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An important question in human genetics is the extent to which genes causing monogenic forms of disease harbor common variants that may contribute to the more typical form of that disease. We aimed to comprehensively evaluate the extent to which common variation in the six known maturity-onset diabetes of the young (MODY) genes, which cause a monogenic form of type 2 diabetes, is associated with type 2 diabetes. Specifically, we determined patterns of common sequence variation in the genes encoding Gck, Ipf1, Tcf2, and NeuroD1 (MODY2 and MODY4-MODY6, respectively), selected a comprehensive set of 107 tag single nucleotide polymorphisms (SNPs) that captured common variation, and genotyped each in 4,206 patients and control subjects from Sweden, Finland, and Canada (including family-based studies and unrelated case-control subjects). All SNPs with a nominal P value <0.1 for association to type 2 diabetes in this initial screen were then genotyped in an additional 4,470 subjects from North America and Poland. Of 30 nominally significant SNPs from the initial sample, 8 achieved consistent results in the replication sample. We found the strongest effect at rs757210 in intron 2 of TCF2, with corrected P values <0.01 for an odds ratio (OR) of 1.13. This association was observed again in an independent sample of 5,891 unrelated case and control subjects and 500 families from the U.K., for an overall OR of 1.12 and a P value <10[sup -e] in >15,000 samples. We combined these results with our previous studies on HNF4α and TCF1 and explicitly tested for gene-gene interactions among these variants and with several known type 2 diabetes susceptibility loci, and we found no genetic interactions between these six genes. We conclude that although rare variants in these six genes explain most cases of MODY, common variants in these same genes contribute very modestly, if at all, to the common form of type 2 diabetes. Diabetes 56:685-693, 2007 [ABSTRACT FROM AUTHOR]

Background: In response to COVID-19, the Swedish government imposed few travel and mobility restrictions. This contrasted with its Scandinavian neighbours which implemented stringent restrictions. The influence these different approaches had on mobility, and thus on COVID-19 mortality was investigated., Methods: Datasets indicating restriction severity and community mobility were examined; Google's 'Community Movement Reports' (CMR) show activity at key location categories; the Oxford COVID-19 Government Response Tracker collates legislative restrictions into a 'Stringency Index' (SI)., Results: CMR mobility categories were negatively correlated with COVID-19 mortality. The strongest correlations were obtained by negatively time lagging mortality data, suggesting restrictions had a delayed influence. During the 'first wave' a model using SI (AIC 632.87) proved favorable to one using contemporaneous CMR data and SI (AIC 1193.84), or lagged CMR data and SI (AIC 642.35). Validation using 'second wave' data confirmed this; the model using SI solely again being optimal (RMSE: 0.2486 vs. 0.522 and 104.62). Cross-country differences were apparent in all models; Swedish data, independent of SI and CMR, proved significant throughout. There was a significant association for Sweden and the death number across models., Conclusion: SI may provide a broader, more accurate, representation of changes in movement in response to COVID-19 restrictions., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

Aims/hypothesis: It is well established that physical activity, abdominal ectopic fat and glycaemic regulation are related but the underlying structure of these relationships is unclear. The previously proposed twin-cycle hypothesis (TC) provides a mechanistic basis for impairment in glycaemic control through the interactions of substrate availability, substrate metabolism and abdominal ectopic fat accumulation. Here, we hypothesise that the effect of physical activity in glucose regulation is mediated by the twin-cycle. We aimed to examine this notion in the Innovative Medicines Initiative Diabetes Research on Patient Stratification (IMI DIRECT) Consortium cohorts comprised of participants with normal or impaired glucose regulation (cohort 1: N ≤ 920) or with recently diagnosed type 2 diabetes (cohort 2: N ≤ 435)., Methods: We defined a structural equation model that describes the TC and fitted this within the IMI DIRECT dataset. A second model, twin-cycle plus physical activity (TC-PA), to assess the extent to which the effects of physical activity in glycaemic regulation are mediated by components in the twin-cycle, was also fitted. Beta cell function, insulin sensitivity and glycaemic control were modelled from frequently sampled 75 g OGTTs (fsOGTTs) and mixed-meal tolerance tests (MMTTs) in participants without and with diabetes, respectively. Abdominal fat distribution was assessed using MRI, and physical activity through wrist-worn triaxial accelerometry. Results are presented as standardised beta coefficients, SE and p values, respectively., Results: The TC and TC-PA models showed better fit than null models (TC: χ 2  = 242, p = 0.004 and χ 2  = 63, p = 0.001 in cohort 1 and 2, respectively; TC-PA: χ 2  = 180, p = 0.041 and χ 2  = 60, p = 0.008 in cohort 1 and 2, respectively). The association of physical activity with glycaemic control was primarily mediated by variables in the liver fat cycle., Conclusions/interpretation: These analyses partially support the mechanisms proposed in the twin-cycle model and highlight mechanistic pathways through which insulin sensitivity and liver fat mediate the association between physical activity and glycaemic control.