 4-fold (HR 4.62 [95%CI 1.65-12.9], n = 996) in the subset aged more than or equal to 65 years. No association was found in the remaining 80% of the cohort with lower vascular risk. CONCLUSIONS Previous hypoglycemia was associated with CAD among high vascular risk patients. Hypoglycemia may not be a CAD risk factor for the majority of primary care patients with lower underlying vascular risk.