To provide global, regional, and country-level estimates of diabetes prevalence and health expenditures for 2021 and projections for 2045.Methods: A total of 219 data sources meeting pre-established quality criteria reporting research conducted between 2005 and 2020 and representing 215 countries and territories were identified. For countries without data meeting quality criteria, estimates were extrapolated from countries with similar economies, ethnicity, geography and language. Logistic
We conducted a three-stage genetic study to identify susceptibility loci for type 2 diabetes (T2D) in East Asian populations. The first stage meta-analysis of eight T2D genome-wide association studies (6,952 cases and 11,865 controls) was followed by a second stage in silico replication analysis (5,843 cases and 4,574 controls) and a stage 3 de novo replication analysis (12,284 cases and 13,172 controls). The combined analysis identified eight new T2D loci reaching genome-wide significance, which were mapped in or near GLIS3, PEPD, FITM2-R3HDML-HNF4A, KCNK16, MAEA, GCC1-PAX4, PSMD6 and ZFAND3. GLIS3, involved in pancreatic beta cell development and insulin gene expression1,2, is known for its association with fasting glucose levels3,4. The evidence of T2D association for PEPD5 and HNF4A6,7 has been detected in previous studies. KCNK16 may regulate glucose-dependent insulin secretion in the pancreas. These findings derived from East Asians provide new perspectives on the etiology of T2D.
Diabetic patients have a high prevalence of NAFLD and advanced fibrosis. Those with obesity and dyslipidaemia are at particularly high risk and may be the target for liver assessment. Our data support screening for NAFLD and/or advanced fibrosis in patients with type 2 diabetes.
SUMMARY
Meta-analyses of genome-wide association studies (GWAS) have identified >240
loci associated with type 2 diabetes (T2D)
1
,
2
, however most loci have been identified in analyses
of European-ancestry individuals. To examine T2D risk in East Asian individuals, we
meta-analyzed GWAS data in 77,418 cases and 356,122 controls. In the main analysis, we
identified 301 distinct association signals at 183 loci, and across T2D association models with
and without consideration of body mass index and sex, we identified 61 loci newly implicated in
T2D predisposition. Common variants associated with T2D in both East Asian and European
populations exhibited strongly correlated effect sizes. New associations include signals
in/near
GDAP1
,
PTF1A
,
SIX3, ALDH2,
a
microRNA cluster, and genes that affect muscle and adipose differentiation
3
. At another locus, eQTLs at two overlapping T2D signals affect
two genes,
NKX6-3
and
ANK1
, in different tissues
4
–
6
.
Association studies in diverse populations identify additional loci and elucidate disease
genes, biology, and pathways.
for the Depression Screening Data (DEPRESSD) PHQ Collaboration IMPORTANCE The Patient Health Questionnaire depression module (PHQ-9) is a 9-item self-administered instrument used for detecting depression and assessing severity of depression. The Patient Health Questionnaire-2 (PHQ-2) consists of the first 2 items of the PHQ-9 (which assess the frequency of depressed mood and anhedonia) and can be used as a first step to identify patients for evaluation with the full PHQ-9.OBJECTIVE To estimate PHQ-2 accuracy alone and combined with the PHQ-9 for detecting major depression.
Aims/hypothesisFTO harbours the strongest known obesity-susceptibility locus in Europeans. While there is growing evidence for a role for FTO in obesity risk in Asians, its association with type 2 diabetes, independently of BMI, remains inconsistent. To test whether there is an association of the FTO locus with obesity and type 2 diabetes, we conducted a meta-analysis of 32 populations including 96,551 East and South Asians.MethodsAll studies published on the association between FTO-rs9939609 (or proxy [r2 > 0.98]) and BMI, obesity or type 2 diabetes in East or South Asians were invited. Each study group analysed their data according to a standardised analysis plan. Association with type 2 diabetes was also adjusted for BMI. Random-effects meta-analyses were performed to pool all effect sizes.ResultsThe FTO-rs9939609 minor allele increased risk of obesity by 1.25-fold/allele (p = 9.0 × 10−19), overweight by 1.13-fold/allele (p = 1.0 × 10−11) and type 2 diabetes by 1.15-fold/allele (p = 5.5 × 10−8). The association with type 2 diabetes was attenuated after adjustment for BMI (OR 1.10-fold/allele, p = 6.6 × 10−5). The FTO-rs9939609 minor allele increased BMI by 0.26 kg/m2 per allele (p = 2.8 × 10−17), WHR by 0.003/allele (p = 1.2 × 10−6), and body fat percentage by 0.31%/allele (p = 0.0005). Associations were similar using dominant models. While the minor allele is less common in East Asians (12–20%) than South Asians (30–33%), the effect of FTO variation on obesity-related traits and type 2 diabetes was similar in the two populations.Conclusions/interpretationFTO is associated with increased risk of obesity and type 2 diabetes, with effect sizes similar in East and South Asians and similar to those observed in Europeans. Furthermore, FTO is also associated with type 2 diabetes independently of BMI.Electronic supplementary materialThe online version of this article (doi:10.1007/s00125-011-2370-7) contains peer-reviewed but unedited supplementary material, which is available to authorised users.
BackgroundItem 9 of the Patient Health Questionnaire-9 (PHQ-9) queries about thoughts of death and self-harm, but not suicidality. Although it is sometimes used to assess suicide risk, most positive responses are not associated with suicidality. The PHQ-8, which omits Item 9, is thus increasingly used in research. We assessed equivalency of total score correlations and the diagnostic accuracy to detect major depression of the PHQ-8 and PHQ-9.MethodsWe conducted an individual patient data meta-analysis. We fit bivariate random-effects models to assess diagnostic accuracy.Results16 742 participants (2097 major depression cases) from 54 studies were included. The correlation between PHQ-8 and PHQ-9 scores was 0.996 (95% confidence interval 0.996 to 0.996). The standard cutoff score of 10 for the PHQ-9 maximized sensitivity + specificity for the PHQ-8 among studies that used a semi-structured diagnostic interview reference standard (N = 27). At cutoff 10, the PHQ-8 was less sensitive by 0.02 (−0.06 to 0.00) and more specific by 0.01 (0.00 to 0.01) among those studies (N = 27), with similar results for studies that used other types of interviews (N = 27). For all 54 primary studies combined, across all cutoffs, the PHQ-8 was less sensitive than the PHQ-9 by 0.00 to 0.05 (0.03 at cutoff 10), and specificity was within 0.01 for all cutoffs (0.00 to 0.01).ConclusionsPHQ-8 and PHQ-9 total scores were similar. Sensitivity may be minimally reduced with the PHQ-8, but specificity is similar.
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